<abstract xmlns="http://www.w3.org/1999/xhtml"><sec><h3>Background</h3><p>Most photography-based arc of motion measurements require human assessment and their accuracy depends on the observer.</p></sec><sec><h3>Objectives</h3><p>To 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.</p></sec><sec><h3>Methods</h3><p>Physiotherapists 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 <italic>t</italic> 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.</p></sec><sec><h3>Results</h3><p>We 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 (<italic>P</italic> &lt; 0.05), but the total ROMs were not significantly different (vs goniometer <italic>P</italic> = 0.32, vs inclinometer <italic>P</italic> = 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.</p></sec><sec><h3>Conclusions</h3><p>Elbow 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.</p></sec></abstract>

BackgroundMost photography-based arc of motion measurements require human assessment and their accuracy depends on the observer.ObjectivesTo 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.MethodsPhysiotherapists 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 t 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.ResultsWe 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 (P < 0.05), but the total ROMs were not significantly different (vs goniometer P = 0.32, vs inclinometer P = 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.ConclusionsElbow 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.

Digital image processing technique to measure the range of motion of the elbow

Department of Orthopaedics, Faculty of Medicine

Department of Computer Engineering, Faculty of Engineering

Research Group on Applied Computer Engineering Technology for Medicine and Healthcare

Asian Biomedicine

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Digital image processing technique to measure the range of motion of the elbow"}

BackgroundMost photography-based arc of motion measurements require human assessment and their accuracy depends on the observer.ObjectivesTo develop a digital...

Digital image processing technique to measure the range of motion of the elbow

Article Category: Technical report

Online veröffentlicht: 13. Juli 2020

Seitenbereich: 37 - 44

DOI: https://doi.org/10.1515/abm-2020-0006

Schlüsselwörter
artificial intelligence, computer-assisted, diagnostic techniques and procedures, elbow joint, image analysis, range of motion

© 2020 Chris Charoenlap et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Digital image processing technique to measure the range of motion of the elbow

Article Category: Technical report

Online veröffentlicht: 13. Juli 2020

Seitenbereich: 37 - 44

DOI: https://doi.org/10.1515/abm-2020-0006

Schlüsselwörterartificial intelligence, computer-assisted, diagnostic techniques and procedures, elbow joint, image analysis, range of motion

© 2020 Chris Charoenlap et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
artificial intelligence, computer-assisted, diagnostic techniques and procedures, elbow joint, image analysis, range of motion