Beat detection is a key step in the analysis of photoplethysmogram (PPG) signals. The 'MSPTD' algorithm was recently identified as one of the most accurate beat detection algorithms, but its current open-source implementation is substantially more computationally expensive than other leading algorithms such as 'qppgfast' . The aim of this work was to develop a more efficient, open-source implementation of the 'MSPTD' algorithm. Five potential improvements were identified to increase efficiency. Each potential improvement was evaluated in turn, and an optimal algorithm configuration named 'MSPTDfast' was developed which incorporated all of the improvements found to reduce algorithm execution time whilst not substantially reducing the accuracy of beat detection. Performance was assessed using data collected from young adults during a lunchbreak in the PPG-DaLiA dataset. The data consisted of wrist PPG signals acquired using an Empatica E4 device, alongside simultaneous ECG signals from which reference heartbeat timings were obtained. 'MSPTDfast' was found to be substantially more efficient than 'MSPTD' (a reduction in execution time of 64.4%), with minimal difference in beat detection accuracy (F1-score 87.8% vs. 87.7%). In addition, the performance of 'MSPTDfast' was much closer to that of the state-of-the-art 'qppgfast' algorithm than the 'MSPTD' algorithm, with a comparable F1-score (87.4% vs. 87.7%), and an execution time which was only 30.0% longer than that of 'qppgfast' (vs. 257.4% longer for 'MSPTD' ). In conclusion, 'MSPTDfast' is an efficient and accurate open-source PPG beat detection algorithm with a substantially faster execution time than 'MSPTD' . It is available under the permissive MIT licence.

P.H.C. has performed consultancy work for Cambridge University Technical Services, has received travel funds from VascAgeNet, and has received honoraria from IOP Publishing and Emory University (the latter not received personally). J.M. has performed consultancy work for BMS/ Pfizer and Omron.

This study is funded by the British Heart Foundation [FS/20/20/34626].

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The study used ONLY openly available human data that were originally located at: https://doi.org/10.24432/C53890

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