Approaches for Assessing Circadian Rest-Activity Patterns Using Actigraphy in Cohort and Population-Based Studies

Purpose of Review To review methods for analyzing circadian rest-activity patterns using actigraphy and to discuss their applications in large cohort and population-based studies. Recent Findings We reviewed several widely used approaches, including parametric analysis (i.e., cosinor model and wavelet analysis), nonparametric analysis, data adaptive approach (i.e., empirical mode decomposition), and nonlinear dynamical approach (i.e., fractal analysis). We delved into the specifics of each approach and highlighted their advantages and disadvantages. Summary Various approaches have been developed to study circadian rest-activity rhythms using actigraphy. Features extracted from these approaches have been associated with population health outcomes. Limitations exist in prior research, including inconsistencies due to various available analytical approaches and lack of studies translating findings to the context of the circadian system. Potential future steps are proposed. The review ends with an introduction to an open-source software application— ezActi2 —developed to facilitate scalable applications in analyzing circadian rest-activity rhythms.