A Threshold Assembler-Based Algorithm for Accurate Systolic Peak Detection in Photoplethysmography Signals

This study presents a novel algorithm for accurately detecting the systolic peak in photoplethysmography (PPG) signals. The proposed algorithm utilizes a threshold assembler approach
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combines four simple thresholding conditions, namely normalized threshold, differential threshold, amplitude threshold, and interval threshold, through a logical judgment process. The effectiveness of the algorithm is demonstrated through a comparison with other existing research in both low-error and high-complexity environments, and the experimental results show that the proposed algorithm achieves the best precision in detecting the systolic peak of PPG signals compared to other existing algorithms. The findings of this study confirm the effectiveness of the proposed algorithm for detecting the systolic peak of PPG signals. Moreover, future studies could optimize the algorithm by using larger and better-distributed datasets. Overall, these results demonstrate the potential impact of the threshold assembler-based algorithm for improving the accuracy of systolic peak detection in PPG signals, and its potential to contribute to the development of PPG-based healthcare applications.