A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors
arXiv:2502.00973v2 Announce Type: replace Abstract: Mental health problems such as stress, anxiety, and depression affect millions of people worldwide. These conditions are usually assessed using questionnaires, which rely on how people describe their own feelings. In this study, we explore whether a wearable device can help measure mental health using physical signals from the body. The device records small changes in blood flow and tissue activity from the fingertip. We collected data from 132 adults across 19 countries and compared these signals with mental health questionnaire results. We
This research emerges as wearable technology matures and AI-driven data analysis becomes more sophisticated, enabling non-invasive health monitoring beyond traditional methods.
This study offers a new pathway for objective, continuous mental health assessment, potentially moving beyond subjective self-reporting and revolutionizing early detection and intervention.
The potential to quantify mental health states using physiological biomarkers, offering a more data-driven and potentially less stigmatizing approach to assessment.
- · Wearable tech companies
- · Healthcare providers
- · AI developers
- · Mental health patients
- · Traditional diagnostic methods reliant solely on questionnaires
Wearable devices gain new, significant medical utility as a diagnostic tool for mental health.
Insurance models and mental health treatment plans could integrate continuous physiological data for personalized interventions.
Ethical and privacy frameworks for biometric mental health data will become a critical area of societal and regulatory debate.
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