Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Guler, Saygun; Golparvar, Ata; Öztürk, Özberk; Dogan, Huseyin; Yapıcı, Murat Kaya

doi:10.1088/2057-1976/acaf8a

Cited by 9 publications

(3 citation statements)

References 37 publications

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“…It is possible that Chebyshev type I and type II filters can find application in other tasks not related to the pulse wave analysis. For example, it was recently shown that the Chebyshev II filter of 2nd, 4th and 6th orders perform the best for denoising remote PPG signals in camera-based imaging technique 42 .…”

Section: Discussionmentioning

confidence: 99%

Estimation of phase distortions of the photoplethysmographic signal in digital IIR filtering

Lapitan,

Rogatkin,

Molchanova

et al. 2024

Sci Rep

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Pre-processing of the photoplethysmography (PPG) signal plays an important role in the analysis of the pulse wave signal. The task of pre-processing is to remove noise from the PPG signal, as well as to transmit the signal without any distortions for further analysis. The integrity of the pulse waveform is essential since many cardiovascular parameters are calculated from it using morphological analysis. Digital filters with infinite impulse response (IIR) are widely used in the processing of PPG signals. However, such filters tend to change the pulse waveform. The aim of this work is to quantify the PPG signal distortions that occur during IIR filtering in order to select a most suitable filter and its parameters. To do this, we collected raw finger PPG signals from 20 healthy volunteers and processed them by 5 main digital IIR filters (Butterworth, Bessel, Elliptic, Chebyshev type I and type II) with varying parameters. The upper cutoff frequency varied from 2 to 10 Hz and the filter order—from 2nd to 6th. To assess distortions of the pulse waveform, we used the following indices: skewness signal quality index (SSQI), reflection index (RI) and ejection time compensated (ETc). It was found that a decrease in the upper cutoff frequency leads to damping of the dicrotic notch and a phase shift of the pulse wave signal. The minimal distortions of a PPG signal are observed when using Butterworth, Bessel and Elliptic filters of the 2nd order. Therefore, we can recommend these filters for use in applications aimed at morphological analysis of finger PPG waveforms of healthy subjects.

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Section: Discussionmentioning

confidence: 99%

Estimation of phase distortions of the photoplethysmographic signal in digital IIR filtering

Lapitan,

Rogatkin,

Molchanova

et al. 2024

Sci Rep

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show abstract

“… Publications by subject area [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , …”

Section: Figureunclassified

Non-Contact Vision-Based Techniques of Vital Sign Monitoring: Systematic Review

Saikevičius,

Raudonis,

Dervinis

et al. 2024

Sensors

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The development of non-contact techniques for monitoring human vital signs has significant potential to improve patient care in diverse settings. By facilitating easier and more convenient monitoring, these techniques can prevent serious health issues and improve patient outcomes, especially for those unable or unwilling to travel to traditional healthcare environments. This systematic review examines recent advancements in non-contact vital sign monitoring techniques, evaluating publicly available datasets and signal preprocessing methods. Additionally, we identified potential future research directions in this rapidly evolving field.

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“…In the realm of remote photoplethysmography (rPPG), optimal digital filter selection becomes paramount for accurate vital signs recognition. The comparative analysis of 100 filters on over 300 rPPG signals reveals the Chebyshev II filter with a 4th order as the optimal choice for signal preprocessing [13].…”

Section: Introductionmentioning

confidence: 99%

Exploration of Digital Filter on Cardiac Monitor through Carotid Pulse and PCG (Phonocardiogram)

Ramadhan,

Yulianto,

Lutfiyah

et al. 2024

j.teknokes

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Heart defect early detection and correct diagnosis have become important healthcare priorities. Tools for monitoring cardiac problems are constantly being developed, with the PCG (Phonocardiogram) and Cardiac Monitor via Carotid Pulse essential for heart evaluation. Although condenser microphones embedded in electric stethoscopes have been used in past research as PCG sensors, more advancements are still required to reduce received noise. This study investigates how well a Chebyshev type-II digital filter works to reduce noise on the cardiac monitor using PCG and carotid pulse. The PCG sensor is the GY-MAX 9814 module, which is interfaced with an Arduino Uno microcontroller. Matlab, Visual Studio (used as a graph viewer), and Doppler Simulator (used as a phantom cardiac signal) are used. SNR (Signal to Noise Ratio) is used in the analysis to assess the effectiveness of two digital filter orders. The average SNR value for the Doppler Simulator is 0.001404 dB at order 2, however, it climbs dramatically to 18.60023 dB at level 4 according to the results of the SNR analysis. The average SNR value in human signals is 11.50718 dB before the filter, 0.001404 dB after the post-order 2 filter, and 12.0009 dB after the post-order 4 filter. According to the results, the digital filter of order 4 is more effective in reducing noise. This study highlights the possibility of an order 4 digital filter to improve the Cardiac Monitor through PCG and Carotid Pulse. Through enhanced signal quality, the creation of this gadget holds the potential for streamlining the identification of cardiac problems. Future developments in this technology could lead to more precise and trustworthy cardiac exams, which would help with early diagnosis and treatment of cardiovascular health.

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Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Cited by 9 publications

References 37 publications

Estimation of phase distortions of the photoplethysmographic signal in digital IIR filtering

Estimation of phase distortions of the photoplethysmographic signal in digital IIR filtering

Non-Contact Vision-Based Techniques of Vital Sign Monitoring: Systematic Review

Exploration of Digital Filter on Cardiac Monitor through Carotid Pulse and PCG (Phonocardiogram)

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