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

Abstract

Wearable photoplethysmography devices such as smartwatches 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.