The MSPTDfast photoplethysmography beat detection algorithm: design, benchmarking, and open-source distribution.

photoplethysmography is widely used for physiological monitoring, whether in clinical devices such as pulse oximeters, or consumer devices such as smartwatches. A key step in the analysis of photoplethysmogram (PPG) signals is detecting heartbeats. The multi-scale peak & trough detection () algorithm has been found to be one of the most accurate PPG beat detection algorithms, but is less computationally efficient than other algorithms. Therefore, the aim of this study was to develop a more efficient, open-source implementation of thealgorithm for PPG beat detection, named.five potential improvements towere identified and evaluated on four datasets.was designed by incorporating each improvement which on its own reduced execution time whilst maintaining a high-score. After internal validation,was benchmarked against state-of-the-art beat detection algorithms on four additional datasets.incorporated two key improvements: pre-processing PPG signals to reduce the sampling frequency to 20 Hz; and only calculating scalogram scales corresponding to heart rates >30 bpm. During internal validationwas found to have an execution time of between approximately one-third and one-twentieth of, and a comparable-score. During benchmarkingwas found to have the highest-score alongside, and amongst one of the lowest execution times with only,andachieving shorter execution times.is an accurate and efficient PPG beat detection algorithm, available in an open-source Matlab toolbox.