Wearable Sensor Data for Panic Attack Risk Across Mental Health Conditions

Passive sensing data from Oura Rings collected over 6 months from 182 young adults with and without psychiatric diagnoses. The study identifies physiological risk factors for next-day panic attacks, with distinct associations found across different mental health conditions. The dataset was authored by Dheeraj Dhanvee Kairamkonda and last updated in April 2026.

Use Cases

• Predicting panic attack risk based on wearable-derived physiological measures like inactivity and heart rate variability.
• Analyzing diagnosis-specific physiological patterns, such as respiratory rate variation for depression or inactivity for panic disorder.
• Investigating the effect of cumulative physiological patterns from data aggregation windows up to 7 days before an event.
• Developing personalized risk models for preventive mental health interventions using continuous monitoring data.

Strengths

• Data spans over 6 months of continuous passive sensing from a defined cohort of 182 participants.
• Includes participants with diverse mental health statuses, including those with panic disorder, depression, and no diagnosis.
• Analysis identifies specific, diagnosis-dependent physiological associations with panic attack risk.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The primary file format is DOCX (1.7 MB), which may not be optimal for direct data analysis.

Provenance

Source

figshare

Collection Method

Passive data collection via Oura Rings worn by study participants.

Time Range

Over 6 months (specific dates not provided).

Freshness

Last updated 2026-04-20 05:22:41; freshness should be verified.

Geography

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