Comparative Efficacy of Commercial Wearables for Circadian Rhythm Home Monitoring from Activity, Heart Rate, and Core Body Temperature

TL;DR

This study evaluates commercial wearables for non-invasive, real-world circadian rhythm monitoring, demonstrating high correlation with traditional measures and potential for scalable health assessment outside laboratories.

Contribution

It provides validation of consumer wearables for circadian rhythm assessment, comparing activity, heart rate, and temperature data with established reference measures.

Findings

High correlation between wearable-derived acrophases and reference measures (r=0.96, 0.87, 0.79).

Wearable acrophases significantly predicted chronotype (R2=0.64).

Commercial sensors can reliably assess circadian rhythms in real-life settings.

Abstract

Circadian rhythms govern biological patterns that follow a 24-hour cycle. Dysfunctions in circadian rhythms can contribute to various health problems, such as sleep disorders. Current circadian rhythm assessment methods, often invasive or subjective, limit circadian rhythm monitoring to laboratories. Hence, this study aims to investigate scalable consumer-centric wearables for circadian rhythm monitoring outside traditional laboratories. In a two-week longitudinal study conducted in real-world settings, 36 participants wore an Actigraph, a smartwatch, and a core body temperature sensor to collect activity, temperature, and heart rate data. We evaluated circadian rhythms calculated from commercial wearables by comparing them with circadian rhythm reference measures, i.e., Actigraph activities and chronotype questionnaire scores. The circadian rhythm metric acrophases, determined from commercial wearables using activity, heart rate, and temperature data, significantly correlated with the acrophase derived from Actigraph activities (r=0.96, r=0.87, r=0.79; all p<0.001) and chronotype questionnaire (r=-0.66, r=-0.73, r=-0.61; all p<0.001). The acrophases obtained concurrently from consumer sensors significantly predicted the chronotype (R2=0.64; p<0.001). Our study validates commercial sensors for circadian rhythm assessment, highlighting their potential to support maintaining healthy rhythms and provide scalable and timely health monitoring in real-life scenarios.