An adaptive delineator for photoplethysmography waveforms.
Photoplethysmography (PPG) waveforms are rich in cardiovascular information, and hence, their analysis is significant in the diagnosis and prevention of cardiovascular diseases (CVDs). The second derivative of photoplethysmography (SDPPG) analysis for the accurate detection of significant points in characterising the PPG waveform is challenging. In this paper, a SDPPG analysis algorithm is proposed based on a resampling technique which normalises the signal and ensures the presence of all significant points of interest in all its recurrences. The proposed delineator detects a, b and e waves in SDPPG, which are based on the combined analysis of PPG waveforms and their second derivatives, characterising them beat-by-beat by electrocardiogram (ECG) signals. Experiments have been conducted on 46 PPG signal records, each of 10-s duration with low and varying amplitudes, and regular and irregular heart rhythms for healthy adults, as well as unhealthy and aged patients obtained from the large-scale openly available database PhysioNet. Based on the experiments conducted, it is found that the proposed algorithm performs better than existing methods in terms of sensitivity and positive predictivity with a highest sensitivity of 99.84% with respect to a (onset) and b waves, 99.67% for e waves (dicrotic notch), and 100% of positive predictivity for a and b waves and 99.82% in case of e waves.
Mohanalakshmi
M
Soundararajan
Sivasubramanian
S
Arunagiri
Swarnalatha
S
Alagala
D000465:Algorithms; D002318:Cardiovascular Diseases / Q000503:physiopathology*; D004562:Electrocardiography / Q000379:methods*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D017156:Photoplethysmography / Q000379:methods*; D012815:Signal Processing, Computer-Assisted