Wavelet Based Measurement on Photoplethysmography by Smartphone Imaging

Abstract

[Purpose] Smartphones video cameras can be used to detect the photoplethysmograph (PPG) signal.The pulse wave signal detected by smartphone always mixed mass noise because of finger moving, unevenness of pressure and outer light interference. Previous studies limit to the filtering algorithm that denoising signals, without considering characteristics information of pulse wave itself. [Method] In this paper, we propose an algorithm based on wavelet to detect qualified PPG, which captures three critical characteristic quantities through wavelet high frequency coefficient. [Results] Experiment illustrates that the detected PPG signal contain dicrotic wave, and whats more, further experiment on artery elasticity indexes indicates good robust of the algorithm. [Conclusions] Wavelet Based Measurement on Photoplethysmography by Smartphone Imaging can be used for the calculation of cardiovascular parameter such as angiosclerosis, arrhythmia, and vascular resistance.

Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging

“…The parts of the signal that are not in this range can be safely blocked. Several filter designs have been introduced and successfully implemented for IPPG signal denoising, including a moving average filter [75], a band-pass filter [70], [85], an adaptive band-pass filter [97], and wavelet denoising [108]. Many books have been written on digital signal processing, and, therefore, a detailed description of the filter design will not be presented in this paper.…”

Robust RPPG Method Based on Reference Signal Envelope to Improve Wave Morphology

“…If the channel contains a high proportion of valuable physiological information, simple smoothing techniques such as regular smoothing perform well. However, if the channel contains a lower proportion of valuable information, even advanced filtering methods such as band-pass filter [9], moving average filter [34], and wavelet transform denoising [39] may not produce the desired results. Once noise has been filtered out, researchers extract information such as heart rate, respiratory rate, and blood pressure.…”