Systolic peak detection of photoplethysmograms via regularity approach

Cardiovascular diseases severely degrade the human health and they threaten the human life. Therefore, the prevention of suffering from the cardiovascular diseases and applying the corresponding treatments are essential. To achieve this goal, the detection and the analysis of the critical points in the photoplethysmograms (PPGs) play an important role for performing the early screening and the intervention of the cardiovascular diseases. In particular, the systolic peak is an important information for detecting the cardiovascular diseases. In recent years, many automatic methods were developed for detecting the systolic peak. However, detecting the systolic peak will the high accuracy is still challenging because the noise is contaminated to the PPGs. Also, the required computational power for detecting the systolic peak is large. This paper proposes a regularity approach for achieving the automatic detection. More precisely, the regularity value is compared to a threshold value and the systolic peak is detected based on the thresholding approach. The computer numerical simulation results show that our proposed method is more resistance to the noise.