Accès libre

Filter and Sampling Rate Optimization for PPG-Based Detection of Autonomic Dysfunction: An ECG-guided Approach

Yi-Hui Kao

Yi-Hui Kao

  • Department of Medical Education and Research, National Taiwan University Hospital Yun-Lin BranchDouliu, Taiwan
  • Graduate Institute of Anatomy and Cell Biology, National Taiwan University College of MedicineTaipei, Taiwan
Recherchez cet auteur sur
Sciendo|Google Scholar
Kao, Yi-Hui
, 
Danyal Shahmirzadi

Danyal Shahmirzadi

Graduate School of Engineering Science and Technology, National Yunlin University of Science and TechnologyDouliou, Taiwan
Profil Orcid
Recherchez cet auteur sur
Sciendo|Google Scholar
Shahmirzadi, Danyal
, 
Sung-Tsang Hsieh

Sung-Tsang Hsieh

  • Department of Neurology, National Taiwan University HospitalTaipei, Taiwan
  • Department of Anatomy and Cell Biology, National Taiwan University College of MedicineTaipei, Taiwan
  • Center of Precision Medicine, National Taiwan University College of MedicineTaipei, Taiwan
  • Graduate Institute of Clinical Medicine, National Taiwan University College of MedicineTaipei, Taiwan
  • Graduate Institute of Brain and Mind Sciences, National Taiwan University College of MedicineTaipei, Taiwan
Recherchez cet auteur sur
Sciendo|Google Scholar
Hsieh, Sung-Tsang
 et 
Wen-Fong Wang

Wen-Fong Wang

Department of Computer Science and Information Engineering, National Yunlin University of Science and TechnologyDouliu, Taiwan
Recherchez cet auteur sur
Sciendo|Google Scholar
Wang, Wen-Fong
  
28 août 2025
Filter and Sampling Rate Optimization for PPG-Based Detection of Autonomic Dysfunction: An ECG-guided Approach's Cover Image
À propos de cet article
Article précédent
Article suivant
Citez
Télécharger la couverture
Publié en ligne: 28 août 2025
Pages: 200 - 211
Reçu: 08 oct. 2024
Accepté: 02 juil. 2025
DOI: https://doi.org/10.2478/msr-2025-0024
Mots clés
© 2025 Yi-Hui Kao et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Fig. 1.

The placement of the ECG electrodes with PowerLab, a physiological signal acquisition instruments from ADInstruments Inc. [30].
The placement of the ECG electrodes with PowerLab, a physiological signal acquisition instruments from ADInstruments Inc. [30].

Fig. 2.

Examples of ECG and PPG signals.
Examples of ECG and PPG signals.

Fig. 3.

Signal processing flow chart for ECG and PPG.
Signal processing flow chart for ECG and PPG.

Fig. 4.

The process of extracting QRS from raw signals.
The process of extracting QRS from raw signals.

Fig. 5.

Detected ECG and PPG peaks.
Detected ECG and PPG peaks.

Fig. 6.

HeatMap of correlation coefficients between the RRI at 1 kHz and the SSIs at various rates in resting (a), breathing phase (b).
HeatMap of correlation coefficients between the RRI at 1 kHz and the SSIs at various rates in resting (a), breathing phase (b).

Fig. 7.

Evaluation of the best SSIV assessment range of normal cardiac autonomic function with the ROC curve, (a) – the resting phase; (b) – the deep breathing phase.
Evaluation of the best SSIV assessment range of normal cardiac autonomic function with the ROC curve, (a) – the resting phase; (b) – the deep breathing phase.

Fig. 8.

HeatMap of average absolute errors between the RRI at 1000 Hz and the SSIs at different sampling rates in resting (a) and breathing phases (b).
HeatMap of average absolute errors between the RRI at 1000 Hz and the SSIs at different sampling rates in resting (a) and breathing phases (b).

Confusion matrix between RRIV and SSIV in the resting and deep breathing phases_

Phase SSIV RRIV Abnormal [ms] RRIV Normal [ms]
Resting Abnormal 44 2
Normal 8 190
Deep breathing Abnormal 44 3
Normal 7 190

SSIV assessment range of normal cardiac autonomic function in each age group based on PPG_

Age [y] 20 ∼ 29 30 ∼ 39 40 ∼ 49 50 ∼ 59 60 ∼ 69
Rest [ms] 13 ∼ 45 7 ∼ 31 7 ∼ 35 6 ∼ 22 8 ∼ 18
Breath [ms] 20 ∼ 61 10 ∼ 53 15 ∼ 47 12 ∼ 58 9 ∼ 27

The sensitivity and specificity of SSIV in different assessment ranges_

Phase Rate [%] Out+2 Out+1 RRIV source In-1 In-2 In-3 In-4
Rest Sensitivity 36.54 63.46 84.62 96.15 96.15 100.00 100.00
Specificity 98.96 98.96 98.96 91.67 79.69 70.83 59.90
Breath Sensitivity 54.90 70.59 86.27 94.12 94.12 96.08 96.08
Specificity 99.48 99.48 98.45 95.85 91.19 84.97 78.24

A descriptive listing of PPG signal processing methods_

No. Filter name Description
F01 Butterworth The passband frequency is from 1 Hz to 5 Hz, and the filter order is 2.
F02 Bessel
F03 Chebyshev
F04 Elliptic
F11 Savitzky-Golay The polynomial order is 3, and the window size 401.
F12 Average The passband frequency is from 1 Hz to 5 Hz.
F13 Periodic moving After normalizing each cardiac cycle with the same number of sampled signals, the ith sampled signals of each of the 5 cycles are averaged, where 1 ≤ i ≤ the normalized cycle length.
F21 Daubechies Use the inverse DWT of Daubechies db6 and Coiflet C3 to reconstruct the selected band from 1 Hz to 5 Hz.
F22 Coiflet C3
F23 Morlet (CWT) Apply the inverse WT of Morlet to reconstruct the selected band from 1 Hz to 5 Hz.

RRIV assessment range of normal cardiac autonomic function in each age group based on ECG [38]_

Age [y] 20 ∼ 29 30 ∼ 39 40 ∼ 49 50 ∼ 59 60 ∼ 69
Rest [ms] 12 ∼ 46 6 ∼ 32 6 ∼ 36 5 ∼ 23 7 ∼ 19
Breath [ms] 19 ∼ 62 9 ∼ 54 14 ∼ 48 11 ∼ 59 8 ∼ 28

Average absolute errors between the RRIV/ECG SDNN/ECG, NN50 at 1000 Hz and the SSIV/PPG SDNN/PPG NN50 at different sampling rates_

Filter/Sample rates Phase Parameter 1000 [Hz] 500 [Hz] 250 [Hz] 200 [Hz] 125 [Hz] 100 [Hz] 50 [Hz] 40 [Hz] 25 [Hz] 20 [Hz]
F01 R SSIV [%] 0.6 0.6 1.2 1.3 1.3 1.4 1.8 2.2 3.4 4.4
F11 R SSIV [%] 1.4 1.5 2.1 2.2 2.3 2.3 2.8 3 4.1 7.3
F23 R SSIV [%] 2 2.2 3 2.5 2.9 2.8 3.2 4.7 4.6 5.8
F01 B SSIV [%] 0.9 1.1 1.2 1.1 1.2 1.2 1.8 2 2.9 3.8
F11 B SSIV [%] 2.5 2.3 2.3 2.5 2.6 2.7 3.1 3.3 4.2 14.4
F23 B SSIV [%] 2.6 2.7 2.9 2.5 2.9 3 3.4 5 4.3 5.6
F01 R SDNN [ms] 0.6 0.6 0.6 0.6 0.8 0.9 2.1 3.1 6.5 9.5
F11 R SDNN [ms] 1.3 1.4 1.5 1.6 1.7 1.9 3.2 4 7.3 12.4
F23 R SDNN [ms] 2.7 2.6 2.8 2.1 2.7 2.3 3.4 6.9 7.5 10.8
F01 B SDNN [ms] 1.2 1.2 1.3 1.3 1.3 1.4 2.2 2.7 5 7.2
F11 B SDNN [ms] 2.2 2.2 2.2 2.4 2.4 2.6 3.3 3.9 6.3 15.3
F23 B SDNN [ms] 2.7 2.7 2.9 2.4 2.7 2.6 3.3 6.1 5.6 8.1
F01 R NN50 [%] 0.8 0.9 0.8 1 1 1.3 1.7 1.7 3.6 3.1
F11 R NN50 [%] 1.7 1.6 1.8 1.6 1.9 2 3.5 2.2 5.1 4.3
F23 R NN50 [%] 1.5 1.5 1.5 1.6 1.6 1.8 2.2 2.1 4.1 3.3
F01 B NN50 [%] 0.8 0.8 0.8 0.9 0.9 1.1 2.2 1.8 3.6 3.1
F11 B NN50 [%] 2.4 2.4 2.8 2.3 2.7 2.3 4.9 2.8 5.9 5.3
F23 B NN50 [%] 1.6 1.6 1.7 1.6 1.7 1.9 3.1 2.5 4.8 4.1
Langue:
Anglais
Périodicité:
6 fois par an
Sujets de la revue:
Ingénierie, Ingénierie électrique, Ingénierie de contrôle, métrologie et essais
RSS Feed de la revue