An improved algorithm for the detection of photoplethysmographic percussion peaks - Feifei Luo; Jin Li; Feng Yun; Tianjun Chen; Xiang Chen (2014 7th International Congress on Image and Signal Processing, 2014)
Accuracy of peak detection is very important for autonomic evaluation based on photoplethysmographic (PPG) signals. Considering percussion peaks may not the maximum points in their PPG periods, the study proposed an improved algorithm of peak detection. It first determines the reference points at the rising edge of PPG percussion waves and then applies the local maximum only in the certain ranges. PPG signals were measured from 32 healthy subjects. 1952 beats PPG pulses were segmented. Among them, there were 998 beats whose tidal peaks or dicrotic peaks were higher than percussion peaks. Compared with the local maximum algorithm, the improved algorithm showed a better performance on peak detection with the sensitivity increasing from 48.61% to 96.82%, the positive predictivity from 46.18% to 95.45% and the failed detection rate decreasing from 51.79% to 3.18%. The results indicate that the improved algorithm is more robust for detection of PPG percussion peaks.