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Rest-Activity Rhythms as Digital Biomarkers: Predicting Relapse in Major Depressive Disorder via Actigraphy

MedXY Editorial TeamFeb 21, 2026
actigraphycircadian rhythmsmajor depressive disorderRelapse Prediction

The Challenge of Relapse in Major Depressive Disorder

Major depressive disorder (MDD) is a chronic and recurrent condition that imposes a staggering burden on global health systems. Despite the availability of various pharmacotherapeutic and psychotherapeutic interventions, a significant proportion of patients experience a relapsing-remitting course. Predicting these relapses remains one of the most formidable challenges in clinical psychiatry. Historically, clinicians have relied on subjective patient self-reports or intermittent clinical interviews—methods that are often hindered by recall bias and the late appearance of symptoms.

There is an urgent clinical need for objective, continuous, and non-invasive biomarkers that can signal an impending depressive episode before a full clinical relapse occurs. Recent advances in wearable technology, specifically actigraphy, have opened new avenues for digital phenotyping. By monitoring rest-activity rhythms (RARs) and sleep-wake cycles in a naturalistic environment, actigraphy provides a high-resolution window into the biological rhythms that are frequently disrupted in mood disorders.

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This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

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