Robust Peak Detection for Photoplethysmography Signal Snalysis

Marton A. Goda, Peter H. Charlton, Joachim A. Behar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Efficient and accurate evaluation of long-term photo-plethysmography (PPG) recordings is essential for both clinical assessments and consumer products. In 2021, the top opensource peak detectors were benchmarked on the Multi-Ethnic Study of Atherosclerosis (MESA) database consisting of polysomnography (PSG) recordings and continuous sleep PPG data, where the Automatic Beat Detector (Aboy) had the best accuracy. This work presents Aboy++, an improved version of the original Aboy beat detector. The algorithm was evaluated on 100 adult PPG recordings from the MESA database, which contains more than 4.25 million reference beats. Aboy++ achieved an F1-score of 85.5%, compared to 80.99% for the original Aboy peak detector. On average, Aboy++ processed a 1 hour-long recording in less than 2 seconds. This is compared to 115 seconds (i.e., over 57-times longer) for the open-source implementation of the original Aboy peak detector. This study demonstrated the importance of developing robust algorithms like Aboy++ to improve PPG data analysis and clinical outcomes. Overall, Aboy++ is a reliable tool for evaluating long-term wearable PPG measurements in clinical and consumer contexts. The open-source algorithm is available on the physiozoo.com website.

Original languageEnglish
Title of host publicationComputing in Cardiology, CinC 2023
ISBN (Electronic)9798350382525
DOIs
StatePublished - 2023
Event50th Computing in Cardiology, CinC 2023 - Atlanta, United States
Duration: 1 Oct 20234 Oct 2023

Publication series

NameComputing in Cardiology

Conference

Conference50th Computing in Cardiology, CinC 2023
Country/TerritoryUnited States
CityAtlanta
Period1/10/234/10/23

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine
  • General Computer Science

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