Accelerometry-Guided Inter-Beat-Interval Assessment from Wrist Photoplethysmography

Peter H. Charlton, Joachim A. Behar, Marton Aron Goda, Jonathan Mant, Panicos A. Kyriacou

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

Abstract

Wearable photoplethysmography devices such as smart-watches can detect possible arrhythmias from inter-beat intervals (IBIs). However, photoplethysmogram (PPG) signals are highly susceptible to motion artifact. This study investigated using simultaneous accelerometry signals to determine whether IBIs can be reliably measured from PPG signals. The PPG-DaLiA and WESAD datasets were used. These datasets contain wrist accelerometry and PPG signals collected from 15 subjects during activities of daily living and mental stress tasks. IBIs were estimated from PPG signals using the 'MSPTD' beat detection algorithm. PPG-based IBIs were deemed accurate if the resulting instantaneous heart rate (IHR) was within ± 5 bpm of a reference ECG-derived IHR. The mean absolute deviation (MAD) of the accelerometry signal was able to predict whether PPG-derived IBIs were accurate, with an area under the precision-recall curve (AUPRC) of 0.82 on all data. An optimal MAD threshold of 12.9 milli-gravitational units was identified. However, performance was poorer during stress (AUPRC of 0.54). In conclusion, accelerometry can be used to identify periods when IBIs can be accurately measured from PPG signals during activities associated with movement, but is not reliable during stress.

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
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Conference

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

ASJC Scopus subject areas

  • General Computer Science
  • Cardiology and Cardiovascular Medicine

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