1. bookVolume 14 (2020): Edition 1 (February 2020)
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Digital image processing technique to measure the range of motion of the elbow

Publié en ligne: 13 Jul 2020
Volume & Edition: Volume 14 (2020) - Edition 1 (February 2020)
Pages: 37 - 44
Détails du magazine
License
Format
Magazine
eISSN
1875-855X
Première parution
01 Jun 2007
Périodicité
6 fois par an
Langues
Anglais

The elbow joint is a hinge joint that allows single plane of movement: flexion and extension. Intra- and extra-articular disease such as elbow contracture and fracture can cause functional impairment of this joint. Range of motion (ROM) is an objective measurement of the elbow function and it is part of a scoring system [1].

Assessment of measurement methods for elbow ROM has been reported in the literature. Radiographic examination gives the most accurate result, but it is not the first choice in daily practice for evaluating elbow function due to the risk from radiation exposure [2]. A standard clinical goniometer, universal and digital type, is very popular because of its availability. Inter- and intra-rater reliability of the goniometer is also high as indicated by recent systematic review [2, 3]. An inclinometer is a practical device, but it should be used by a trained professional. Moreover, a digital inclinometer especially a dual-type inclinometer is quite expensive.

Photography-based methods have been proposed and validated in many studies [1, 4, 5, 6, 7, 8]. The concept of this method is to take a photo or video of elbow in extension and flexion position, and then to draw lines of arm and forearm axis on images by the assessor using a visible reference point and calculating the angle between these two lines. ROM value is obtained from flexion angle minus extension angle. This provides many benefits such as being inexpensive, durable, easy data storage and transfer to allow multiple observers, and possibility of measurement at any time in any location [4, 6]. Image capturing devices can be a digital camera or smartphone, as has been already validated for measuring elbow ROM [1, 8]. However, accuracy of these measurement methods depends on observer's experience [7].

Digital image processing technique (DIPT) is a method of using computer software to analyze digital images for several purposes such as image feature extraction, classification, or pattern recognition. ROM measurement by using DIPT is the innovative concept of the present study. This method can be applied to a patient who is in a remote area taking and sending his or her elbow image in flexed–extended position via a smart device such as a smartphone or a tablet to a hospital database. Then image analysis software is used to automatically measure extension and flexion angles and send a report to a corresponding physician. We anticipated that the DIPT method can be used interchangeably using goniometer and inclinometer. The DIPT method can also reduce observational bias, examination time, labor burden, and cost of transportation.

The present study aimed to develop a DIPT for measuring elbow ROM, and to assess validity and reliability of this technique compared with standard digital goniometer and inclinometer which are instruments for measuring arc of motion in daily clinical practice.

Materials and methods

This study was approved by the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand (Certificate of Approval No. 198/2019). Participants were recruited from students and staff in the university by poster announcement. Inclusion criteria included all volunteer participants aged over 18 years who were able to lift their shoulder perpendicular to the floor and hold it still in an elbow extension and flexion position. Exclusion criteria included those who had deformity of arm and forearm or pain and discomfort at the elbow. Participants were informed about study protocol and risks involved in this study. The written informed consent was provided. Sample size was determined by calculating two-dependent mean sample sizes. Ten degree of elbow motion arc measurement error was considered as minimal clinically important difference (MCID) and used as summative difference. Standard deviation was obtained from the difference between photographic and goniometric measure ments [7]. A total of 14 elbows were required.

A digital goniometer and digital inclinometer were used as reference measuring devices to compare ROM measurements with those from DIPT. All measurements and capturing photographs were conducted on the same day (April 20, 2019) in the orthopedic operating room of King Chulalongkorn Memorial Hospital. Two trained physiotherapists with 2 years’ experience were briefed about the measurement techniques and they practiced the measurements on each other. Both examiners performed goniometer, inclinometer, and ROM measurements on the bilateral elbows of participants. Two research assistants recorded the measurement values on record forms.

<sec id="j_abm-2020-0006_s_001_s_001_s_001_w2aab3b7c28b1b6b1ab1b5b3b1Aa"><div>Digital goniometer</div><p>A digital protractor goniometer with ±0.5° precision (Mediguage) was used. The goniometer was centered on the lateral epicondyle. The proximal part of goniometer pointed at the greater tuberosity of humerus and the distal part pointed at the middle portion of wrist [<a ref-type="bibr" href="#j_abm-2020-0006_ref_002_w2aab3b7c28b1b6b1ab2b2b2Aa">2</a>]. The examiner measured the flexion and extension position of elbow three times for each side.</p></sec><sec id="j_abm-2020-0006_s_001_s_001_s_002_w2aab3b7c28b1b6b1ab1b5b3b2Aa"><div>Digital inclinometer</div><p>A baseline digital inclinometer (Fabrication Enterprises) was calibrated. The measurement technique for the inclinometer was modified from the American Medical Association (AMA) recommendation [<a ref-type="bibr" href="#j_abm-2020-0006_ref_009_w2aab3b7c28b1b6b1ab2b2b9Aa">9</a>]. The participant laid supine on a bed and both elbows hung beyond the edge of the bed. To measure the extension angle, the inclinometer was aligned on the long axis of forearm and set to zero. The participant was then asked to extend his or her elbow and the measurement value was recorded. To measure the flexion angle, the participant fully flexed his or her elbow while the examiner aligned the inclinometer with the forearm, read the flexion angle, and then repeated the same protocol two more times for extension and flexion. Three measurement values for the same limb and same position should be within 5° or 10% of the mean.</p></sec><sec id="j_abm-2020-0006_s_001_s_001_s_003_w2aab3b7c28b1b6b1ab1b5b3b3Aa"><div>Smartphone photography</div><p>The participant stood as close as possible in front of a blue screen to control the horizontal plane of the arm and then performed lateral abduction of the shoulder to 90° perpendicular to the floor. This position is considered as practical for a patient to take a photograph of his or her elbow at home and the monotonous color contrast background should help reduce image processing error. The upper extremity was exposed from shoulder to hand. A photographer took elbow images in with the arm fully extended and fully flexed three times for each position (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_001_w2aab3b7c28b1b6b1ab1b5b3b3b2Aa">Figure 1</a></bold>). The smartphone camera was at the same level of the elbow joint while taking a shot. Participant was told to drop his or her arm to a relaxed position between each photo shot and then raised it again so that the next image could be acquired. All images were taken using a iPhone 6 (Apple) with 8-megapixel rear camera (3,264 × 2,448 pixels, 72 dpi).</p><figure id="j_abm-2020-0006_fig_001_w2aab3b7c28b1b6b1ab1b5b3b3b2Aa" position="float" fig-type="figure"><h2>Figure 1</h2><figCaption><p>Photographic positions. Subject laterally abducted shoulder perpendicular to the floor and fully extended elbow <bold>(A)</bold>. Elbow was maximally flexed <bold>(B)</bold>.</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_abm-2020-0006_fig_001.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=5bbb053dca5cef5a29a9f611bf0a46ee62d441baf4223d107e5afbdda62a3b03" class="mw-100"></img></figure></sec><sec id="j_abm-2020-0006_s_001_s_001_s_004_w2aab3b7c28b1b6b1ab1b5b3b4Aa"><div>Digital image processing technique</div><p>The first step is “line detection,” which is the protocol for finding all possible lines in an image. All upper extremity images were cropped at below wrist level in the distal part and at deltoid muscle insertion in the proximal part. The horizontal and vertical blue areas were deleted from edges to eliminate the blue screen background as much as possible (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_002_w2aab3b7c28b1b6b1ab1b5b3b4b2Aa">Figure 2A</a></bold>). A median filter was applied to reduce noise from the camera and reduce light by converting the colored space from red, green, and blue (RGB) to hue saturation value (HSV) to create a mask with color range (100,0,0) and (180,255,255) in the HSV color space (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_002_w2aab3b7c28b1b6b1ab1b5b3b4b2Aa">Figure 2B</a></bold>). A mask was then applied to find the contour of the skin and clean the noise with a median blur filter (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_002_w2aab3b7c28b1b6b1ab1b5b3b4b2Aa">Figure 2C</a></bold>). Detection of lines was based on a Canny and Hough transformation (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_003_w2aab3b7c28b1b6b1ab1b5b3b4b3Aa">Figures 3A</a></bold> and <bold><a ref-type="fig" href="#j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa">4A</a></bold>) [<a ref-type="bibr" href="#j_abm-2020-0006_ref_010_w2aab3b7c28b1b6b1ab2b2c10Aa">10</a>, <a ref-type="bibr" href="#j_abm-2020-0006_ref_011_w2aab3b7c28b1b6b1ab2b2c11Aa">11</a>]. To improve accuracy, outlier detection was used to eliminate unrelated lines.</p><figure id="j_abm-2020-0006_fig_002_w2aab3b7c28b1b6b1ab1b5b3b4b2Aa" position="float" fig-type="figure"><h2>Figure 2</h2><figCaption><p>Line detection process. <bold>(A)</bold> Cropped image. <bold>(B)</bold> Converting red, green, and blue (RGB) to hue saturation value (HSV). <bold>(C)</bold> Detection of lines using Canny and Hough transformation.</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_abm-2020-0006_fig_002.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=3e1587ed199bd7f78487df0549c7090abab1f6d73b831945468a980bae197aab" class="mw-100"></img></figure><figure id="j_abm-2020-0006_fig_003_w2aab3b7c28b1b6b1ab1b5b3b4b3Aa" position="float" fig-type="figure"><h2>Figure 3</h2><figCaption><p>Angle calculation step for extended elbow image. <bold>(A):</bold> Locate middle points of arm and forearm from one-third of distance of both edges. <bold>(B):</bold> Calculate angle from difference between two slopes.</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_abm-2020-0006_fig_003.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=1b1a21eb94c6763e5eaec24b15e7e084502e581ec557763350ed643e1654bb53" class="mw-100"></img></figure><figure id="j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa" position="float" fig-type="figure"><h2>Figure 4</h2><figCaption><p>Angle calculation step for flexed elbow image. <bold>(A)</bold> Determine cutting point for classifying four reference lines. <bold>(B)</bold> Calculate angle from two slopes.</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_abm-2020-0006_fig_004.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=69ba0fcf8439e2ba27588cfbeecf4f6f3e556a90bebdb0d0e649db9fb7f1f383" class="mw-100"></img></figure><p>After the line detection process, the next step is “angle calculation.” The algorithm for flexion and extension angles is similar. They varied depending on sides. For left flexion, right flexion, left extension, and right extension, the variation are the base lines for detecting upper and lower arms. For both flexion and extension, four base lines (upper arm, lower arm, upper forearm, and lower forearm) are located differently. The protocols for calculation of extension and flexion angles are described as follows.</p><sec id="j_abm-2020-0006_s_001_s_001_s_004_s_001_w2aab3b7c28b1b6b1ab1b5b3b4b6Aa"><div>Extension angle</div><list list-type="custom"><list-item><label>(1)</label><p>Two scan lines, such as a left scan line and a right scan line, were determined. The first scan line was located in one-third distance of the dominate edge (right edge for the left hand and vice versa). The second scan line was a quarter from another edge (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_003_w2aab3b7c28b1b6b1ab1b5b3b4b3Aa">Figure 3A</a></bold>).</p></list-item><list-item><label>(2)</label><p>For both scan lines, we found the cutting points for classifying lines into two groups on each side. The cutting points were determined by the middle point of the skin (calculated from the mask).</p></list-item><list-item><label>(3)</label><p>Lines were partitioned into four groups: top left lines, top right lines, lower left lines, and lower right lines. Between the left edge and the middle point, the intersection of each line and the scan line was used to determine the upper left lines and the lower left lines. A similar method was applied between the right edge and the middle point to determine the upper right lines and the lower right lines.</p></list-item><list-item><label>(4)</label><p>To calculate the angle, the average slopes between the upper lines and the lower lines were calculated. The angle was calculated from the difference between the two slopes (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_003_w2aab3b7c28b1b6b1ab1b5b3b4b3Aa">Figure 3B</a></bold>).</p></list-item></list></sec><sec id="j_abm-2020-0006_s_001_s_001_s_004_s_002_w2aab3b7c28b1b6b1ab1b5b3b4b7Aa"><div>Flexion angle</div><list list-type="custom"><list-item><label>(1)</label><p>A scan line was determined by using a vertical line from 10% of the edge. Either the left edge or right edge was used based on the side of the elbow.</p></list-item><list-item><label>(2)</label><p>The scan line was scanned to find the cutting points for classifying four lines. The top point was determined by the middle point of the forearm. The lower point was determined by the middle point of the arm. The middle point between the empty spaces in the middle was used to partition between the forearm and the arm (dots in <bold><a ref-type="fig" href="#j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa">Figure 4A</a></bold>).</p></list-item><list-item><label>(3)</label><p>For each line, we determined whether the line was a part for the upper or lower line by calculating the intersection at the scan line. The intersection point was then partitioned into 4 groups based on the detection points in the second step: upper top lines, lower top lines, upper low lines, and lower low lines (colored lines in <bold><a ref-type="fig" href="#j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa">Figure 4A</a></bold>).</p></list-item><list-item><label>(4)</label><p>For each group of lines, we found and averaged the slope. There were slopes.</p></list-item><list-item><label>(5)</label><p>We used a slope from the upper top line as the top reference line. This line is likely to be aligned with the ulnar bone. We used an average between the 2 slopes from the lower top lines and lower low lines as a base line. The angle was calculated from the 2 slopes, such as top reference line and base line, using an arctan function (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa">Figure 4B</a></bold>).</p></list-item></list><p>To validate our algorithm, we implemented our design using Python version 3.6. The imaging processing library is OpenCV [OpenCV] version 3.3. The outlier detection was based on local and outlier factor found in the Scikit-learn library version 0.19 [<a ref-type="bibr" href="#j_abm-2020-0006_ref_012_w2aab3b7c28b1b6b1ab2b2c12Aa">12</a>].</p></sec></sec><sec id="j_abm-2020-0006_s_001_s_001_s_005_w2aab3b7c28b1b6b1ab1b5b3b5Aa"><div>Statistical analyses</div><p>Intra- and inter-rater reliability of all methods was computed using an intraclass correlation coefficient (ICC). The model for intrarater reliability of goniometer, inclinometer, and photographic image analysis was “two-way mixed” and “absolute agreement.” Inter-rater reliability of goniometer and inclinometer between two physiotherapists’ analytical models was “two-way random” and “absolute agreement.” Excellent agreement was determined by an ICC value >0.9, good agreement 0.75–0.90, and moderate agreement 0.50–0.90 [<a ref-type="bibr" href="#j_abm-2020-0006_ref_013_w2aab3b7c28b1b6b1ab2b2c13Aa">13</a>]. Reliability test was conducted using IBM SPSS for Windows version 22.</p><p>The average of flexion and extension scores from both examiners and DIPT were used in the analysis. Total ROM value was the flexion angle minus the extension angle. Minimal clinical significance difference for elbow ROM was considered as 10°. Kolmogorov–Smirnov and Shapiro–Wilk tests were used to verify if variables were normally distributed. A paired Student's <italic>t</italic> test and Wilcoxon-signed rank test were used to detect systematic bias between all measurement techniques. Bias and possible range of difference between methods were illustrated using Bland–Altman plot and limits of agreement (LOA) analysis. Bland–Altman analysis was conducted in <italic>R</italic> (R Core Team) using the “blandr” package [<a ref-type="bibr" href="#j_abm-2020-0006_ref_014_w2aab3b7c28b1b6b1ab2b2c14Aa">14</a>, <a ref-type="bibr" href="#j_abm-2020-0006_ref_015_w2aab3b7c28b1b6b1ab2b2c15Aa">15</a>]. DIPT measurement values that were <10° of difference were compared with the other 2 reference methods calculated in percentage.</p></sec></sec></sec><sec id="j_abm-2020-0006_s_002_w2aab3b7c28b1b6b1ab1b6Aa"><div>Results</div><p>Thirty healthy volunteer participants joined this study. After inspecting all images, two participants were removed from final analysis because their elbows were not fully flexed. Ultimately, we used data from a total 56 elbows from 15 male and 13 female participants. The average age was 20.6 years (range: 19–31 years). Mean weight, height, and body mass index were 58.9 kg (range: 39–110 kg), 165.3 cm (range: 150–189 cm), 21.4 kg/cm<sup>2</sup> (range: 16.7–34.0 kg/cm<sup>2</sup>).</p><p>Intrarater ICC of goniometric and inclinometer in flexion and extension position showed excellent agreement between 0.953 and 0.994. Intrarater ICC of DIPT was 0.943 in extension and 0.886 in flexion. There was moderate-to-good inter-rater reliability of extension (E) and flexion (F) angle ICC between the two examiners, 0.862 (E) and 0.738 (F) for goniometer and 0.882 (E) and 0.784 (F) for inclinometer.</p><p>All variable groups, except extension position of inclinometer group (<italic>P</italic> = 0.026), were normally distributed. Mean extension and flexion angles as measured by DIPT were significantly greater than those measured by goniometry and inclinometry (<italic>P</italic> < 0.05), but total ROM was comparable with both reference methods (DIPT vs goniometer <italic>P</italic> = 0.322, DIPT vs inclinometer <italic>P</italic> = 0.534) (<bold><a ref-type="table" href="#j_abm-2020-0006_tab_001_w2aab3b7c28b1b6b1ab1b6b4Aa">Table 1</a></bold>).</p><table-wrap id="j_abm-2020-0006_tab_001_w2aab3b7c28b1b6b1ab1b6b4Aa" position="float"><label>Table 1</label><caption><p>Comparison measurement of digital image processing method with digital goniometer and digital inclinometer</p></caption><table rules="groups"><thead><tr><th align="left" valign="middle"><bold>Angle measurement</bold></th><th align="center" valign="middle"><bold>Digital image processing</bold></th><th align="center" valign="middle"><bold>Digital goniometer</bold></th><th align="center" valign="middle"><bold>Digital inclinometer</bold></th></tr><tr><th align="left" valign="middle" colspan="4"/></tr><tr><th align="center" valign="middle"/><th align="center" valign="middle"><bold>Mean ± SD (range)</bold></th><th align="center" valign="middle"><bold>Mean ± SD (range)</bold></th><th align="center" valign="middle"><bold>Mean ± SD (range)</bold></th></tr></thead><tbody><tr><td align="left" valign="top">Extension</td><td align="center" valign="top">−2.01 ± 6.30 (−16.86 – 8.92)</td><td align="center" valign="top">−6.67 ± 3.48 (−11.83 – 0.28)</td><td align="center" valign="top">−6.74 ± 3.58 (−11.87 – 0.15)</td></tr><tr><td align="left" valign="top">Flexion</td><td align="center" valign="top">146.80 ± 5.20 (137.05 – 157.16)</td><td align="center" valign="top">141.28 ± 4.71 (129.98 – 148.80)</td><td align="center" valign="top">142.79 ± 6.58 (129.97 – 155.97)</td></tr><tr><td align="left" valign="top">Total ROM</td><td align="center" valign="top">148.81 ± 7.72 (135.89 – 164.70)</td><td align="center" valign="top">147.95 ± 6.89 (132.12 – 160.53)</td><td align="center" valign="top">149.55 ± 8.36 (131.63 – 167.27)</td></tr></tbody></table><table-wrap-foot><fn-group><fn><p>ROM, range of motion.</p></fn></fn-group></table-wrap-foot></table-wrap><p>Normality of score differences in image analysis and the goniometer and inclinometer methods were assessed using a Shapiro–Wilk test. All methods demonstrated a normal distribution pattern (<italic>P</italic> = 0.06–0.39).</p><p>Bland–Altman analysis showed extension and flexion angle bias of the DIPT–goniometer 4.51 (95% CI 3.14–5.88), 5.46 (95% CI 4.12–6.80) and DIPT–inclinometer 4.61 (95% CI 3.25–5.96), 3.98 (95% CI 2.45–5.50). Total ROM mean difference of DIPT–goniometer and DIPT–inclinometer was 0.94 (–0.95 to 2.84) and –0.63 (–2.64 to 1.38). Absolute maximal error of flexion and extension angles was 9.81°–11.17° and total ROM angle was 13.84°–15.99°. There were 80.4%–91.1% of DIPT values that were <10° of MCID compared with goniometer and 83.9–87.5% compared with inclinometer (<bold><a ref-type="table" href="#j_abm-2020-0006_tab_002_w2aab3b7c28b1b6b1ab1b6b7Aa">Table 2</a></bold> and <bold><a ref-type="fig" href="#j_abm-2020-0006_fig_005_w2aab3b7c28b1b6b1ab1b6b8Aa">Figures 5</a></bold> and <bold><a ref-type="fig" href="#j_abm-2020-0006_fig_006_w2aab3b7c28b1b6b1ab1b6b9Aa">6</a></bold>).</p><table-wrap id="j_abm-2020-0006_tab_002_w2aab3b7c28b1b6b1ab1b6b7Aa" position="float"><label>Table 2</label><caption><p>Bland–Altman analytic results and percentage of DIPT measurement error within 10° compared with goniometer and inclinometer</p></caption><table rules="groups"><thead><tr><th align="left" valign="top"><bold>Angle measurement</bold></th><th align="center" valign="top"><bold>Mean of difference (95% CI)</bold></th><th align="center" valign="top"><bold>Upper LOA (95% CI)</bold></th><th align="center" valign="top"><bold>Lower LOA (95% CI)</bold></th><th align="center" valign="top"><bold>Absolute maximal error<a ref-type="table-fn" href="#j_abm-2020-0006_table-fn_001_w2aab3b7c28b1b6b1ab1b6b7b3aaAa"><sup>†</sup></a></bold></th><th align="center" valign="top"><bold>Within 10° of error (%)</bold></th></tr></thead><tbody><tr><td align="left" valign="top" colspan="6"><italic>Goniometer</italic></td></tr><tr><td align="left" valign="top">Extension</td><td align="center" valign="top">4.51 (3.14, 5.88)</td><td align="center" valign="top">14.56 (12.2, 16.92)</td><td align="center" valign="top">–5.54 (–7.9, –3.18)</td><td align="center" valign="top">±10.05</td><td align="center" valign="top">91.1</td></tr><tr><td align="left" valign="top">Flexion</td><td align="center" valign="top">5.46 (4.12, 6.80)</td><td align="center" valign="top">15.26 (12.96, 17.57)</td><td align="center" valign="top">–4.35 (–6.66, –2.05)</td><td align="center" valign="top">±9.81</td><td align="center" valign="top">82.1</td></tr><tr><td align="left" valign="top">Total ROM</td><td align="center" valign="top">0.94 (–0.95, 2.84)</td><td align="center" valign="top">14.79 (11.54, 18.04)</td><td align="center" valign="top">–12.90 (–16.16, –9.65)</td><td align="center" valign="top">±13.84</td><td align="center" valign="top">80.4</td></tr><tr><td align="left" valign="top" colspan="6"><italic>Inclinometer</italic></td></tr><tr><td align="left" valign="top">Extension</td><td align="center" valign="top">4.61 (3.25, 5.96)</td><td align="center" valign="top">14.53 (12.2, 16.86)</td><td align="center" valign="top">–5.32 (–7.65, –2.99)</td><td align="center" valign="top">±9.93</td><td align="center" valign="top">87.5</td></tr><tr><td align="left" valign="top">Flexion</td><td align="center" valign="top">3.98 (2.45, 5.50)</td><td align="center" valign="top">15.15 (12.52, 17.77)</td><td align="center" valign="top">–7.19 (–9.81, –4.57)</td><td align="center" valign="top">±11.17</td><td align="center" valign="top">85.7</td></tr><tr><td align="left" valign="top">Total ROM</td><td align="center" valign="top">–0.63 (–2.64, 1.38)</td><td align="center" valign="top">14.10 (10.64, 17.56)</td><td align="center" valign="top">–15.36 (–18.82, –11.9)</td><td align="center" valign="top">±15.99</td><td align="center" valign="top">83.9</td></tr></tbody></table><table-wrap-foot><fn-group><fn id="j_abm-2020-0006_table-fn_001_w2aab3b7c28b1b6b1ab1b6b7b3aaAa"><label>†</label><p>Absolute maximal error = Mean – lower LOA.</p></fn><fn><p>CI, confidence interval; LOA, limit of agreement; ROM, range of motion.</p></fn></fn-group></table-wrap-foot></table-wrap><figure id="j_abm-2020-0006_fig_005_w2aab3b7c28b1b6b1ab1b6b8Aa" position="float" fig-type="figure"><h2>Figure 5</h2><figCaption><p>Bland–Altman plot of digital image analysis and goniometer. <bold>(A)</bold> Extension. <bold>(B)</bold> Flexion. <bold>(C)</bold> Elbow range of motion (ROM).</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_abm-2020-0006_fig_005.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=696885a85a5a664daac922f3b127b97dc634c6a645a73c42a2cf77363d5ee622" class="mw-100"></img></figure><figure id="j_abm-2020-0006_fig_006_w2aab3b7c28b1b6b1ab1b6b9Aa" position="float" fig-type="figure"><h2>Figure 6</h2><figCaption><p>Bland–Altman plot of digital image analysis and inclinometer. <bold>(A)</bold> Extension. <bold>(B):</bold> Flexion. <bold>(C):</bold> Elbow range of motion (ROM).</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_abm-2020-0006_fig_006.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=705cd072475ac8654cedc226b1056d2c6f6e761fecde42ac97047e8a70f58937" class="mw-100"></img></figure></sec><sec id="j_abm-2020-0006_s_003_w2aab3b7c28b1b6b1ab1b7Aa"><div>Discussion</div><p>There are several advantages of using photography-based ROM measurement, especially in the era of telemedicine. Innovative methods to collect data remotely from a patient have been popularized in recent years. Physicians can assess their patients’ function and make suggestion via Internet portal without having patients come to the clinic. Photography- and video-based ROM measurement method required human observers who need proper training to achieve high accuracy (7). Most photographic–goniometric methods use bony or alternative landmarks for drawing two reference lines that may be difficult to locate in some cases (1, 4, 5, 7). The present study aimed to solve these observer-related problems using DIPT.</p><p>The present study has some limitations. First, DIPT protocol assesses only the active ROM. An examiner is needed to perform passive ROM measurement. Second, some participants may not produce their best effort, do not understand instructions clearly, and do not extend or flex their elbow fully. We needed to exclude four images from the analysis. Third, the extension rod as recommended by AMA was not available for digital inclinometer used in the current study.</p><p>DIPT measurement of flexion and extension had higher bias around 4°–5° than in the other methods. There are various explanations for this deviation. First is the difference in vertex location, and goniometer and inclinometer measurements begin with localizing lateral epicondyle as vertex of angle and then projecting its arm to distal and proximal bony landmark. DIPT is different from reference methods, it uses extremity contour to create proximal arm and distal forearm line, and the vertex is intersected between these lines. Second, the dorsal surface of the forearm is thin and close to ulnar shaft alignment which affects distal reference line when calculating angle using DIPT. Also, vertex of goniometer and inclinometer angles lies anteriorly compared with ulnar bone shaft line. This is demonstrated from geometric illustration obtained using fluoroscopic images of the elbow which use similar DIPT protocol for drawing angle alignment (<bold><a ref-type="fig" href="#j_abm-2020-0006_fig_007_w2aab3b7c28b1b6b1ab1b7b4Aa">Figures 7A</a></bold> and <bold><a ref-type="fig" href="#j_abm-2020-0006_fig_007_w2aab3b7c28b1b6b1ab1b7b4Aa">7B</a></bold>). Another possible cause can be found from images review, and some participants minimally flexed instead of fully extended their elbows in extension image, probably because they used biceps muscle function to control shoulder joint in the abduction plane.</p><figure id="j_abm-2020-0006_fig_007_w2aab3b7c28b1b6b1ab1b7b4Aa" position="float" fig-type="figure"><h2>Figure 7</h2><figCaption><p>Conceptual illustration of systematic measurement bias between landmark-based method, goniometer and inclinometer, and contour-based DIPT. Green circles are lateral epicondyle location and green lines are imaginary lines of goniometer and inclinometer measurements. Pink lines are the result of using DIPT on fluoroscopic image. <bold>(A)</bold> Extension image. <bold>(B)</bold> Flexion image.</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_abm-2020-0006_fig_007.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_007.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=6796ba85afce47181129cd974ed16420adf33828b330e8ce99e92b2a88c0ee2a" class="mw-100"></img></figure><p>Total ROM had comparable result with reference methods, but had an absolute error >10° margin of MCID for elbow joint. Total ROM is the calculated value from flexion angle minus extension angle, so the error is combination between these two values. Twenty from total 116 DIPT measurements, 11 compared with goniometer and 9 compared with inclinometer, had difference >10°. These can be divided into 3 groups: group 1 denotes lower extension angle and higher flexion angle; group 2 denotes higher extension angle and lower flexion angle; and group 3 denotes higher extension and flexion angles. There were 8, 7, and 5 measurements in group 1, group 2, and group 3, respectively. Of note, 15 of 20 measurements had higher value and more effect than lower value, and other 5 measurements had nearly equal effect between higher and lower values. This can be speculated that significant difference of total ROM between DIPT measurement and reference methods occurred because DIPT measurement tended to have higher value of either flexion or extension angle than goniometer and inclinometer measurements.</p><p>There are several studies using photograph for elbow arc of motion measurement with variety of methods (<bold><a ref-type="table" href="#j_abm-2020-0006_tab_003_w2aab3b7c28b1b6b1ab1b7b7Aa">Table 3</a></bold>). Image capturing devices in literatures were either digital camera [<a ref-type="bibr" href="#j_abm-2020-0006_ref_004_w2aab3b7c28b1b6b1ab2b2b4Aa">4</a>, <a ref-type="bibr" href="#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa">7</a>, <a ref-type="bibr" href="#j_abm-2020-0006_ref_008_w2aab3b7c28b1b6b1ab2b2b8Aa">8</a>], or smartphone [<a ref-type="bibr" href="#j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa">1</a>, <a ref-type="bibr" href="#j_abm-2020-0006_ref_005_w2aab3b7c28b1b6b1ab2b2b5Aa">5</a>]. Most reports except those reported by Russo et al. use lateral side of arm and forearm for measurement. Healthy volunteers were recruited in most studies, but Blonna et al. tested with patients and Russo et al. used cadaveric elbows. The accuracy of photography-based elbow ROM measurement among studies varied and also depended on observer's experience [<a ref-type="bibr" href="#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa">7</a>]. The mean differences of current study were comparable with previous literature; however, the error margins were higher.</p><table-wrap id="j_abm-2020-0006_tab_003_w2aab3b7c28b1b6b1ab1b7b7Aa" position="float"><label>Table 3</label><caption><p>The results of photography-based ROM of the elbow measurement from previous literatures compared with current study</p></caption><table rules="groups"><thead><tr><th align="left" valign="middle" rowspan="3"><bold>Study</bold></th><th align="center" valign="middle" rowspan="3"><bold>Elbows</bold></th><th align="center" valign="middle" rowspan="3"><bold>Reference method</bold></th><th align="center" valign="middle" colspan="3"><bold>Mean difference (°)</bold></th><th align="center" valign="middle" colspan="3"><bold>95% LOA (°)</bold></th><th align="center" valign="middle" colspan="3"><bold>Within 10° (%)</bold></th></tr><tr><th align="center" valign="middle" colspan="3"/><th align="center" valign="middle" colspan="3"/><th align="center" valign="middle" colspan="3"/></tr><tr><th align="center" valign="middle"><bold>Extension</bold></th><th align="center" valign="middle"><bold>Flexion</bold></th><th align="center" valign="middle"><bold>ROM</bold></th><th align="center" valign="middle"><bold>Extension</bold></th><th align="center" valign="middle"><bold>Flexion</bold></th><th align="center" valign="middle"><bold>ROM</bold></th><th align="center" valign="middle"><bold>Extension</bold></th><th align="center" valign="middle"><bold>Flexion</bold></th><th align="center" valign="middle"><bold>ROM</bold></th></tr></thead><tbody><tr><td align="left" valign="top">Blonna et al. [<a ref-type="bibr" href="#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa">7</a>]</td><td align="center" valign="top">50</td><td align="center" valign="top">DG</td><td align="center" valign="top">0</td><td align="center" valign="top">1</td><td align="center" valign="top"/><td align="center" valign="top">7–31</td><td align="center" valign="top">8–21</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/></tr><tr><td align="left" valign="top">Meislin et al. [<a ref-type="bibr" href="#j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa">1</a>]</td><td align="center" valign="top">64</td><td align="center" valign="top">DG</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top">0.2–0.3</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top">8.3–9.5</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top">95</td></tr><tr><td align="left" valign="top">Keijsers et al. [<a ref-type="bibr" href="#j_abm-2020-0006_ref_008_w2aab3b7c28b1b6b1ab2b2b8Aa">8</a>]</td><td align="center" valign="top">80</td><td align="center" valign="top">DG</td><td align="center" valign="top">1</td><td align="center" valign="top">0</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/></tr><tr><td align="left" valign="top">Russo et al. [<a ref-type="bibr" href="#j_abm-2020-0006_ref_004_w2aab3b7c28b1b6b1ab2b2b4Aa">4</a>]</td><td align="center" valign="top">20</td><td align="center" valign="top">MCA</td><td align="center" valign="top">4</td><td align="center" valign="top">11.7</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top">16<a ref-type="table-fn" href="#j_abm-2020-0006_table-fn_002_w2aab3b7c28b1b6b1ab1b7b7b3aaAa"><sup>†</sup></a></td><td align="center" valign="top">93</td><td align="center" valign="top"/></tr><tr><td align="left" valign="top">Chanlalit and Kongmalai [<a ref-type="bibr" href="#j_abm-2020-0006_ref_005_w2aab3b7c28b1b6b1ab2b2b5Aa">5</a>]</td><td align="center" valign="top">60</td><td align="center" valign="top">DG</td><td align="center" valign="top">2.6</td><td align="center" valign="top">2.1</td><td align="center" valign="top"/><td align="center" valign="top">7.8</td><td align="center" valign="top">13.4</td><td align="center" valign="top"/><td align="center" valign="top">98.3</td><td align="center" valign="top">85</td><td align="center" valign="top"/></tr><tr><td align="left" valign="top">Current study (DG)</td><td align="center" valign="top">56</td><td align="center" valign="top">DG</td><td align="center" valign="top">4.5</td><td align="center" valign="top">5.5</td><td align="center" valign="top">0.9</td><td align="center" valign="top">10.1</td><td align="center" valign="top">9.81</td><td align="center" valign="top">13.8</td><td align="center" valign="top">91.1</td><td align="center" valign="top">82.1</td><td align="center" valign="top">80.4</td></tr><tr><td align="left" valign="top">Current study (DI)</td><td align="center" valign="top">56</td><td align="center" valign="top">DI</td><td align="center" valign="top">4.6</td><td align="center" valign="top">4.0</td><td align="center" valign="top">0.6</td><td align="center" valign="top">9.9</td><td align="center" valign="top">11.2</td><td align="center" valign="top">16</td><td align="center" valign="top">87.5</td><td align="center" valign="top">85.7</td><td align="center" valign="top">83.9</td></tr></tbody></table><table-wrap-foot><fn-group><fn id="j_abm-2020-0006_table-fn_002_w2aab3b7c28b1b6b1ab1b7b7b3aaAa"><label>†</label><p>Within 5°.</p></fn><fn><p>DI, digital inclinometer; DG, digital goniometer; LOA, limit of agreement; MCA, motion capture analysis; ROM, range of motion.</p></fn></fn-group></table-wrap-foot></table-wrap><p>There are some implementation problems of DIPT that should be concerned. First, the initial position for photographic images was 90° lateral abduction of shoulder, which was different from other standard methods, in which elbow joint lied beside torso in anatomical position. The reasons for modification are outline detection function that requires body lie on the monotonous background. For this reason, the current method cannot be used in some patients, if they have problems such as shoulder joint stiffness or muscle weakness, thus they cannot lift their elbow against the background. Second, the compliance of patient to obtain valid images is very important. It is important to follow proper image capturing protocol to prevent photographic error such as incorrect projection. Third, in case of loss in the normal contour of arm or forearm from injury, morbid obesity, or other diseases in patients, this method may not give an accurate result. Finally, image should be cropped by the observer in the current protocol. Developing algorithm to detect anatomy and position of arm and forearm may help alleviate this burden.</p></sec><sec id="j_abm-2020-0006_s_004_w2aab3b7c28b1b6b1ab1b8Aa"><div>Conclusions</div><p>This research developed an innovative method for measuring ROM from photograph of elbow. Elbow ROM measurement from current DIPT protocol had comparable result with goniometer and inclinometer, but it can be different from other two methods up to 15.99°. Further investigations and protocol adjustment are needed to increase the accuracy of the image analytic technique.</p></sec></div></div></div></div><div id="pane-3" class="SeriesTab_card__26XnC SeriesTab_tab-pane__3pc7y card tab-pane" role="tabpanel" aria-labelledby="tab-3"><div class="SeriesTab_card-header__1DTAS card-header d-md-none pl-0" role="tab" id="heading-3"><h4 class="mb-0"><a data-toggle="collapse" href="#collapse-3" data-parent="#content" aria-expanded="false" aria-controls="collapse-3" style="padding:24px 0">Figures et tableaux<svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="chevron-down" class="svg-inline--fa fa-chevron-down fa-w-14 " role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><path fill="currentColor" d="M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z"></path></svg></a></h4></div><div id="collapse-3" class="SeriesTab_seriesTabCollapse__2csiF collapse" role="tabpanel" aria-labelledby="heading-3" data-parent="#content"><div class="SeriesTab_series-tab-body__1tZ1H SeriesTab_card-body__31JEh card-body Article_figures-tables__2SC5X"><figure><h4 class="mb-4">Figure 1</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=5bbb053dca5cef5a29a9f611bf0a46ee62d441baf4223d107e5afbdda62a3b03" alt="Photographic positions. Subject laterally abducted shoulder perpendicular to the floor and fully extended elbow (A). Elbow was maximally flexed (B)." class="mw-100"/><figcaption class="fw-500">Photographic positions. Subject laterally abducted shoulder perpendicular to the floor and fully extended elbow (A). Elbow was maximally flexed (B).</figcaption></figure><figure><h4 class="mb-4">Figure 2</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=3e1587ed199bd7f78487df0549c7090abab1f6d73b831945468a980bae197aab" alt="Line detection process. (A) Cropped image. (B) Converting red, green, and blue (RGB) to hue saturation value (HSV). (C) Detection of lines using Canny and Hough transformation." class="mw-100"/><figcaption class="fw-500">Line detection process. (A) Cropped image. (B) Converting red, green, and blue (RGB) to hue saturation value (HSV). (C) Detection of lines using Canny and Hough transformation.</figcaption></figure><figure><h4 class="mb-4">Figure 3</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=1b1a21eb94c6763e5eaec24b15e7e084502e581ec557763350ed643e1654bb53" alt="Angle calculation step for extended elbow image. (A): Locate middle points of arm and forearm from one-third of distance of both edges. (B): Calculate angle from difference between two slopes." class="mw-100"/><figcaption class="fw-500">Angle calculation step for extended elbow image. (A): Locate middle points of arm and forearm from one-third of distance of both edges. (B): Calculate angle from difference between two slopes.</figcaption></figure><figure><h4 class="mb-4">Figure 4</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=69ba0fcf8439e2ba27588cfbeecf4f6f3e556a90bebdb0d0e649db9fb7f1f383" alt="Angle calculation step for flexed elbow image. (A) Determine cutting point for classifying four reference lines. (B) Calculate angle from two slopes." class="mw-100"/><figcaption class="fw-500">Angle calculation step for flexed elbow image. (A) Determine cutting point for classifying four reference lines. (B) Calculate angle from two slopes.</figcaption></figure><figure><h4 class="mb-4">Figure 5</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=696885a85a5a664daac922f3b127b97dc634c6a645a73c42a2cf77363d5ee622" alt="Bland–Altman plot of digital image analysis and goniometer. (A) Extension. (B) Flexion. (C) Elbow range of motion (ROM)." class="mw-100"/><figcaption class="fw-500">Bland–Altman plot of digital image analysis and goniometer. (A) Extension. (B) Flexion. (C) Elbow range of motion (ROM).</figcaption></figure><figure><h4 class="mb-4">Figure 6</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=705cd072475ac8654cedc226b1056d2c6f6e761fecde42ac97047e8a70f58937" alt="Bland–Altman plot of digital image analysis and inclinometer. (A) Extension. (B): Flexion. (C): Elbow range of motion (ROM)." class="mw-100"/><figcaption class="fw-500">Bland–Altman plot of digital image analysis and inclinometer. (A) Extension. (B): Flexion. (C): Elbow range of motion (ROM).</figcaption></figure><figure><h4 class="mb-4">Figure 7</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_007.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20221206T141759Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=6796ba85afce47181129cd974ed16420adf33828b330e8ce99e92b2a88c0ee2a" alt="Conceptual illustration of systematic measurement bias between landmark-based method, goniometer and inclinometer, and contour-based DIPT. Green circles are lateral epicondyle location and green lines are imaginary lines of goniometer and inclinometer measurements. Pink lines are the result of using DIPT on fluoroscopic image. (A) Extension image. (B) Flexion image." class="mw-100"/><figcaption class="fw-500">Conceptual illustration of systematic measurement bias between landmark-based method, goniometer and inclinometer, and contour-based DIPT. Green circles are lateral epicondyle location and green lines are imaginary lines of goniometer and inclinometer measurements. Pink lines are the result of using DIPT on fluoroscopic image. (A) Extension image. (B) Flexion image.</figcaption></figure><h4 class="mb-4 mt-4">Comparison measurement of digital image processing method with digital goniometer and digital inclinometer</h4><table rules="groups"><thead><tr><th align="left" valign="middle"><bold>Angle measurement</bold></th><th align="center" valign="middle"><bold>Digital image processing</bold></th><th align="center" valign="middle"><bold>Digital goniometer</bold></th><th align="center" valign="middle"><bold>Digital inclinometer</bold></th></tr><tr><th align="left" valign="middle" colspan="4"/></tr><tr><th align="center" valign="middle"/><th align="center" valign="middle"><bold>Mean ± SD (range)</bold></th><th align="center" valign="middle"><bold>Mean ± SD (range)</bold></th><th align="center" valign="middle"><bold>Mean ± SD (range)</bold></th></tr></thead><tbody><tr><td align="left" valign="top">Extension</td><td align="center" valign="top">−2.01 ± 6.30 (−16.86 – 8.92)</td><td align="center" valign="top">−6.67 ± 3.48 (−11.83 – 0.28)</td><td align="center" valign="top">−6.74 ± 3.58 (−11.87 – 0.15)</td></tr><tr><td align="left" valign="top">Flexion</td><td align="center" valign="top">146.80 ± 5.20 (137.05 – 157.16)</td><td align="center" valign="top">141.28 ± 4.71 (129.98 – 148.80)</td><td align="center" valign="top">142.79 ± 6.58 (129.97 – 155.97)</td></tr><tr><td align="left" valign="top">Total ROM</td><td align="center" valign="top">148.81 ± 7.72 (135.89 – 164.70)</td><td align="center" valign="top">147.95 ± 6.89 (132.12 – 160.53)</td><td align="center" valign="top">149.55 ± 8.36 (131.63 – 167.27)</td></tr></tbody></table><h4 class="mb-4 mt-4">Bland–Altman analytic results and percentage of DIPT measurement error within 10° compared with goniometer and inclinometer</h4><table rules="groups"><thead><tr><th align="left" valign="top"><bold>Angle measurement</bold></th><th align="center" valign="top"><bold>Mean of difference (95% CI)</bold></th><th align="center" valign="top"><bold>Upper LOA (95% CI)</bold></th><th align="center" valign="top"><bold>Lower LOA (95% CI)</bold></th><th align="center" valign="top"><bold>Absolute maximal error<xref ref-type="table-fn" rid="j_abm-2020-0006_table-fn_001_w2aab3b7c28b1b6b1ab1b6b7b3aaAa"><sup>†</sup></xref></bold></th><th align="center" valign="top"><bold>Within 10° of error (%)</bold></th></tr></thead><tbody><tr><td align="left" valign="top" colspan="6"><italic>Goniometer</italic></td></tr><tr><td align="left" valign="top">Extension</td><td align="center" valign="top">4.51 (3.14, 5.88)</td><td align="center" valign="top">14.56 (12.2, 16.92)</td><td align="center" valign="top">–5.54 (–7.9, –3.18)</td><td align="center" valign="top">±10.05</td><td align="center" valign="top">91.1</td></tr><tr><td align="left" valign="top">Flexion</td><td align="center" valign="top">5.46 (4.12, 6.80)</td><td align="center" valign="top">15.26 (12.96, 17.57)</td><td align="center" valign="top">–4.35 (–6.66, –2.05)</td><td align="center" valign="top">±9.81</td><td align="center" valign="top">82.1</td></tr><tr><td align="left" valign="top">Total ROM</td><td align="center" valign="top">0.94 (–0.95, 2.84)</td><td align="center" valign="top">14.79 (11.54, 18.04)</td><td align="center" valign="top">–12.90 (–16.16, –9.65)</td><td align="center" valign="top">±13.84</td><td align="center" valign="top">80.4</td></tr><tr><td align="left" valign="top" colspan="6"><italic>Inclinometer</italic></td></tr><tr><td align="left" valign="top">Extension</td><td align="center" valign="top">4.61 (3.25, 5.96)</td><td align="center" valign="top">14.53 (12.2, 16.86)</td><td align="center" valign="top">–5.32 (–7.65, –2.99)</td><td align="center" valign="top">±9.93</td><td align="center" valign="top">87.5</td></tr><tr><td align="left" valign="top">Flexion</td><td align="center" valign="top">3.98 (2.45, 5.50)</td><td align="center" valign="top">15.15 (12.52, 17.77)</td><td align="center" valign="top">–7.19 (–9.81, –4.57)</td><td align="center" valign="top">±11.17</td><td align="center" valign="top">85.7</td></tr><tr><td align="left" valign="top">Total ROM</td><td align="center" valign="top">–0.63 (–2.64, 1.38)</td><td align="center" valign="top">14.10 (10.64, 17.56)</td><td align="center" valign="top">–15.36 (–18.82, –11.9)</td><td align="center" valign="top">±15.99</td><td align="center" valign="top">83.9</td></tr></tbody></table><h4 class="mb-4 mt-4">The results of photography-based ROM of the elbow measurement from previous literatures compared with current study</h4><table rules="groups"><thead><tr><th align="left" valign="middle" rowspan="3"><bold>Study</bold></th><th align="center" valign="middle" rowspan="3"><bold>Elbows</bold></th><th align="center" valign="middle" rowspan="3"><bold>Reference method</bold></th><th align="center" valign="middle" colspan="3"><bold>Mean difference (°)</bold></th><th align="center" valign="middle" colspan="3"><bold>95% LOA (°)</bold></th><th align="center" valign="middle" colspan="3"><bold>Within 10° (%)</bold></th></tr><tr><th align="center" valign="middle" colspan="3"/><th align="center" valign="middle" colspan="3"/><th align="center" valign="middle" colspan="3"/></tr><tr><th align="center" valign="middle"><bold>Extension</bold></th><th align="center" valign="middle"><bold>Flexion</bold></th><th align="center" valign="middle"><bold>ROM</bold></th><th align="center" valign="middle"><bold>Extension</bold></th><th align="center" valign="middle"><bold>Flexion</bold></th><th align="center" valign="middle"><bold>ROM</bold></th><th align="center" valign="middle"><bold>Extension</bold></th><th align="center" valign="middle"><bold>Flexion</bold></th><th align="center" valign="middle"><bold>ROM</bold></th></tr></thead><tbody><tr><td align="left" valign="top">Blonna et al. [<xref ref-type="bibr" rid="j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa">7</xref>]</td><td align="center" valign="top">50</td><td align="center" valign="top">DG</td><td align="center" valign="top">0</td><td align="center" valign="top">1</td><td align="center" valign="top"/><td align="center" valign="top">7–31</td><td align="center" valign="top">8–21</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/></tr><tr><td align="left" valign="top">Meislin et al. [<xref ref-type="bibr" rid="j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa">1</xref>]</td><td align="center" valign="top">64</td><td align="center" valign="top">DG</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top">0.2–0.3</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top">8.3–9.5</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top">95</td></tr><tr><td align="left" valign="top">Keijsers et al. [<xref ref-type="bibr" rid="j_abm-2020-0006_ref_008_w2aab3b7c28b1b6b1ab2b2b8Aa">8</xref>]</td><td align="center" valign="top">80</td><td align="center" valign="top">DG</td><td align="center" valign="top">1</td><td align="center" valign="top">0</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/></tr><tr><td align="left" valign="top">Russo et al. [<xref ref-type="bibr" rid="j_abm-2020-0006_ref_004_w2aab3b7c28b1b6b1ab2b2b4Aa">4</xref>]</td><td align="center" valign="top">20</td><td align="center" valign="top">MCA</td><td align="center" valign="top">4</td><td align="center" valign="top">11.7</td><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top"/><td align="center" valign="top">16<xref ref-type="table-fn" rid="j_abm-2020-0006_table-fn_002_w2aab3b7c28b1b6b1ab1b7b7b3aaAa"><sup>†</sup></xref></td><td align="center" valign="top">93</td><td align="center" valign="top"/></tr><tr><td align="left" valign="top">Chanlalit and Kongmalai [<xref ref-type="bibr" rid="j_abm-2020-0006_ref_005_w2aab3b7c28b1b6b1ab2b2b5Aa">5</xref>]</td><td align="center" valign="top">60</td><td align="center" valign="top">DG</td><td align="center" valign="top">2.6</td><td align="center" valign="top">2.1</td><td align="center" valign="top"/><td align="center" valign="top">7.8</td><td align="center" valign="top">13.4</td><td align="center" valign="top"/><td align="center" valign="top">98.3</td><td align="center" valign="top">85</td><td align="center" valign="top"/></tr><tr><td align="left" valign="top">Current study (DG)</td><td align="center" valign="top">56</td><td align="center" valign="top">DG</td><td align="center" valign="top">4.5</td><td align="center" valign="top">5.5</td><td align="center" valign="top">0.9</td><td align="center" valign="top">10.1</td><td align="center" valign="top">9.81</td><td align="center" valign="top">13.8</td><td align="center" valign="top">91.1</td><td align="center" valign="top">82.1</td><td align="center" valign="top">80.4</td></tr><tr><td align="left" valign="top">Current study (DI)</td><td align="center" valign="top">56</td><td align="center" valign="top">DI</td><td align="center" valign="top">4.6</td><td align="center" valign="top">4.0</td><td align="center" valign="top">0.6</td><td align="center" valign="top">9.9</td><td align="center" valign="top">11.2</td><td align="center" valign="top">16</td><td align="center" valign="top">87.5</td><td align="center" valign="top">85.7</td><td align="center" valign="top">83.9</td></tr></tbody></table></div></div></div><div id="reference" class="SeriesTab_card__26XnC SeriesTab_tab-pane__3pc7y card tab-pane" role="tabpanel" aria-labelledby="tab-4"><div class="SeriesTab_card-header__1DTAS card-header d-md-none pl-0" role="tab" id="heading-4"><h4 class="mb-0"><a data-toggle="collapse" href="#collapse-4" data-parent="#content" aria-expanded="false" aria-controls="collapse-4" style="padding:24px 0">Références<svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="chevron-down" class="svg-inline--fa fa-chevron-down fa-w-14 " role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><path fill="currentColor" d="M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z"></path></svg></a></h4></div><div id="collapse-4" class="SeriesTab_seriesTabCollapse__2csiF collapse" role="tabpanel" aria-labelledby="heading-4" data-parent="#content"><div class="SeriesTab_series-tab-body__1tZ1H SeriesTab_card-body__31JEh card-body"><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa"><label>[1]</label><mixed-citation>Meislin MA, Wagner ER, Shin AY. 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den folgenden Services indiziert: \u003c/P\u003e \u003cUL\u003e \u003cLI\u003eBaidu Scholar \u003c/LI\u003e \u003cLI\u003eCABI (over 50 subsections) \u003c/LI\u003e \u003cLI\u003eChemical Abstracts Service (CAS) - CAplus \u003c/LI\u003e \u003cLI\u003eChemical Abstracts Service (CAS) - SciFinder \u003c/LI\u003e \u003cLI\u003eCNKI Scholar (China National Knowledge Infrastructure) \u003c/LI\u003e \u003cLI\u003eCNPIEC - cnpLINKer \u003c/LI\u003e \u003cLI\u003eDimensions \u003c/LI\u003e \u003cLI\u003eEBSCO \u003c/LI\u003e \u003cLI\u003eExLibris \u003c/LI\u003e \u003cLI\u003eGoogle Scholar \u003c/LI\u003e \u003cLI\u003eJ-Gate \u003c/LI\u003e \u003cLI\u003eJournal Citation Reports/Science Edition \u003c/LI\u003e \u003cLI\u003eJournalGuide \u003c/LI\u003e \u003cLI\u003eJournalTOCs \u003c/LI\u003e \u003cLI\u003eKESLI-NDSL (Korean National Discovery for Science Leaders) \u003c/LI\u003e \u003cLI\u003eMyScienceWork \u003c/LI\u003e \u003cLI\u003eNaver Academic \u003c/LI\u003e \u003cLI\u003eNaviga 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Asian Biomedicine (U.S. National Library of Medicine and ISO title abbreviation: Asian Biomed (Res Rev News)) is an international peer-reviewed journal covered by Clarivate Science Citation Index Expanded, Web of Science Core Collection (formerly the Institute for Scientific Information (ISI) Web of Knowledge), InCites Journal Citation Reports (Clarivate Analytics; originally ISI, previously Thomson Reuters), and is supported by the Commission on Higher Education, Ministry of Education, Thailand, with editorial offices at the Faculty of Medicine, Chulalongkorn University, Bangkok. It is intended to serve the biomedical and health sciences community of the entire Asian region and is published in cooperation with Sciendo (\u003cA href=\"http://www.sciendo.com/\"\u003ewww.sciendo.com\u003c/A\u003e) a De Gruyter company (\u003cA href=\"http://www.degruyter.com/\"\u003ewww.degruyter.com\u003c/A\u003e) devoted to academic publication and services, with offices at De Gruyter Poland Sp. in Warsaw. \u003c/P\u003e \u003cP\u003eThe content of the journal is open to full access by all online without charge. No submission, or article processing or page charges (APCs) are levied on authors or their institutions. Asian Biomedicine will bear the cost of publication of articles, but will publish color Figures at its discretion. \u003c/P\u003e\u003cP\u003eAsian Biomedicine is an international, general medical and biomedical journal that aims to publish original peer-reviewed contributions dealing with various topics in the biomedical and health sciences from basic experimental to clinical aspects. The work and authorship must be strongly affiliated with a country in Asia, or with specific importance and relevance to the Asian region. The Journal will publish reviews, original experimental studies, observational studies, technical and clinical (case) reports, practice guidelines, historical perspectives of Asian biomedicine, clinicopathological conferences, and commentaries \u003c/P\u003e \u003cP\u003eAsian Biomedicine is intended for a broad and international audience, primarily those in the health professions including researchers, physician practitioners, basic medical scientists, dentists, educators, administrators, those in the assistive professions, such as nurses, and the many types of allied health professionals in research and health care delivery systems including those in training. \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eRejection Rate\u003c/STRONG\u003e \u003c/P\u003e \u003cUL\u003e \u003cLI\u003e75% \u003c/LI\u003e\u003c/UL\u003e \u003cP\u003e\u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eArchiving \u003c/STRONG\u003e\u003c/P\u003e \u003cP\u003eSciendo archives the contents of this journal in \u003cA href=\"https://www.portico.org/\"\u003ePortico\u003c/A\u003e - digital long-term preservation service of scholarly books, journals and collections. \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003ePlagiarism Policy\u003c/STRONG\u003e \u003c/P\u003e \u003cP\u003eThe editorial board is participating in a growing community of \u003cA href=\"https://www.crossref.org/services/similarity-check/\"\u003eSimilarity Check System's\u003c/A\u003e users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. \u003c/P\u003e\u003c/DIV\u003e"},{"type":"submission","language":"English","textformat":null,"content":"\u003cDIV align=left\u003e \u003cP\u003eThe Editors of Asian Biomedicine require authors to be in compliance with the recommendations of the International Committee of Medical Journal Editors (ICMJE) for the conduct and reporting of scholarly work in medical journals. The current recommendations (December 2018 at printing) are available at \u003cA href=\"http://www.icmje.org/\"\u003ewww.icmje.org\u003c/A\u003e. \u003c/P\u003e \u003cP\u003eThe Editors of Asian Biomedicine adhere to principles of research integrity and aim to avoid any type of scientific misconduct, such as fabrication, falsification, plagiarism, redundant publication, and authorship problems. All submitted manuscripts are checked for potential plagiarism of all types, including patchwork plagiarism, using specialist software including iThenticate, and are reviewed by an editor responsible for publication integrity. In resolving any potential scientific misconduct, Asian Biomedicine follows international standards, guidelines, and flowcharts provided by the Committee on Publication Ethics (COPE) (available at: \u003cA href=\"http://publicationethics.org/\"\u003epublicationethics.org/\u003c/A\u003e resources), the Council for International Organizations of Medical Sciences (CIOMS), the World Association of Medical Editors (WAME) (\u003cA href=\"http://www.wame.org/about/recommendations-on-publication-ethicspolicie\"\u003ewww.wame.org/about/recommendations-on-publication-ethicspolicie\u003c/A\u003e), and the Council of Science Editors (\u003cA href=\"http://www.councilscienceeditors.org/resource-library/editorial-policies/\"\u003ewww.councilscienceeditors.org/resource-library/editorial-policies/\u003c/A\u003e). \u003c/P\u003e \u003cP\u003eAsian Biomedicine gives equal consideration to every carefully performed study investigating an important question within the scope of the Journal, whether the results are negative or positive. \u003c/P\u003e \u003cP\u003eThe \u003cA href=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/ABM/Guide_for_Authors.pdf\"\u003eGuide for Authors\u003c/A\u003e is revised periodically by the Editors as needed, and includes our ethical and policy guidelines. Authors should consult a recent issue of the Journal or visit \u003cA href=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/ABM/Guide_for_Authors.pdf\"\u003ethe link\u003c/A\u003e for the latest version of these guidelines. Any manuscript not prepared according to these guidelines may be returned to the author(s) for revision without review. \u003c/P\u003e \u003cP\u003eAll submissions must be made online via the \u003cA href=\"https://www.editorialmanager.com/abm/Default.aspx\"\u003eEditorial Manager\u003c/A\u003e submission system. A tutorial is found by clicking the Instructions for Authors button on the Editorial Manager home page. In case of any technical problems, please contact the Editorial Office of Asian Biomedicine at \u003cA href=\"mailto:abmjournal@chula.ac.th\"\u003eabmjournal@chula.ac.th\u003c/A\u003e \u003c/P\u003e\u003cBR\u003e \u003cP\u003e\u003cSTRONG\u003eOpen Access Statement\u003c/STRONG\u003e \u003c/P\u003e \u003cP\u003eThe journal is an Open Access journal that allows a free unlimited access to all its contents without any restrictions upon publication to all users. \u003c/P\u003e \u003cP\u003e\u003cA href=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/ABM/Open_Access_License.pdf\"\u003eOpen Access License\u003c/A\u003e \u003c/P\u003e\u003c/DIV\u003e"},{"type":"editorial","language":"English","textformat":null,"content":"\u003cSTRONG\u003eEditor-in-Chief\u003cBR\u003e\u003c/STRONG\u003eChitr Sitthi-amorn, Faculty of Medicine, Chulalongkorn University, Thailand \u003cP\u003e\u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eCoeditor-in-Chief\u003c/STRONG\u003e\u003cBR\u003eRobin James Storer, Faculty of Medicine, Chulalongkorn University, Thailand \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eManaging Editor\u003c/STRONG\u003e\u003cBR\u003eSunitra Pakinsee, Faculty of Medicine, Chulalongkorn University, Thailand \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eCo Editors\u003c/STRONG\u003e\u003cBR\u003eSittisak Honsawek, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eAlain Jacquet, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eWeerapan Khovidhunkit, Faculty of Medicine, Chulalongkorn University, Thailand \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eAssistant Editors\u003c/STRONG\u003e\u003cBR\u003eIssarang Nuchprayoon, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eAmornpun Sereemaspun, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eSira Sriswasdi, Faculty of Medicine, Chulalongkorn University, Thailand \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eEditorial Advisory Board\u003cBR\u003e\u003c/STRONG\u003eLarry Carbone, Independent Consultant, Laboratory and Veterinary Animal Welfare, California, USA \u003cBR\u003eShu Chien, Institute for Engineering Medicine, Jacobs School of Engineering, University of California, USA\u003cBR\u003eSootiporn Chittmittrapap, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eRobert E. Dedmon, Medical College of Wisconsin, USA\u003cBR\u003ePrasit Futrakul, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003ePirom Kamolratanakul, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003ePinit Kullavanijaya, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eHideyuki Niimi, National Cardiovascular Center Research Institute, Japan\u003cBR\u003eYong Poovorawan, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eDanielle Rice, Ottawa Hospital Research Institute, McGill University, Canada\u003cBR\u003eSamruay Shuangshoti, Faculty of Medicine, Chulalongkorn University, Thailand \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eEditors\u003c/STRONG\u003e\u003cBR\u003eStephen J. Atwood, School of Global Studies, Thammasat University, Thailand\u003cBR\u003eParvapan Bhattarakosol, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eWanpen Chaicumpa, Faculty of Tropical Medicine, Mahidol University, Thailand\u003cBR\u003eJames CM Chan, Tufts University School of Medicine, USA\u003cBR\u003eNavapun Charuruks, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eNipon Chattipakorn, Faculty of Medicine, Chiang Mai University, Thailand\u003cBR\u003eVilai Chentanez, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eSomchai Eiam-ong, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eVincenzo Eusebi, University of Bologna, Italy\u003cBR\u003eSuthat Fucharoen, Institute of Molecular Biosciences, Mahidol University, Thailand\u003cBR\u003eJoel Gelernter, Yale University School of Medicine, USA\u003cBR\u003eJing-Yang Han, Tasly Microcirculation Research Center, Peking University, China\u003cBR\u003eThiravat Hemachudha, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eVirginia H. Huxley, University of Missouri School of Medicine, USA\u003cBR\u003eB. A. Khalid, Universiti Kebangsaan Malaysia Medical Centre, Malaysia\u003cBR\u003eJiraporn Laothamatas, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Thailand\u003cBR\u003eAsada Leelahavanichkul, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eDennis Y. M. Lo, Department of Chemical Pathology, The Chinese University of Hong Kong, China\u003cBR\u003eNaomichi Matsumoto, Yokohama City University Graduate School of Medicine, Japan\u003cBR\u003eGregor Mikuz, Institute of Pathology, Medical University Innsbruck, Austria\u003cBR\u003eMary Elizabeth Miranda, Research Institute for Tropical Medicine, Philippines\u003cBR\u003eApiwat Mutirangura, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eBoonsong Ongphiphad-hanakul, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Thailand\u003cBR\u003eSuthiluk Patumraj, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eLisa C. Ranford-Cartwright, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, UK\u003cBR\u003eKiat Ruxrungtham, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eNaseem Salahuddin, The Aga Khan University, Karachi, Pakistan\u003cBR\u003ePichet Sampatanukul, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eVorasuk Shotelersuk, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eAnan Srikiatkhachorn, Faculty of Medicine, King Mongkut's Institute of Technology Ladkrabang, Thailand\u003cBR\u003eSuvit Sriussadaporn, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eMakoto Suematsu, Keio University School of Medicine, Japan\u003cBR\u003eYasuhiko Tabata, Institute for Frontier Medical Sciences, Kyoto University, Japan\u003cBR\u003eYuen Tannirandorn, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003ePyatat Tatsanavivat, Faculty of Medicine, Khon Kaen University, Thailand\u003cBR\u003ePaul Scott Thorner, Hospital for Sick Children and University of Toronto, Canada\u003cBR\u003eRachanee Udomsangpetch, Faculty of Medical Technology, Mahidol University, Thailand\u003cBR\u003ePakit Vichyanond, Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand\u003cBR\u003eSirenda Vong, Institut Pasteur-Cambodia, Cambodia\u003cBR\u003eThewarug Werawatganon, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eHenry Wilde, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eZhi-yi Xu, International Vaccine Institute, Seoul National University, Republic of Korea \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eStatistical Editors\u003c/STRONG\u003e\u003cBR\u003eYuda Chongpison, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eCameron Hurst, Queensland Institute of Medical Research, Australia\u003cBR\u003eStephen Kerr, Faculty of Medicine, Chulalongkorn University, Thailand \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eBoard of management\u003c/STRONG\u003e\u003cBR\u003eWacharasindhu Suttipong, Dean, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eVorasuk Shotelersuk, Associate Dean, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003eSupatporn Tepmongkol, Assistant Dean, Faculty of Medicine, Chulalongkorn University, Thailand\u003cBR\u003ePawinee Rerknimitr, Assistant Dean, Faculty of Medicine, Chulalongkorn University, Thailand \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eContact\u003c/STRONG\u003e\u003cBR\u003e\u003cA href=\"mailto:abmjournal@chula.ac.th\"\u003eabmjournal@chula.ac.th\u003c/A\u003e \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003ePublisher\u003c/STRONG\u003e\u003cBR\u003eDe Gruyter Poland\u003cBR\u003eBogumiła Zuga 32A Str.\u003cBR\u003e01-811 Warsaw, Poland\u003cBR\u003eT: +48 22 701 50 15 \u003c/P\u003e"}]}],"metrics":{"metric":[{"name":"5-year Impact Factor","value":0.292},{"name":"Cite Score","value":0.8},{"name":"Impact Factor","value":0.324},{"name":"SCImago Journal Rank","value":0.2},{"name":"Source Normalized Impact per Paper","value":0.542}]},"pricing":null,"publicationFrequency":{"frequency":"6","period":"YEAR"},"permissions":null,"contributors":"","serial":null,"publishMonth":"2","publishYear":"2020","tableCount":null,"figureCount":null,"refCount":null,"keywords":[],"figures":null,"tables":null,"planPubDates":[],"epubLink":null,"pdfLink":null,"coverImage":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/cover-image.jpg","coverImageOriginal":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/cover-image-original.jpg","pdfFiles":[],"parentObjectId":"6009bc9799b8105a15d5b368","isParentConference":false,"relatedTitles":null,"forAuthors":null,"nextPackageId":null,"prevPackageId":"61e4161f1792e62a88ec4586","parentName":"Volume 14 (2020): Issue 1 (February 2020)","grandParentId":"6005adc3e797941b18f23619","grandParentName":"Asian Biomedicine","isGrandParentConference":false,"publisherName":"Sciendo","publisherLocation":null,"nextMap":{"doi":null},"prevMap":{"id":{"timestamp":1642337823,"date":"2022-01-16T12:57:03.000+00:00"},"doi":"10.1515/abm-2020-0005"},"counter":0,"apaString":"Charoenlap,C. \u0026 Piromsopa,K.(2020).\u003carticle-title\u003eDigital image processing technique to measure the range of motion of the elbow\u003c/article-title\u003e. 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Vienna, Austria. 2019.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"book\" publication-format=\"print\"\u003e\u003ccollab\u003eR Core Team\u003c/collab\u003e\u003csource\u003eR: a language and environment for statistical computing\u003c/source\u003e\u003cpublisher-loc\u003eVienna, Austria\u003c/publisher-loc\u003e\u003cyear\u003e2019\u003c/year\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_abm-2020-0006_ref_015_w2aab3b7c28b1b6b1ab2b2c15Aa","citeString":"Datta D. blandr: a Bland-Altman method comparison package for R. 2017.","doi":null,"mixed-citation":"\u003cref id=\"j_abm-2020-0006_ref_015_w2aab3b7c28b1b6b1ab2b2c15Aa\"\u003e\u003clabel\u003e[15]\u003c/label\u003e\u003cmixed-citation\u003eDatta D. blandr: a Bland-Altman method comparison package for R. 2017.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"other\"\u003e\u003cname\u003e\u003csurname\u003eDatta\u003c/surname\u003e\u003cgiven-names\u003eD\u003c/given-names\u003e\u003c/name\u003e\u003csource\u003eBlandr: a Bland-Altman method comparison package for R\u003c/source\u003e\u003cyear\u003e2017\u003c/year\u003e\u003c/element-citation\u003e\u003c/ref\u003e"}],"pdfUrl":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/10.1515_abm-2020-0006.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20221206T141759Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=5779fac0f675e4f312d460518d259314fc5f3568748f36352250853c15344670","authorNotes":null,"publishMonth":"07","publishYear":"2020","receivedDate":null,"acceptedDate":null,"ePubDate":"2020-07-13T00:00:00.000+00:00","ePubDateText":"13 July 2020","pPubDate":null,"pPubDateText":null,"issueDate":"2020-02-01T00:00:00.000+00:00","coverDate":"2020-02-01T00:00:00.000+00:00","tableCount":null,"figureCount":null,"refCount":null,"articleCategories":"{\"subj-group\":{\"subject\":\"Technical report\"}}","titleGroup":"{\"article-title\":\"Digital image processing technique to measure the range of motion of the elbow\"}","fundingGroup":null,"abstractContent":[{"title":"Abstract","language":"English","content":"\u003cabstract\u003e\u003ctitle style='display:none'\u003eAbstract\u003c/title\u003e\u003csec\u003e\u003ctitle style='display:none'\u003eBackground\u003c/title\u003e\u003cp\u003eMost photography-based arc of motion measurements require human assessment and their accuracy depends on the observer.\u003c/p\u003e\u003c/sec\u003e\u003csec\u003e\u003ctitle style='display:none'\u003eObjectives\u003c/title\u003e\u003cp\u003eTo develop a digital image processing technique (DIPT) for measuring elbow range of motion (ROM), and to assess its validity and reliability compared with standard methods.\u003c/p\u003e\u003c/sec\u003e\u003csec\u003e\u003ctitle style='display:none'\u003eMethods\u003c/title\u003e\u003cp\u003ePhysiotherapists performed digital goniometer and inclinometer ROM measurements bilaterally on healthy volunteer elbows. A photographer took digital images of elbows fully extended and fully flexed 3 times using an 8-megapixel smartphone camera. Extension and flexion angles were calculated using the DIPT. Intra- and inter-rater reliability of all methods was assessed using an intraclass correlation coefficient (ICC). A paired Student's \u003citalic\u003et\u003c/italic\u003e test and Wilcoxon-signed rank test were used to assess systematic bias. A Bland–Altman plot was used to show possible range of difference between the methods.\u003c/p\u003e\u003c/sec\u003e\u003csec\u003e\u003ctitle style='display:none'\u003eResults\u003c/title\u003e\u003cp\u003eWe measured 56 elbows from 28 participants. Intra- and inter-rater ICCs of goniometer and inclinometer showed moderate-to-excellent agreement. Mean extension and flexion angles for the DIPT were greater than those for the goniometer and inclinometer measurements (\u003citalic\u003eP\u003c/italic\u003e \u0026lt; 0.05), but the total ROMs were not significantly different (vs goniometer \u003citalic\u003eP\u003c/italic\u003e = 0.32, vs inclinometer \u003citalic\u003eP\u003c/italic\u003e = 0.53). Limits of agreement were 9.93°–10.05° for extension angle, 9.81°–11.7° for flexion angle, and 13.84°–15.99° for total ROMs.\u003c/p\u003e\u003c/sec\u003e\u003csec\u003e\u003ctitle style='display:none'\u003eConclusions\u003c/title\u003e\u003cp\u003eElbow ROM measurement using the current DIPT produces results comparable with goniometer and inclinometer measurements, but the difference from the standard methods was up to 15.99° for total ROM.\u003c/p\u003e\u003c/sec\u003e\u003c/abstract\u003e"}],"figures":[{"label":"Figure 1","caption":"Photographic positions. Subject laterally abducted shoulder perpendicular to the floor and fully extended elbow (A). Elbow was maximally flexed (B).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20221206T141759Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=5bbb053dca5cef5a29a9f611bf0a46ee62d441baf4223d107e5afbdda62a3b03"},{"label":"Figure 2","caption":"Line detection process. (A) Cropped image. (B) Converting red, green, and blue (RGB) to hue saturation value (HSV). (C) Detection of lines using Canny and Hough transformation.","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20221206T141759Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=3e1587ed199bd7f78487df0549c7090abab1f6d73b831945468a980bae197aab"},{"label":"Figure 3","caption":"Angle calculation step for extended elbow image. (A): Locate middle points of arm and forearm from one-third of distance of both edges. (B): Calculate angle from difference between two slopes.","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20221206T141759Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=1b1a21eb94c6763e5eaec24b15e7e084502e581ec557763350ed643e1654bb53"},{"label":"Figure 4","caption":"Angle calculation step for flexed elbow image. (A) Determine cutting point for classifying four reference lines. (B) Calculate angle from two slopes.","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20221206T141759Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=69ba0fcf8439e2ba27588cfbeecf4f6f3e556a90bebdb0d0e649db9fb7f1f383"},{"label":"Figure 5","caption":"Bland–Altman plot of digital image analysis and goniometer. (A) Extension. (B) Flexion. (C) Elbow range of motion (ROM).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20221206T141759Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=696885a85a5a664daac922f3b127b97dc634c6a645a73c42a2cf77363d5ee622"},{"label":"Figure 6","caption":"Bland–Altman plot of digital image analysis and inclinometer. (A) Extension. (B): Flexion. (C): Elbow range of motion (ROM).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20221206T141759Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=705cd072475ac8654cedc226b1056d2c6f6e761fecde42ac97047e8a70f58937"},{"label":"Figure 7","caption":"Conceptual illustration of systematic measurement bias between landmark-based method, goniometer and inclinometer, and contour-based DIPT. Green circles are lateral epicondyle location and green lines are imaginary lines of goniometer and inclinometer measurements. Pink lines are the result of using DIPT on fluoroscopic image. (A) Extension image. (B) Flexion image.","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_007.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20221206T141759Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=6796ba85afce47181129cd974ed16420adf33828b330e8ce99e92b2a88c0ee2a"}],"tableContent":{"Comparison measurement of digital image processing method with digital goniometer and digital inclinometer":"\u003ctable rules=\"groups\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" valign=\"middle\"\u003e\u003cbold\u003eAngle measurement\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eDigital image processing\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eDigital goniometer\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eDigital inclinometer\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" valign=\"middle\" colspan=\"4\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"center\" valign=\"middle\"/\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eMean ± SD (range)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eMean ± SD (range)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eMean ± SD (range)\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eExtension\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e−2.01 ± 6.30 (−16.86 – 8.92)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e−6.67 ± 3.48 (−11.83 – 0.28)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e−6.74 ± 3.58 (−11.87 – 0.15)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eFlexion\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e146.80 ± 5.20 (137.05 – 157.16)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e141.28 ± 4.71 (129.98 – 148.80)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e142.79 ± 6.58 (129.97 – 155.97)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eTotal ROM\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e148.81 ± 7.72 (135.89 – 164.70)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e147.95 ± 6.89 (132.12 – 160.53)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e149.55 ± 8.36 (131.63 – 167.27)\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e","Bland–Altman analytic results and percentage of DIPT measurement error within 10° compared with goniometer and inclinometer":"\u003ctable rules=\"groups\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" valign=\"top\"\u003e\u003cbold\u003eAngle measurement\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eMean of difference (95% CI)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eUpper LOA (95% CI)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eLower LOA (95% CI)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eAbsolute maximal error\u003cxref ref-type=\"table-fn\" rid=\"j_abm-2020-0006_table-fn_001_w2aab3b7c28b1b6b1ab1b6b7b3aaAa\"\u003e\u003csup\u003e†\u003c/sup\u003e\u003c/xref\u003e\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eWithin 10° of error (%)\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\" colspan=\"6\"\u003e\u003citalic\u003eGoniometer\u003c/italic\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eExtension\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.51 (3.14, 5.88)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e14.56 (12.2, 16.92)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–5.54 (–7.9, –3.18)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±10.05\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e91.1\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eFlexion\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e5.46 (4.12, 6.80)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e15.26 (12.96, 17.57)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–4.35 (–6.66, –2.05)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±9.81\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e82.1\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eTotal ROM\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0.94 (–0.95, 2.84)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e14.79 (11.54, 18.04)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–12.90 (–16.16, –9.65)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±13.84\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e80.4\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\" colspan=\"6\"\u003e\u003citalic\u003eInclinometer\u003c/italic\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eExtension\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.61 (3.25, 5.96)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e14.53 (12.2, 16.86)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–5.32 (–7.65, –2.99)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±9.93\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e87.5\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eFlexion\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e3.98 (2.45, 5.50)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e15.15 (12.52, 17.77)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–7.19 (–9.81, –4.57)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±11.17\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e85.7\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eTotal ROM\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–0.63 (–2.64, 1.38)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e14.10 (10.64, 17.56)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–15.36 (–18.82, –11.9)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±15.99\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e83.9\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e","The results of photography-based ROM of the elbow measurement from previous literatures compared with current study":"\u003ctable rules=\"groups\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" valign=\"middle\" rowspan=\"3\"\u003e\u003cbold\u003eStudy\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" rowspan=\"3\"\u003e\u003cbold\u003eElbows\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" rowspan=\"3\"\u003e\u003cbold\u003eReference method\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"\u003e\u003cbold\u003eMean difference (°)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"\u003e\u003cbold\u003e95% LOA (°)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"\u003e\u003cbold\u003eWithin 10° (%)\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"/\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"/\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eExtension\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eFlexion\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eROM\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eExtension\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eFlexion\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eROM\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eExtension\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eFlexion\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eROM\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eBlonna et al. [\u003cxref ref-type=\"bibr\" rid=\"j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa\"\u003e7\u003c/xref\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e50\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e7–31\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e8–21\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eMeislin et al. [\u003cxref ref-type=\"bibr\" rid=\"j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa\"\u003e1\u003c/xref\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e64\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0.2–0.3\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e8.3–9.5\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e95\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eKeijsers et al. [\u003cxref ref-type=\"bibr\" rid=\"j_abm-2020-0006_ref_008_w2aab3b7c28b1b6b1ab2b2b8Aa\"\u003e8\u003c/xref\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e80\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eRusso et al. [\u003cxref ref-type=\"bibr\" rid=\"j_abm-2020-0006_ref_004_w2aab3b7c28b1b6b1ab2b2b4Aa\"\u003e4\u003c/xref\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e20\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eMCA\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e11.7\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e16\u003cxref ref-type=\"table-fn\" rid=\"j_abm-2020-0006_table-fn_002_w2aab3b7c28b1b6b1ab1b7b7b3aaAa\"\u003e\u003csup\u003e†\u003c/sup\u003e\u003c/xref\u003e\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e93\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eChanlalit and Kongmalai [\u003cxref ref-type=\"bibr\" rid=\"j_abm-2020-0006_ref_005_w2aab3b7c28b1b6b1ab2b2b5Aa\"\u003e5\u003c/xref\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e60\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e2.6\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e2.1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e7.8\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e13.4\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e98.3\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e85\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eCurrent study (DG)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e56\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.5\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e5.5\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0.9\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e10.1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e9.81\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e13.8\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e91.1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e82.1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e80.4\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eCurrent study (DI)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e56\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDI\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.6\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.0\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0.6\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e9.9\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e11.2\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e16\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e87.5\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e85.7\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e83.9\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e"},"tables":null,"articleContent":"\n\u003cdiv\u003e\u003cp\u003eThe elbow joint is a hinge joint that allows single plane of movement: flexion and extension. Intra- and extra-articular disease such as elbow contracture and fracture can cause functional impairment of this joint. Range of motion (ROM) is an objective measurement of the elbow function and it is part of a scoring system [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa\"\u003e1\u003c/a\u003e].\u003c/p\u003e\u003cp\u003eAssessment of measurement methods for elbow ROM has been reported in the literature. Radiographic examination gives the most accurate result, but it is not the first choice in daily practice for evaluating elbow function due to the risk from radiation exposure [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_002_w2aab3b7c28b1b6b1ab2b2b2Aa\"\u003e2\u003c/a\u003e]. A standard clinical goniometer, universal and digital type, is very popular because of its availability. Inter- and intra-rater reliability of the goniometer is also high as indicated by recent systematic review [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_002_w2aab3b7c28b1b6b1ab2b2b2Aa\"\u003e2\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_003_w2aab3b7c28b1b6b1ab2b2b3Aa\"\u003e3\u003c/a\u003e]. An inclinometer is a practical device, but it should be used by a trained professional. Moreover, a digital inclinometer especially a dual-type inclinometer is quite expensive.\u003c/p\u003e\u003cp\u003ePhotography-based methods have been proposed and validated in many studies [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa\"\u003e1\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_004_w2aab3b7c28b1b6b1ab2b2b4Aa\"\u003e4\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_005_w2aab3b7c28b1b6b1ab2b2b5Aa\"\u003e5\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_006_w2aab3b7c28b1b6b1ab2b2b6Aa\"\u003e6\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa\"\u003e7\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_008_w2aab3b7c28b1b6b1ab2b2b8Aa\"\u003e8\u003c/a\u003e]. The concept of this method is to take a photo or video of elbow in extension and flexion position, and then to draw lines of arm and forearm axis on images by the assessor using a visible reference point and calculating the angle between these two lines. ROM value is obtained from flexion angle minus extension angle. This provides many benefits such as being inexpensive, durable, easy data storage and transfer to allow multiple observers, and possibility of measurement at any time in any location [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_004_w2aab3b7c28b1b6b1ab2b2b4Aa\"\u003e4\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_006_w2aab3b7c28b1b6b1ab2b2b6Aa\"\u003e6\u003c/a\u003e]. Image capturing devices can be a digital camera or smartphone, as has been already validated for measuring elbow ROM [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa\"\u003e1\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_008_w2aab3b7c28b1b6b1ab2b2b8Aa\"\u003e8\u003c/a\u003e]. However, accuracy of these measurement methods depends on observer's experience [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa\"\u003e7\u003c/a\u003e].\u003c/p\u003e\u003cp\u003eDigital image processing technique (DIPT) is a method of using computer software to analyze digital images for several purposes such as image feature extraction, classification, or pattern recognition. ROM measurement by using DIPT is the innovative concept of the present study. This method can be applied to a patient who is in a remote area taking and sending his or her elbow image in flexed–extended position via a smart device such as a smartphone or a tablet to a hospital database. Then image analysis software is used to automatically measure extension and flexion angles and send a report to a corresponding physician. We anticipated that the DIPT method can be used interchangeably using goniometer and inclinometer. The DIPT method can also reduce observational bias, examination time, labor burden, and cost of transportation.\u003c/p\u003e\u003cp\u003eThe present study aimed to develop a DIPT for measuring elbow ROM, and to assess validity and reliability of this technique compared with standard digital goniometer and inclinometer which are instruments for measuring arc of motion in daily clinical practice.\u003c/p\u003e\u003csec id=\"j_abm-2020-0006_s_001_w2aab3b7c28b1b6b1ab1b5Aa\"\u003e\u003cdiv\u003eMaterials and methods\u003c/div\u003e\u003cp\u003eThis study was approved by the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand (Certificate of Approval No. 198/2019). Participants were recruited from students and staff in the university by poster announcement. Inclusion criteria included all volunteer participants aged over 18 years who were able to lift their shoulder perpendicular to the floor and hold it still in an elbow extension and flexion position. Exclusion criteria included those who had deformity of arm and forearm or pain and discomfort at the elbow. Participants were informed about study protocol and risks involved in this study. The written informed consent was provided. Sample size was determined by calculating two-dependent mean sample sizes. Ten degree of elbow motion arc measurement error was considered as minimal clinically important difference (MCID) and used as summative difference. Standard deviation was obtained from the difference between photographic and goniometric measure ments [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa\"\u003e7\u003c/a\u003e]. A total of 14 elbows were required.\u003c/p\u003e\u003cp\u003eA digital goniometer and digital inclinometer were used as reference measuring devices to compare ROM measurements with those from DIPT. All measurements and capturing photographs were conducted on the same day (April 20, 2019) in the orthopedic operating room of King Chulalongkorn Memorial Hospital. Two trained physiotherapists with 2 years’ experience were briefed about the measurement techniques and they practiced the measurements on each other. Both examiners performed goniometer, inclinometer, and ROM measurements on the bilateral elbows of participants. Two research assistants recorded the measurement values on record forms.\u003c/p\u003e\u003csec id=\"j_abm-2020-0006_s_001_s_001_w2aab3b7c28b1b6b1ab1b5b3Aa\"\u003e\u003ctitle/\u003e\u003csec id=\"j_abm-2020-0006_s_001_s_001_s_001_w2aab3b7c28b1b6b1ab1b5b3b1Aa\"\u003e\u003cdiv\u003eDigital goniometer\u003c/div\u003e\u003cp\u003eA digital protractor goniometer with ±0.5° precision (Mediguage) was used. The goniometer was centered on the lateral epicondyle. The proximal part of goniometer pointed at the greater tuberosity of humerus and the distal part pointed at the middle portion of wrist [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_002_w2aab3b7c28b1b6b1ab2b2b2Aa\"\u003e2\u003c/a\u003e]. The examiner measured the flexion and extension position of elbow three times for each side.\u003c/p\u003e\u003c/sec\u003e\u003csec id=\"j_abm-2020-0006_s_001_s_001_s_002_w2aab3b7c28b1b6b1ab1b5b3b2Aa\"\u003e\u003cdiv\u003eDigital inclinometer\u003c/div\u003e\u003cp\u003eA baseline digital inclinometer (Fabrication Enterprises) was calibrated. The measurement technique for the inclinometer was modified from the American Medical Association (AMA) recommendation [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_009_w2aab3b7c28b1b6b1ab2b2b9Aa\"\u003e9\u003c/a\u003e]. The participant laid supine on a bed and both elbows hung beyond the edge of the bed. To measure the extension angle, the inclinometer was aligned on the long axis of forearm and set to zero. The participant was then asked to extend his or her elbow and the measurement value was recorded. To measure the flexion angle, the participant fully flexed his or her elbow while the examiner aligned the inclinometer with the forearm, read the flexion angle, and then repeated the same protocol two more times for extension and flexion. Three measurement values for the same limb and same position should be within 5° or 10% of the mean.\u003c/p\u003e\u003c/sec\u003e\u003csec id=\"j_abm-2020-0006_s_001_s_001_s_003_w2aab3b7c28b1b6b1ab1b5b3b3Aa\"\u003e\u003cdiv\u003eSmartphone photography\u003c/div\u003e\u003cp\u003eThe participant stood as close as possible in front of a blue screen to control the horizontal plane of the arm and then performed lateral abduction of the shoulder to 90° perpendicular to the floor. This position is considered as practical for a patient to take a photograph of his or her elbow at home and the monotonous color contrast background should help reduce image processing error. The upper extremity was exposed from shoulder to hand. A photographer took elbow images in with the arm fully extended and fully flexed three times for each position (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_001_w2aab3b7c28b1b6b1ab1b5b3b3b2Aa\"\u003eFigure 1\u003c/a\u003e\u003c/bold\u003e). The smartphone camera was at the same level of the elbow joint while taking a shot. Participant was told to drop his or her arm to a relaxed position between each photo shot and then raised it again so that the next image could be acquired. All images were taken using a iPhone 6 (Apple) with 8-megapixel rear camera (3,264 × 2,448 pixels, 72 dpi).\u003c/p\u003e\u003cfigure id=\"j_abm-2020-0006_fig_001_w2aab3b7c28b1b6b1ab1b5b3b3b2Aa\" position=\"float\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 1\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003ePhotographic positions. Subject laterally abducted shoulder perpendicular to the floor and fully extended elbow \u003cbold\u003e(A)\u003c/bold\u003e. Elbow was maximally flexed \u003cbold\u003e(B)\u003c/bold\u003e.\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_abm-2020-0006_fig_001.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20221206T141759Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=5bbb053dca5cef5a29a9f611bf0a46ee62d441baf4223d107e5afbdda62a3b03\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003c/sec\u003e\u003csec id=\"j_abm-2020-0006_s_001_s_001_s_004_w2aab3b7c28b1b6b1ab1b5b3b4Aa\"\u003e\u003cdiv\u003eDigital image processing technique\u003c/div\u003e\u003cp\u003eThe first step is “line detection,” which is the protocol for finding all possible lines in an image. All upper extremity images were cropped at below wrist level in the distal part and at deltoid muscle insertion in the proximal part. The horizontal and vertical blue areas were deleted from edges to eliminate the blue screen background as much as possible (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_002_w2aab3b7c28b1b6b1ab1b5b3b4b2Aa\"\u003eFigure 2A\u003c/a\u003e\u003c/bold\u003e). A median filter was applied to reduce noise from the camera and reduce light by converting the colored space from red, green, and blue (RGB) to hue saturation value (HSV) to create a mask with color range (100,0,0) and (180,255,255) in the HSV color space (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_002_w2aab3b7c28b1b6b1ab1b5b3b4b2Aa\"\u003eFigure 2B\u003c/a\u003e\u003c/bold\u003e). A mask was then applied to find the contour of the skin and clean the noise with a median blur filter (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_002_w2aab3b7c28b1b6b1ab1b5b3b4b2Aa\"\u003eFigure 2C\u003c/a\u003e\u003c/bold\u003e). Detection of lines was based on a Canny and Hough transformation (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_003_w2aab3b7c28b1b6b1ab1b5b3b4b3Aa\"\u003eFigures 3A\u003c/a\u003e\u003c/bold\u003e and \u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa\"\u003e4A\u003c/a\u003e\u003c/bold\u003e) [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_010_w2aab3b7c28b1b6b1ab2b2c10Aa\"\u003e10\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_011_w2aab3b7c28b1b6b1ab2b2c11Aa\"\u003e11\u003c/a\u003e]. To improve accuracy, outlier detection was used to eliminate unrelated lines.\u003c/p\u003e\u003cfigure id=\"j_abm-2020-0006_fig_002_w2aab3b7c28b1b6b1ab1b5b3b4b2Aa\" position=\"float\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 2\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eLine detection process. \u003cbold\u003e(A)\u003c/bold\u003e Cropped image. \u003cbold\u003e(B)\u003c/bold\u003e Converting red, green, and blue (RGB) to hue saturation value (HSV). \u003cbold\u003e(C)\u003c/bold\u003e Detection of lines using Canny and Hough transformation.\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_abm-2020-0006_fig_002.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20221206T141759Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=3e1587ed199bd7f78487df0549c7090abab1f6d73b831945468a980bae197aab\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cfigure id=\"j_abm-2020-0006_fig_003_w2aab3b7c28b1b6b1ab1b5b3b4b3Aa\" position=\"float\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 3\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eAngle calculation step for extended elbow image. \u003cbold\u003e(A):\u003c/bold\u003e Locate middle points of arm and forearm from one-third of distance of both edges. \u003cbold\u003e(B):\u003c/bold\u003e Calculate angle from difference between two slopes.\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_abm-2020-0006_fig_003.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20221206T141759Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=1b1a21eb94c6763e5eaec24b15e7e084502e581ec557763350ed643e1654bb53\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cfigure id=\"j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa\" position=\"float\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 4\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eAngle calculation step for flexed elbow image. \u003cbold\u003e(A)\u003c/bold\u003e Determine cutting point for classifying four reference lines. \u003cbold\u003e(B)\u003c/bold\u003e Calculate angle from two slopes.\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_abm-2020-0006_fig_004.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20221206T141759Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=69ba0fcf8439e2ba27588cfbeecf4f6f3e556a90bebdb0d0e649db9fb7f1f383\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cp\u003eAfter the line detection process, the next step is “angle calculation.” The algorithm for flexion and extension angles is similar. They varied depending on sides. For left flexion, right flexion, left extension, and right extension, the variation are the base lines for detecting upper and lower arms. For both flexion and extension, four base lines (upper arm, lower arm, upper forearm, and lower forearm) are located differently. The protocols for calculation of extension and flexion angles are described as follows.\u003c/p\u003e\u003csec id=\"j_abm-2020-0006_s_001_s_001_s_004_s_001_w2aab3b7c28b1b6b1ab1b5b3b4b6Aa\"\u003e\u003cdiv\u003eExtension angle\u003c/div\u003e\u003clist list-type=\"custom\"\u003e\u003clist-item\u003e\u003clabel\u003e(1)\u003c/label\u003e\u003cp\u003eTwo scan lines, such as a left scan line and a right scan line, were determined. The first scan line was located in one-third distance of the dominate edge (right edge for the left hand and vice versa). The second scan line was a quarter from another edge (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_003_w2aab3b7c28b1b6b1ab1b5b3b4b3Aa\"\u003eFigure 3A\u003c/a\u003e\u003c/bold\u003e).\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003clabel\u003e(2)\u003c/label\u003e\u003cp\u003eFor both scan lines, we found the cutting points for classifying lines into two groups on each side. The cutting points were determined by the middle point of the skin (calculated from the mask).\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003clabel\u003e(3)\u003c/label\u003e\u003cp\u003eLines were partitioned into four groups: top left lines, top right lines, lower left lines, and lower right lines. Between the left edge and the middle point, the intersection of each line and the scan line was used to determine the upper left lines and the lower left lines. A similar method was applied between the right edge and the middle point to determine the upper right lines and the lower right lines.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003clabel\u003e(4)\u003c/label\u003e\u003cp\u003eTo calculate the angle, the average slopes between the upper lines and the lower lines were calculated. The angle was calculated from the difference between the two slopes (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_003_w2aab3b7c28b1b6b1ab1b5b3b4b3Aa\"\u003eFigure 3B\u003c/a\u003e\u003c/bold\u003e).\u003c/p\u003e\u003c/list-item\u003e\u003c/list\u003e\u003c/sec\u003e\u003csec id=\"j_abm-2020-0006_s_001_s_001_s_004_s_002_w2aab3b7c28b1b6b1ab1b5b3b4b7Aa\"\u003e\u003cdiv\u003eFlexion angle\u003c/div\u003e\u003clist list-type=\"custom\"\u003e\u003clist-item\u003e\u003clabel\u003e(1)\u003c/label\u003e\u003cp\u003eA scan line was determined by using a vertical line from 10% of the edge. Either the left edge or right edge was used based on the side of the elbow.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003clabel\u003e(2)\u003c/label\u003e\u003cp\u003eThe scan line was scanned to find the cutting points for classifying four lines. The top point was determined by the middle point of the forearm. The lower point was determined by the middle point of the arm. The middle point between the empty spaces in the middle was used to partition between the forearm and the arm (dots in \u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa\"\u003eFigure 4A\u003c/a\u003e\u003c/bold\u003e).\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003clabel\u003e(3)\u003c/label\u003e\u003cp\u003eFor each line, we determined whether the line was a part for the upper or lower line by calculating the intersection at the scan line. The intersection point was then partitioned into 4 groups based on the detection points in the second step: upper top lines, lower top lines, upper low lines, and lower low lines (colored lines in \u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa\"\u003eFigure 4A\u003c/a\u003e\u003c/bold\u003e).\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003clabel\u003e(4)\u003c/label\u003e\u003cp\u003eFor each group of lines, we found and averaged the slope. There were slopes.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003clabel\u003e(5)\u003c/label\u003e\u003cp\u003eWe used a slope from the upper top line as the top reference line. This line is likely to be aligned with the ulnar bone. We used an average between the 2 slopes from the lower top lines and lower low lines as a base line. The angle was calculated from the 2 slopes, such as top reference line and base line, using an arctan function (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_004_w2aab3b7c28b1b6b1ab1b5b3b4b4Aa\"\u003eFigure 4B\u003c/a\u003e\u003c/bold\u003e).\u003c/p\u003e\u003c/list-item\u003e\u003c/list\u003e\u003cp\u003eTo validate our algorithm, we implemented our design using Python version 3.6. The imaging processing library is OpenCV [OpenCV] version 3.3. The outlier detection was based on local and outlier factor found in the Scikit-learn library version 0.19 [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_012_w2aab3b7c28b1b6b1ab2b2c12Aa\"\u003e12\u003c/a\u003e].\u003c/p\u003e\u003c/sec\u003e\u003c/sec\u003e\u003csec id=\"j_abm-2020-0006_s_001_s_001_s_005_w2aab3b7c28b1b6b1ab1b5b3b5Aa\"\u003e\u003cdiv\u003eStatistical analyses\u003c/div\u003e\u003cp\u003eIntra- and inter-rater reliability of all methods was computed using an intraclass correlation coefficient (ICC). The model for intrarater reliability of goniometer, inclinometer, and photographic image analysis was “two-way mixed” and “absolute agreement.” Inter-rater reliability of goniometer and inclinometer between two physiotherapists’ analytical models was “two-way random” and “absolute agreement.” Excellent agreement was determined by an ICC value \u0026gt;0.9, good agreement 0.75–0.90, and moderate agreement 0.50–0.90 [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_013_w2aab3b7c28b1b6b1ab2b2c13Aa\"\u003e13\u003c/a\u003e]. Reliability test was conducted using IBM SPSS for Windows version 22.\u003c/p\u003e\u003cp\u003eThe average of flexion and extension scores from both examiners and DIPT were used in the analysis. Total ROM value was the flexion angle minus the extension angle. Minimal clinical significance difference for elbow ROM was considered as 10°. Kolmogorov–Smirnov and Shapiro–Wilk tests were used to verify if variables were normally distributed. A paired Student's \u003citalic\u003et\u003c/italic\u003e test and Wilcoxon-signed rank test were used to detect systematic bias between all measurement techniques. Bias and possible range of difference between methods were illustrated using Bland–Altman plot and limits of agreement (LOA) analysis. Bland–Altman analysis was conducted in \u003citalic\u003eR\u003c/italic\u003e (R Core Team) using the “blandr” package [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_014_w2aab3b7c28b1b6b1ab2b2c14Aa\"\u003e14\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_015_w2aab3b7c28b1b6b1ab2b2c15Aa\"\u003e15\u003c/a\u003e]. DIPT measurement values that were \u0026lt;10° of difference were compared with the other 2 reference methods calculated in percentage.\u003c/p\u003e\u003c/sec\u003e\u003c/sec\u003e\u003c/sec\u003e\u003csec id=\"j_abm-2020-0006_s_002_w2aab3b7c28b1b6b1ab1b6Aa\"\u003e\u003cdiv\u003eResults\u003c/div\u003e\u003cp\u003eThirty healthy volunteer participants joined this study. After inspecting all images, two participants were removed from final analysis because their elbows were not fully flexed. Ultimately, we used data from a total 56 elbows from 15 male and 13 female participants. The average age was 20.6 years (range: 19–31 years). Mean weight, height, and body mass index were 58.9 kg (range: 39–110 kg), 165.3 cm (range: 150–189 cm), 21.4 kg/cm\u003csup\u003e2\u003c/sup\u003e (range: 16.7–34.0 kg/cm\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003eIntrarater ICC of goniometric and inclinometer in flexion and extension position showed excellent agreement between 0.953 and 0.994. Intrarater ICC of DIPT was 0.943 in extension and 0.886 in flexion. There was moderate-to-good inter-rater reliability of extension (E) and flexion (F) angle ICC between the two examiners, 0.862 (E) and 0.738 (F) for goniometer and 0.882 (E) and 0.784 (F) for inclinometer.\u003c/p\u003e\u003cp\u003eAll variable groups, except extension position of inclinometer group (\u003citalic\u003eP\u003c/italic\u003e = 0.026), were normally distributed. Mean extension and flexion angles as measured by DIPT were significantly greater than those measured by goniometry and inclinometry (\u003citalic\u003eP\u003c/italic\u003e \u0026lt; 0.05), but total ROM was comparable with both reference methods (DIPT vs goniometer \u003citalic\u003eP\u003c/italic\u003e = 0.322, DIPT vs inclinometer \u003citalic\u003eP\u003c/italic\u003e = 0.534) (\u003cbold\u003e\u003ca ref-type=\"table\" href=\"#j_abm-2020-0006_tab_001_w2aab3b7c28b1b6b1ab1b6b4Aa\"\u003eTable 1\u003c/a\u003e\u003c/bold\u003e).\u003c/p\u003e\u003ctable-wrap id=\"j_abm-2020-0006_tab_001_w2aab3b7c28b1b6b1ab1b6b4Aa\" position=\"float\"\u003e\u003clabel\u003eTable 1\u003c/label\u003e\u003ccaption\u003e\u003cp\u003eComparison measurement of digital image processing method with digital goniometer and digital inclinometer\u003c/p\u003e\u003c/caption\u003e\u003ctable rules=\"groups\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" valign=\"middle\"\u003e\u003cbold\u003eAngle measurement\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eDigital image processing\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eDigital goniometer\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eDigital inclinometer\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" valign=\"middle\" colspan=\"4\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"center\" valign=\"middle\"/\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eMean ± SD (range)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eMean ± SD (range)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eMean ± SD (range)\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eExtension\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e−2.01 ± 6.30 (−16.86 – 8.92)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e−6.67 ± 3.48 (−11.83 – 0.28)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e−6.74 ± 3.58 (−11.87 – 0.15)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eFlexion\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e146.80 ± 5.20 (137.05 – 157.16)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e141.28 ± 4.71 (129.98 – 148.80)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e142.79 ± 6.58 (129.97 – 155.97)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eTotal ROM\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e148.81 ± 7.72 (135.89 – 164.70)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e147.95 ± 6.89 (132.12 – 160.53)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e149.55 ± 8.36 (131.63 – 167.27)\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003ctable-wrap-foot\u003e\u003cfn-group\u003e\u003cfn\u003e\u003cp\u003eROM, range of motion.\u003c/p\u003e\u003c/fn\u003e\u003c/fn-group\u003e\u003c/table-wrap-foot\u003e\u003c/table-wrap\u003e\u003cp\u003eNormality of score differences in image analysis and the goniometer and inclinometer methods were assessed using a Shapiro–Wilk test. All methods demonstrated a normal distribution pattern (\u003citalic\u003eP\u003c/italic\u003e = 0.06–0.39).\u003c/p\u003e\u003cp\u003eBland–Altman analysis showed extension and flexion angle bias of the DIPT–goniometer 4.51 (95% CI 3.14–5.88), 5.46 (95% CI 4.12–6.80) and DIPT–inclinometer 4.61 (95% CI 3.25–5.96), 3.98 (95% CI 2.45–5.50). Total ROM mean difference of DIPT–goniometer and DIPT–inclinometer was 0.94 (–0.95 to 2.84) and –0.63 (–2.64 to 1.38). Absolute maximal error of flexion and extension angles was 9.81°–11.17° and total ROM angle was 13.84°–15.99°. There were 80.4%–91.1% of DIPT values that were \u0026lt;10° of MCID compared with goniometer and 83.9–87.5% compared with inclinometer (\u003cbold\u003e\u003ca ref-type=\"table\" href=\"#j_abm-2020-0006_tab_002_w2aab3b7c28b1b6b1ab1b6b7Aa\"\u003eTable 2\u003c/a\u003e\u003c/bold\u003e and \u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_005_w2aab3b7c28b1b6b1ab1b6b8Aa\"\u003eFigures 5\u003c/a\u003e\u003c/bold\u003e and \u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_006_w2aab3b7c28b1b6b1ab1b6b9Aa\"\u003e6\u003c/a\u003e\u003c/bold\u003e).\u003c/p\u003e\u003ctable-wrap id=\"j_abm-2020-0006_tab_002_w2aab3b7c28b1b6b1ab1b6b7Aa\" position=\"float\"\u003e\u003clabel\u003eTable 2\u003c/label\u003e\u003ccaption\u003e\u003cp\u003eBland–Altman analytic results and percentage of DIPT measurement error within 10° compared with goniometer and inclinometer\u003c/p\u003e\u003c/caption\u003e\u003ctable rules=\"groups\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" valign=\"top\"\u003e\u003cbold\u003eAngle measurement\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eMean of difference (95% CI)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eUpper LOA (95% CI)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eLower LOA (95% CI)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eAbsolute maximal error\u003ca ref-type=\"table-fn\" href=\"#j_abm-2020-0006_table-fn_001_w2aab3b7c28b1b6b1ab1b6b7b3aaAa\"\u003e\u003csup\u003e†\u003c/sup\u003e\u003c/a\u003e\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"top\"\u003e\u003cbold\u003eWithin 10° of error (%)\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\" colspan=\"6\"\u003e\u003citalic\u003eGoniometer\u003c/italic\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eExtension\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.51 (3.14, 5.88)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e14.56 (12.2, 16.92)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–5.54 (–7.9, –3.18)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±10.05\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e91.1\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eFlexion\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e5.46 (4.12, 6.80)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e15.26 (12.96, 17.57)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–4.35 (–6.66, –2.05)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±9.81\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e82.1\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eTotal ROM\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0.94 (–0.95, 2.84)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e14.79 (11.54, 18.04)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–12.90 (–16.16, –9.65)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±13.84\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e80.4\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\" colspan=\"6\"\u003e\u003citalic\u003eInclinometer\u003c/italic\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eExtension\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.61 (3.25, 5.96)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e14.53 (12.2, 16.86)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–5.32 (–7.65, –2.99)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±9.93\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e87.5\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eFlexion\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e3.98 (2.45, 5.50)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e15.15 (12.52, 17.77)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–7.19 (–9.81, –4.57)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±11.17\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e85.7\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eTotal ROM\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–0.63 (–2.64, 1.38)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e14.10 (10.64, 17.56)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e–15.36 (–18.82, –11.9)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e±15.99\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e83.9\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003ctable-wrap-foot\u003e\u003cfn-group\u003e\u003cfn id=\"j_abm-2020-0006_table-fn_001_w2aab3b7c28b1b6b1ab1b6b7b3aaAa\"\u003e\u003clabel\u003e†\u003c/label\u003e\u003cp\u003eAbsolute maximal error = Mean – lower LOA.\u003c/p\u003e\u003c/fn\u003e\u003cfn\u003e\u003cp\u003eCI, confidence interval; LOA, limit of agreement; ROM, range of motion.\u003c/p\u003e\u003c/fn\u003e\u003c/fn-group\u003e\u003c/table-wrap-foot\u003e\u003c/table-wrap\u003e\u003cfigure id=\"j_abm-2020-0006_fig_005_w2aab3b7c28b1b6b1ab1b6b8Aa\" position=\"float\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 5\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eBland–Altman plot of digital image analysis and goniometer. \u003cbold\u003e(A)\u003c/bold\u003e Extension. \u003cbold\u003e(B)\u003c/bold\u003e Flexion. \u003cbold\u003e(C)\u003c/bold\u003e Elbow range of motion (ROM).\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_abm-2020-0006_fig_005.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20221206T141759Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=696885a85a5a664daac922f3b127b97dc634c6a645a73c42a2cf77363d5ee622\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cfigure id=\"j_abm-2020-0006_fig_006_w2aab3b7c28b1b6b1ab1b6b9Aa\" position=\"float\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 6\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eBland–Altman plot of digital image analysis and inclinometer. \u003cbold\u003e(A)\u003c/bold\u003e Extension. \u003cbold\u003e(B):\u003c/bold\u003e Flexion. \u003cbold\u003e(C):\u003c/bold\u003e Elbow range of motion (ROM).\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_abm-2020-0006_fig_006.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20221206T141759Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=705cd072475ac8654cedc226b1056d2c6f6e761fecde42ac97047e8a70f58937\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003c/sec\u003e\u003csec id=\"j_abm-2020-0006_s_003_w2aab3b7c28b1b6b1ab1b7Aa\"\u003e\u003cdiv\u003eDiscussion\u003c/div\u003e\u003cp\u003eThere are several advantages of using photography-based ROM measurement, especially in the era of telemedicine. Innovative methods to collect data remotely from a patient have been popularized in recent years. Physicians can assess their patients’ function and make suggestion via Internet portal without having patients come to the clinic. Photography- and video-based ROM measurement method required human observers who need proper training to achieve high accuracy (7). Most photographic–goniometric methods use bony or alternative landmarks for drawing two reference lines that may be difficult to locate in some cases (1, 4, 5, 7). The present study aimed to solve these observer-related problems using DIPT.\u003c/p\u003e\u003cp\u003eThe present study has some limitations. First, DIPT protocol assesses only the active ROM. An examiner is needed to perform passive ROM measurement. Second, some participants may not produce their best effort, do not understand instructions clearly, and do not extend or flex their elbow fully. We needed to exclude four images from the analysis. Third, the extension rod as recommended by AMA was not available for digital inclinometer used in the current study.\u003c/p\u003e\u003cp\u003eDIPT measurement of flexion and extension had higher bias around 4°–5° than in the other methods. There are various explanations for this deviation. First is the difference in vertex location, and goniometer and inclinometer measurements begin with localizing lateral epicondyle as vertex of angle and then projecting its arm to distal and proximal bony landmark. DIPT is different from reference methods, it uses extremity contour to create proximal arm and distal forearm line, and the vertex is intersected between these lines. Second, the dorsal surface of the forearm is thin and close to ulnar shaft alignment which affects distal reference line when calculating angle using DIPT. Also, vertex of goniometer and inclinometer angles lies anteriorly compared with ulnar bone shaft line. This is demonstrated from geometric illustration obtained using fluoroscopic images of the elbow which use similar DIPT protocol for drawing angle alignment (\u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_007_w2aab3b7c28b1b6b1ab1b7b4Aa\"\u003eFigures 7A\u003c/a\u003e\u003c/bold\u003e and \u003cbold\u003e\u003ca ref-type=\"fig\" href=\"#j_abm-2020-0006_fig_007_w2aab3b7c28b1b6b1ab1b7b4Aa\"\u003e7B\u003c/a\u003e\u003c/bold\u003e). Another possible cause can be found from images review, and some participants minimally flexed instead of fully extended their elbows in extension image, probably because they used biceps muscle function to control shoulder joint in the abduction plane.\u003c/p\u003e\u003cfigure id=\"j_abm-2020-0006_fig_007_w2aab3b7c28b1b6b1ab1b7b4Aa\" position=\"float\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 7\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eConceptual illustration of systematic measurement bias between landmark-based method, goniometer and inclinometer, and contour-based DIPT. Green circles are lateral epicondyle location and green lines are imaginary lines of goniometer and inclinometer measurements. Pink lines are the result of using DIPT on fluoroscopic image. \u003cbold\u003e(A)\u003c/bold\u003e Extension image. \u003cbold\u003e(B)\u003c/bold\u003e Flexion image.\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_abm-2020-0006_fig_007.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6009bc9799b8105a15d5b368/j_abm-2020-0006_fig_007.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20221206T141759Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20221206%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=6796ba85afce47181129cd974ed16420adf33828b330e8ce99e92b2a88c0ee2a\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cp\u003eTotal ROM had comparable result with reference methods, but had an absolute error \u0026gt;10° margin of MCID for elbow joint. Total ROM is the calculated value from flexion angle minus extension angle, so the error is combination between these two values. Twenty from total 116 DIPT measurements, 11 compared with goniometer and 9 compared with inclinometer, had difference \u0026gt;10°. These can be divided into 3 groups: group 1 denotes lower extension angle and higher flexion angle; group 2 denotes higher extension angle and lower flexion angle; and group 3 denotes higher extension and flexion angles. There were 8, 7, and 5 measurements in group 1, group 2, and group 3, respectively. Of note, 15 of 20 measurements had higher value and more effect than lower value, and other 5 measurements had nearly equal effect between higher and lower values. This can be speculated that significant difference of total ROM between DIPT measurement and reference methods occurred because DIPT measurement tended to have higher value of either flexion or extension angle than goniometer and inclinometer measurements.\u003c/p\u003e\u003cp\u003eThere are several studies using photograph for elbow arc of motion measurement with variety of methods (\u003cbold\u003e\u003ca ref-type=\"table\" href=\"#j_abm-2020-0006_tab_003_w2aab3b7c28b1b6b1ab1b7b7Aa\"\u003eTable 3\u003c/a\u003e\u003c/bold\u003e). Image capturing devices in literatures were either digital camera [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_004_w2aab3b7c28b1b6b1ab2b2b4Aa\"\u003e4\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa\"\u003e7\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_008_w2aab3b7c28b1b6b1ab2b2b8Aa\"\u003e8\u003c/a\u003e], or smartphone [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa\"\u003e1\u003c/a\u003e, \u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_005_w2aab3b7c28b1b6b1ab2b2b5Aa\"\u003e5\u003c/a\u003e]. Most reports except those reported by Russo et al. use lateral side of arm and forearm for measurement. Healthy volunteers were recruited in most studies, but Blonna et al. tested with patients and Russo et al. used cadaveric elbows. The accuracy of photography-based elbow ROM measurement among studies varied and also depended on observer's experience [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa\"\u003e7\u003c/a\u003e]. The mean differences of current study were comparable with previous literature; however, the error margins were higher.\u003c/p\u003e\u003ctable-wrap id=\"j_abm-2020-0006_tab_003_w2aab3b7c28b1b6b1ab1b7b7Aa\" position=\"float\"\u003e\u003clabel\u003eTable 3\u003c/label\u003e\u003ccaption\u003e\u003cp\u003eThe results of photography-based ROM of the elbow measurement from previous literatures compared with current study\u003c/p\u003e\u003c/caption\u003e\u003ctable rules=\"groups\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" valign=\"middle\" rowspan=\"3\"\u003e\u003cbold\u003eStudy\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" rowspan=\"3\"\u003e\u003cbold\u003eElbows\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" rowspan=\"3\"\u003e\u003cbold\u003eReference method\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"\u003e\u003cbold\u003eMean difference (°)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"\u003e\u003cbold\u003e95% LOA (°)\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"\u003e\u003cbold\u003eWithin 10° (%)\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"/\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"/\u003e\u003cth align=\"center\" valign=\"middle\" colspan=\"3\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eExtension\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eFlexion\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eROM\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eExtension\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eFlexion\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eROM\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eExtension\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eFlexion\u003c/bold\u003e\u003c/th\u003e\u003cth align=\"center\" valign=\"middle\"\u003e\u003cbold\u003eROM\u003c/bold\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eBlonna et al. [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_007_w2aab3b7c28b1b6b1ab2b2b7Aa\"\u003e7\u003c/a\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e50\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e7–31\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e8–21\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eMeislin et al. [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_001_w2aab3b7c28b1b6b1ab2b2b1Aa\"\u003e1\u003c/a\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e64\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0.2–0.3\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e8.3–9.5\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e95\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eKeijsers et al. [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_008_w2aab3b7c28b1b6b1ab2b2b8Aa\"\u003e8\u003c/a\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e80\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eRusso et al. [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_004_w2aab3b7c28b1b6b1ab2b2b4Aa\"\u003e4\u003c/a\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e20\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eMCA\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e11.7\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e16\u003ca ref-type=\"table-fn\" href=\"#j_abm-2020-0006_table-fn_002_w2aab3b7c28b1b6b1ab1b7b7b3aaAa\"\u003e\u003csup\u003e†\u003c/sup\u003e\u003c/a\u003e\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e93\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eChanlalit and Kongmalai [\u003ca ref-type=\"bibr\" href=\"#j_abm-2020-0006_ref_005_w2aab3b7c28b1b6b1ab2b2b5Aa\"\u003e5\u003c/a\u003e]\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e60\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e2.6\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e2.1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e7.8\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e13.4\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003ctd align=\"center\" valign=\"top\"\u003e98.3\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e85\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eCurrent study (DG)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e56\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDG\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.5\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e5.5\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0.9\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e10.1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e9.81\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e13.8\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e91.1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e82.1\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e80.4\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" valign=\"top\"\u003eCurrent study (DI)\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e56\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003eDI\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.6\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e4.0\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e0.6\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e9.9\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e11.2\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e16\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e87.5\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e85.7\u003c/td\u003e\u003ctd align=\"center\" valign=\"top\"\u003e83.9\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003ctable-wrap-foot\u003e\u003cfn-group\u003e\u003cfn id=\"j_abm-2020-0006_table-fn_002_w2aab3b7c28b1b6b1ab1b7b7b3aaAa\"\u003e\u003clabel\u003e†\u003c/label\u003e\u003cp\u003eWithin 5°.\u003c/p\u003e\u003c/fn\u003e\u003cfn\u003e\u003cp\u003eDI, digital inclinometer; DG, digital goniometer; LOA, limit of agreement; MCA, motion capture analysis; ROM, range of motion.\u003c/p\u003e\u003c/fn\u003e\u003c/fn-group\u003e\u003c/table-wrap-foot\u003e\u003c/table-wrap\u003e\u003cp\u003eThere are some implementation problems of DIPT that should be concerned. First, the initial position for photographic images was 90° lateral abduction of shoulder, which was different from other standard methods, in which elbow joint lied beside torso in anatomical position. The reasons for modification are outline detection function that requires body lie on the monotonous background. For this reason, the current method cannot be used in some patients, if they have problems such as shoulder joint stiffness or muscle weakness, thus they cannot lift their elbow against the background. Second, the compliance of patient to obtain valid images is very important. It is important to follow proper image capturing protocol to prevent photographic error such as incorrect projection. Third, in case of loss in the normal contour of arm or forearm from injury, morbid obesity, or other diseases in patients, this method may not give an accurate result. Finally, image should be cropped by the observer in the current protocol. Developing algorithm to detect anatomy and position of arm and forearm may help alleviate this burden.\u003c/p\u003e\u003c/sec\u003e\u003csec id=\"j_abm-2020-0006_s_004_w2aab3b7c28b1b6b1ab1b8Aa\"\u003e\u003cdiv\u003eConclusions\u003c/div\u003e\u003cp\u003eThis research developed an innovative method for measuring ROM from photograph of elbow. Elbow ROM measurement from current DIPT protocol had comparable result with goniometer and inclinometer, but it can be different from other two methods up to 15.99°. Further investigations and protocol adjustment are needed to increase the accuracy of the image analytic technique.\u003c/p\u003e\u003c/sec\u003e\u003c/div\u003e","keywords":[{"title":"Keywords","language":null,"keywords":["artificial intelligence","computer-assisted","diagnostic techniques and procedures","elbow joint","image analysis","range of motion"]}],"recentIssues":{"10.2478/abm-2022-0019":"\u003carticle-title\u003eA One Health approach to antimicrobial resistance\u003c/article-title\u003e","10.2478/abm-2022-0020":"\u003carticle-title\u003eSialic acid: an attractive biomarker with promising biomedical applications\u003c/article-title\u003e","10.2478/abm-2022-0023":"\u003carticle-title\u003eAntibiotic resistance, biofilm forming ability, and clonal profiling of clinical isolates of \u003citalic\u003eStaphylococcus aureus\u003c/italic\u003e from southern and northeastern India\u003c/article-title\u003e","10.2478/abm-2022-0024":"\u003carticle-title\u003eAn 85-amino-acid polypeptide 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We have partnered with Cvent and Converia.","conferenceServices.third":"We can publish your conference proceedings and optionally provide you with the event management systems. We publish conference proceedings online using the Open Access model. Printed copies can be bought online. We currently publish proceedings in English language only.","conferenceServices.fourth":"The services and solutions that we offer for conference proceedings are bundled into three packages: \u003c1\u003eStandard\u003c/1\u003e, \u003c3\u003eClassic\u003c/3\u003e and \u003c5\u003ePremier\u003c/5\u003e. We charge for each paper published and the charge depends on the package and any additional services and solutions you choose.","conferenceServices.fifth":"The diagram shows the key components of each package.","conferenceServices.sixth":"Sciendo would be delighted to publish your conference proceedings and provide event management systems for your conference. 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The role of the university is to select and channel books and book proposals for this publishing co-operation, as well as to promote this publishing opportunity to its faculty.","whiteLabelContent.fourth":"The university can decide which package of services applies to each journal and book. 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