What question did this study set out to answer?

The central aim is to identify and validate digital biomarkers for detecting depressive episodes in bipolar disorder.

February 24, 2026npj Mental Health ResearchOpen Access

A systematic exploration of digital biomarkers for the detection of depressive episodes in bipolar disorder

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A longitudinal study identifies digital biomarkers for depressive episodes in bipolar disorder, suggesting new diagnostic avenues.

The central aim is to identify and validate digital biomarkers for detecting depressive episodes in bipolar disorder.
Conducted a longitudinal study with 133 bipolar disorder participants over a median of 251 days.
Analyzed multivariate, densely sampled data using explainable machine learning.
Included self-reported mood, energy, anxiety, and passive data from an Oura ring.
Identified robust digital biomarkers such as lower daily mood variability and higher sleep onset latency variability.
Achieved an AU-ROC performance of 0.82 ± 0.03 for self-reported daily mood features.
Demonstrated the value of multimodal data in enhancing the detection of depressive episodes.

Halabi et al. (2026) studied this question.

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