Gaussian modelling characteristics changes derived from finger photoplethysmographic pulses during exercise and recovery

Gaussian modelling method has been reported as a useful method to analyze arterial pulse waveform changes. This study aimed to provide scientific evidence on Gaussian modelling characteristics changes derived from the finger photoplethysmographic (PPG) pulses during exercise and recovery. 65 healthy subjects (18 female and 47 male) were recruited. Finger PPG pulses were digitally recorded with 5 different exercise loads (0, 50, 75, 100, 125W) as well as during each of 4minute (min) recovery period. The PPG pulses were normalized in both width and amplitude for each recording, which were decomposed into three independent Gaussian waves with nine parameters determined, including the peak amplitude (H1, H2, H3), peak time position (N1, N2, N3) and half-width (W1, W2, W3) from each Gaussian wave, and four extended parameters determined, including the peak time interval (T1,2, T1,3) and amplitude ratio (R1,2, R1,3) between 1st Gaussian wave and 2nd, 3rd Gaussian waves. These derived parameters were finally compared between different exercise loads and recovery phases. With gradually increased exercise loads, the peak amplitude H2, peak time position N1, N2, N3, and half-width W1, W2 increased, peak amplitude H3 decreased significantly (all P