What question did this study set out to answer?

To systematically review passively collected digital biomarkers across modalities and analytic techniques for identifying mood states in bipolar disorder and outline priorities for clinical implementation.

August 15, 2026JMIR Mental HealthOpen Access

Digital Markers for Passive Remote Monitoring of Bipolar Disorder: Systematic Review

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Authors

TKThomas P. Kutcher ICIsha Chakraborty KKKristin M. Kostick

Discussion

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Overview

Systematic review demonstrates that passive digital markers reflect mood state shifts in bipolar disorder, highlighting the potential for early episode detection.

Key Points

To systematically review passively collected digital biomarkers across modalities and analytic techniques for identifying mood states in bipolar disorder and outline priorities for clinical implementation.
Searched MEDLINE, PsycINFO, Scopus, IEEE Xplore, and ACM Digital Library through February 16, 2026, adhering to PRISMA guidelines.
Included 57 peer-reviewed studies evaluating passively captured digital markers in adults with bipolar I or bipolar II disorder across manic, hypomanic, depressive, mixed, and euthymic states.
Identified eight primary digital marker domains: physical activity, heart rate, electrodermal activity, geolocation, smartphone use, light exposure, sleep, and speech.
Depressive states consistently correlated with decreased mobility, reduced socialization, delayed sleep onset, and lower daytime light exposure, while mania and hypomania correlated with heightened activity and reduced sleep duration.
Machine learning models in 21 studies demonstrated predictive potential, but clinical adoption is limited by small cohorts (60% with N≤50), lack of external validation, short monitoring intervals, and unaligned clinical labels.

Cite This Study

Kutcher et al. (2026) studied this question.

synapsesocial.com/papers/6a801a1a75c2e31742c8697c https://doi.org/10.2196/94819

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August 15, 2026JMIR Mental HealthOpen Access

Digital Markers for Passive Remote Monitoring of Bipolar Disorder: Systematic Review

View Full Paper

Ask AI

Bookmark

Authors

TKThomas P. Kutcher ICIsha Chakraborty KKKristin M. Kostick

Discussion

Member takes

Overview

Systematic review demonstrates that passive digital markers reflect mood state shifts in bipolar disorder, highlighting the potential for early episode detection.

Key Points

To systematically review passively collected digital biomarkers across modalities and analytic techniques for identifying mood states in bipolar disorder and outline priorities for clinical implementation.
Searched MEDLINE, PsycINFO, Scopus, IEEE Xplore, and ACM Digital Library through February 16, 2026, adhering to PRISMA guidelines.
Included 57 peer-reviewed studies evaluating passively captured digital markers in adults with bipolar I or bipolar II disorder across manic, hypomanic, depressive, mixed, and euthymic states.
Identified eight primary digital marker domains: physical activity, heart rate, electrodermal activity, geolocation, smartphone use, light exposure, sleep, and speech.
Depressive states consistently correlated with decreased mobility, reduced socialization, delayed sleep onset, and lower daytime light exposure, while mania and hypomania correlated with heightened activity and reduced sleep duration.
Machine learning models in 21 studies demonstrated predictive potential, but clinical adoption is limited by small cohorts (60% with N≤50), lack of external validation, short monitoring intervals, and unaligned clinical labels.

Cite This Study

Kutcher et al. (2026) studied this question.

synapsesocial.com/papers/6a801a1a75c2e31742c8697c https://doi.org/10.2196/94819

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