ArticleSensors (Basel, Switzerland)2026
Integrating Wearable Temperature, Activity, Melanopic Light, and Lifelog Data to Assess Circadian-Behavioral Coupling in Free-Living Conditions.
Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Circadian-behavioral misalignment, defined as a mismatch between internal circadian timing and daily sleep activity behavior, is associated with sleep quality, daytime function, cognitive performance, and long-term health risks. However, practical approaches for integrating circadian-phase-related physiological markers with behavioral and environmental sensing under free-living conditions remain limited. This study presents a multimodal wearable and lifelog monitoring workflow that combines a heat-flux-based wearable temperature-estimation sensor, a wrist-worn actigraph, melanopic equivalent daylight illuminance (EDI) measurement, and web-based lifelog entries. Ten healthy young adults were monitored for approximately one week in daily life. The midpoint between the descending and ascending mid-level crossings of the nocturnal temperature rhythm was extracted as a circadian-phase-related temperature rhythm marker. In a practical comparison with gastrointestinal temperature measured using an ingestible capsule, the wearable-derived rhythm marker showed a mean absolute difference of 27.1 ± 16.6 min. The temporal difference between the two markers was defined as the phase angle, and coupling stability was evaluated using phase angle variability and the correlation between the markers. After excluding one participant who traveled overseas, clustering and principal component analyses were used to visualize exploratory participant-level differences in circadian-behavioral coupling. Integrated analysis with melanopic EDI, activity, and lifelog-derived features suggested that light exposure, activity timing, and behavioral timing may provide contextual information for interpreting coupling patterns in this small cohort. These findings support the feasibility of a sensing system application that integrates physiological, behavioral, environmental, and lifelog data for the exploratory assessment of circadian-behavioral coupling under free-living conditions, rather than the development of new sensor hardware.
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