Improved Peak Detection Algorithm for Photoplethysmographic Signals

We present a computationally efficient non-parametric algorithm for the automated detection of systolic peaks in photoplethysmography (PPG) signal that does not require preprocessing for artifact elimination, signal filtering, or detrending. It is validated in an experimental setup based on the publicly available CLAS dataset. The experimental results show that it outperforms two well-known methods in terms of detection accuracy and computational demands. We report a very high detection accuracy, with an error rate below 0.5%, on good quality signals and below 13% on very low-quality PPG signals. The proposed algorithm is characterized with very short processing times and on a low-cost laptop computer requires approximately 0.000012 real-time for the processing of a 60-seconds recording.