This methodological study demonstrates a novel structural decomposition approach for extracting pulse wave characteristics and heart rate from remote photoplethysmography signals.
Hypothesis-generating for rPPG structural decomposition; prospective validation required before clinical adoption.
A method for extracting the pulse wave by methods of structural decomposition of a remote-photoplethysmography (rPPG) time series is proposed. Structural decomposition of rPPG signals into wave processes presumes a natural symbiosis of methods for multiscale, singular, and digital spectral analysis of nonstationary processes. Using the Hilbert transform, adaptive estimates of instantaneous heartbeat frequencies and their correlating spectral characteristics are obtained. According to the analysis of various algorithms for the formation of informative components of the pulse wave, variational pulsometry indicators are verified. The efficiency of the structural decomposition of the time series in the analysis of heart rate by the rPPG method is substantiated.
No takes yet. Share an insight, caveat, or question.
Labunets et al. (2022) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: