Clinical application of physical activity time series: toward detection of early warning of depression

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In this study, we aimed at establishing a personalized early-warning-detection-system (sign-based Ecological Momentary Assessment) for mood disorders. We measured locomotor activity around clinical bifurcation points (e.g. relapse, exacerbation, and remission) and treatment, and then developed a behavioral biomarker for the diseases, characterizing motor abnormalities, specifically, alterations in behavioral organization and/or an increased intermittency of locomotor activity. In addition, we examined the underlying theoretical background of the behavioral organization by the mathematical modeling. Through these clinical and mathematical validations of our behavioral biomarker, we could obtain a firm basis for realization of early warning detection of the mood disorders, triggered by alteration in locomotor activity.