Circadian rhythms using an accelerometer-based sensor network

This paper investigates the influence of chronotype and social zeitgebers on circadian rhythm using an accelerometer-based sensor network. Participants with different chronotypes (i.e., morning types and evening types) were recruited to participate in this study. Chronotype was determined by participant responses to the Morningness-Eveningess Questionnaire (MEQ). A wearable accelerometer- based sensor network was used for ambulatory monitoring of participants?? circadian rhythm based on physical activity. Acceleration signals collected from the portable accelerometers were processed by circadian rhythm estimation algorithms including: sleep/wake cycle analysis, Cosinor analysis, and Poincar?? plot analysis. From an analysis of the indices generated by the proposed circadian rhythm estimation algorithms, we conclude that significant differences exist in circadian rhythms among various chronotypes. In addition, according to our analysis, we conclude that chronotype does indeed influence circadian rhythms, with the most significant difference observed for sleep midpoint. Additionally, social zeitgebers also impact the circadian rhythms of evening types.