Profiling the Propagation of Error from PPG to HRV Features in a WearableudPhysiological-Monitoring Device

摘要

Wearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantiveudstudies of their performance when measuring the physiology of ambulatory patients. In this paper, we investigate the reliability of the heartrateudsensor in an exemplar “wearable" wrist-worn monitoring system (the Microsoft Band 2); our experiments quantify the propagation ofuderror from (i) the photoplethysmogram (PPG) acquired by pulse oximetry, to (ii) estimation of heart rate (HR), and (iii) subsequent calculationudof heart rate variability (HRV) features. Our experiments confirm that motion artefacts account for the majority of this error, and show thatudthe unreliable portions of heart rate data can be removed, using the accelerometer sensor from the wearable device. Our experiments furtherudshow that acquired signals contain noise with substantial energy in the high-frequency band, and that this contributes to subsequent variabilityudin standard HRV features often used in clinical practice. We finally show that the conventional use of long-duration windows of data is notudneeded to perform accurate estimation of time-domain HRV features.