How nonlinear-type time-frequency analysis can help in sensing instantaneous heart rate and instantaneous respiratory rate from photoplethysmography in a reliable way

摘要

Despite the population of the noninvasive, economic, comfortable, andeasy-to-install photoplethysmography (PPG), it is still lacking amathematically rigorous and stable algorithm which is able to simultaneouslyextract from a single-channel PPG signal the instantaneous heart rate (IHR) andthe instantaneous respiratory rate (IRR). In this paper, a novel algorithmcalled deppG is provided to tackle this challenge. deppG is composed of twotheoretically solid nonlinear-type time-frequency analyses techniques, thede-shape short time Fourier transform and the synchrosqueezing transform, whichallows us to extract the instantaneous physiological information from the PPGsignal in a reliable way. To test its performance, in addition to validatingthe algorithm by a simulated signal and discussing the meaning of"instantaneous", the algorithm is applied to two publicly available batchdatabases, the Capnobase and the ICASSP 2015 signal processing cup. The formercontains PPG signals relative to spontaneous or controlled breathing in staticpatients, and the latter is made up of PPG signals collected from subjectsdoing intense physical activities. The accuracies of the estimated IHR and IRRare compared with the ones obtained by other methods, and represent thestate-of-the-art in this field of research. The results suggest the potentialof deppG to extract instantaneous physiological information from a signalacquired from widely available wearable devices, even when a subject carriesout intense physical activities.