A morphology-based PPG heart rate monitoring algorithm achieved 99.5% accuracy, 1.65% mean absolute percentage error, and 1.18 BPM mean absolute error with an average response time of 6.85 seconds.
A novel PPG morphology-based algorithm provides highly accurate, fast spot heart rate measurements with low computational requirements suitable for embedded platforms.
). In this paper, an efficient heart rate monitoring algorithm based on the morphology of photoplethysmography (PPG) signals to measure the spot heart rate (HR) and its real-time implementation is proposed. The algorithm does pre-processing and detects the onsets and systolic peaks of the PPG signal to estimate the heart rate of the subject. Since the algorithm is based on the morphology of the signal, it works well when the subject is not moving, which is a typical test case. So, this algorithm is developed mainly to measure the heart rate at on-demand applications. Real-time experimental results indicate the heart rate accuracy of 99.5%, mean absolute percentage error (MAPE) of 1.65%, mean absolute error (MAE) of 1.18 BPM and reference closeness factor (RCF) of 0.988. The results further show that the average response time of the algorithm to give the spot HR is 6.85 s, so that the users need not wait longer to see their HR. The hardware implementation results show that the algorithm only requires 18 KBytes of total memory and runs at high speed with 0.85 MIPS. So, this algorithm can be targeted to low-cost embedded platforms.
Mohan et al. (Fri,) conducted a other in Heart rate monitoring. Morphology-based PPG heart rate monitoring algorithm was evaluated on Heart rate accuracy. A morphology-based PPG heart rate monitoring algorithm achieved 99.5% accuracy, 1.65% mean absolute percentage error, and 1.18 BPM mean absolute error with an average response time of 6.85 seconds.
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