PPG delineator for real-time ubiquitous applications.

This paper presents real-time signal processing algorithm for detection of onsets and peaks in Photoplethysmogram (PPG) waveform. Algorithm relies on the analysis of amplitude, slope and inter-beat intervals. The presented algorithm consists of four stages for characterizing PPG waveform. Preprocessing stage involves transformation of PPG since the original waveform is less impulsive and robust. In second stage, algorithm seeks for valid pulse detection in transformed signal complying with the amplitude threshold and inter-beat interval. On detection of valid pulses, algorithm then searches backward and forward in transformed signal for the detection of peaks and onsets. Further the detection parameters are made adaptive to comply with varying beat morphologies and fluctuations in baseline. All signal processing steps and decision logics are implemented with low computational complexity to make it applicable for compact ubiquitous health monitoring devices. On evaluation with our database, the algorithm achieved sensitivity of 96.89% and positive predictivity of 94.55% within an acceptance level of 12 ms.