Comparison of rest-activity rhythm metrics from apple watch and ActiGraph devices

Study Objectives Objective rest-activity rhythm (RAR) disturbances are linked with major disease outcomes. If consumer wearables yield RAR measures comparable to traditional research devices, these popular devices could provide a scalable option for clinical applications of RAR monitoring, e.g., risk factor screening. Methods We asked convenience sample of participants (analytic n = 23; mean age = 27 years; 80% female) to wear Apple Watch and ActiGraph devices on separate wrists for one week. We derived a time series of activity counts from the raw accelerometer data, then extracted non-parametric (interdaily stability (IS), relative amplitude (RA), intradaily variability (IV)) and extended-cosine (pseudo-F, amplitude, up-mesor, acrophase, down-mesor) RAR variables. Spearman correlation coefficients (R) assessed association. Intraclass Correlation Coefficients (ICCs) assessed both agreement (closeness of values) and consistency (similarity of rankings) of RAR measures from the two devices. Results The devices’ RAR measures were highly correlated (Spearman R range: 0.7-0.9, p<.001). Agreement ICCs indicated good reliability for most metrics (ICC = 0.74–0.85), except for amplitude (which is highly dependent on the activity-count’s scale; ICC = 0.01). Agreement ICCs had wide confidence intervals, most reached at least the moderate agreement range (e.g., IS agreement ICC = 0.77; 95% CI: 0.47–0.90). Consistency ICCs were higher and exhibited narrower 95% CIs, with estimates in the good-to-excellent range (e.g., IS consistency ICC = 0.84; 95% CI: 0.61–0.92). Conclusions Good-to-excellent consistency ICCs indicate that these devices yield similar participants rank-orderings on these RAR measures. However, there was systematic disagreement, suggesting absolute values from different devices’ measures should not be pooled.