Photoplethysmogram signal processing and analysis in evaluating arterial stiffness

Reguig, Med Anes Bereksi; Reguig, F. Bereksi

doi:10.1504/ijbet.2017.082674

Cited by 4 publications

(4 citation statements)

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“…The second derivative of the PPG waveform has been applied in several studies to assess the arterial stiffness (Pilt et al 2013, Reguig andReguig 2017) and was also used to detect the dicrotic notch of the PPG waveform without an apparent diastolic peak (McDuff et al 2014). However, the complication of applying the second derivative PPG is that it consists of four systolic feature points and one diastolic feature point and so must be used ratiometrically in situations where the raw PPG signal waveform is suboptimal (such as the presence of sinlike waveforms), and having more data points creates an added layer of difficulty in peak detection and so room for inaccuracy in the subsequent computation of SI.…”

Section: Discussionmentioning

confidence: 99%

Modified photoplethysmography signal processing and analysis procedure for obtaining reliable stiffness index reflecting arteriosclerosis severity

Wu¹,

Liu²,

Tzeng³

et al. 2022

Physiol. Meas.

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Objective. This study aimed to describe a modified photoplethysmography (PPG) signal processing and analysis procedure to obtain a more reliable arterial stiffness index (SI). Approach. Three parameters were used to assess the PPG signal quality without prominent diastolic waves, which are similar to a sinusoidal waveform shape. The first parameter, sinusoidal ratio (S-value), was based on frequency-domain analysis: a higher S-value indicated the presence of PPG pulse wave with unapparent diastolic peak. The second parameter was the time difference between systolic peak-to-diastolic peak and the systolic peak-to-dicrotic notch. The third parameter was the percentage of sin-like waveform in the PPG signals. The applicability of these parameters was demonstrated in 40 participants, including 11 with apparent diastolic peaks in the PPG signals and 29 with unapparent diastolic peaks. Main results. An S-value of >3.5 indicated apparent diastolic peaks in the PPG signals. In addition, a systolic peak-to-diastolic peak time difference >80% and a sin-like waveform >55% may be associated with severity of vascular aging. Significance. These parameters successfully detected low-quality PPG signals with unapparent diastolic waveform before SI calculation, thereby ensuring the accuracy of subsequent evaluation of cardiovascular-related disease and clinical risk stratification.

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Section: Discussionmentioning

confidence: 99%

Modified photoplethysmography signal processing and analysis procedure for obtaining reliable stiffness index reflecting arteriosclerosis severity

Wu¹,

Liu²,

Tzeng³

et al. 2022

Physiol. Meas.

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“…This point is determined as the first local maximum of FDPPG and can be confirmed by the second positive-to-negative crossing zero of SDPPG. The b/a ratio can be found from the parameters extracted to detect arterial stiffness [46]. In addition, PPG waveform and its derivatives (FDPPG and SDPPG) calculated by two forward mathematical derivatives can be used in extracting PAT [48].…”

Section: Derivative Of Ppgmentioning

confidence: 99%

“…The disadvantages of this technique are the unrefined precision of existing cardiovascular indicators, the trade-off between camera lens power and distance, its inability to perform real-time implementation, capturing waveform morphology in ambient light, and the sensitivity of a remote camera to MA. SDPPG can provide waves a and b, which are crucial for the assessment of arterial stiffness and other cardiovascular parameters [41], [46]. The detection algorithm for waves a and b from a study [41] produced a very high sensitivity (99.78%) for both waves.…”

Section: Derivative Of Ppgmentioning

confidence: 99%

Methods of Extracting Feature from Photoplethysmogram Waveform for Non-Invasive Diagnostic Applications

Hafifah

Nayan

2020

Int. J. Onl. Eng.

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<p>This paper presents a bibliographical survey of recently-published research on different techniques to extract feature from photoplethysmogram (PPG). These techniques and approaches have been implemented for better accuracy in detecting diseases. Moreover, several aspects in analyzing PPG waveform are discussed on the techniques in feature extraction, parameters involved and performance comparisons. This review will serve as a comparative study and reference for researches working on PPG waveform in health care applications.</p>

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“…Pulse wave analysis is very susceptible to motion artifacts, such that the Fast Fourier (FF) or the Wavelet Transform (WT) has been used to decompose 22,23 and “de-noise” 8,24,25 the spectra of these complex oscillatory signals. The application of WT to the PPG signal led researchers in the field to propose the “augmentation index (AI)” and the “b/a ratio,” which seem to help characterize vascular ageing 26,27 . More recently, the second derivative wave of the original PPG signal (accelerometer data) was referred to contain important health-related information 8,25 .…”

Section: Introductionmentioning

confidence: 99%

Different lasers reveal different skin microcirculatory flowmotion - data from the wavelet transform analysis of human hindlimb perfusion

Rodrigues

Rocha

Ferreira

et al. 2019

Sci Rep

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Laser Doppler flowmetry (LDF) and reflection photoplethysmography (PPG) are standard technologies to access microcirculatory function in vivo. However, different light frequencies mean different interaction with tissues, such that LDF and PPG flowmotion curves might have distinct meanings, particularly during adaptative (homeostatic) processes. Therefore, we analyzed LDF and PPG perfusion signals obtained in response to opposite challenges. Young healthy volunteers, both sexes, were assigned to Group 1 (n = 29), submitted to a normalized Swedish massage procedure in one lower limb, increasing perfusion, or Group 2 (n = 14), submitted to a hyperoxia challenge test, decreasing perfusion. LDF (Periflux 5000) and PPG (PLUX-Biosignals) green light sensors applied distally on both lower limbs recorded perfusion changes for each experimental protocol. Both techniques detected the perfusion increase with massage, and the perfusion decrease with hyperoxia, in both limbs. Further analysis with the wavelet transform (WT) revealed better depth-related discriminative ability for PPG (more superficial, less blood sampling) compared with LDF in both challenges. Spectral amplitude profiles consistently demonstrated better sensitivity for LDF, especially regarding the lowest frequency components. Strong correlations between components were not found. Therefore, LDF and PPG flowmotion curves are not equivalent, a relevant finding to better study microcirculatory physiology.

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Photoplethysmogram signal processing and analysis in evaluating arterial stiffness

Cited by 4 publications

References 0 publications

Modified photoplethysmography signal processing and analysis procedure for obtaining reliable stiffness index reflecting arteriosclerosis severity

Modified photoplethysmography signal processing and analysis procedure for obtaining reliable stiffness index reflecting arteriosclerosis severity

Methods of Extracting Feature from Photoplethysmogram Waveform for Non-Invasive Diagnostic Applications

Different lasers reveal different skin microcirculatory flowmotion - data from the wavelet transform analysis of human hindlimb perfusion

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