CALI bridges your Physiology to your Psychology

The Cognipatch was built on peer-reviewed literature from UC Berkeley, Harvard, MIT, UCSF, and Stanford Medical School.

CALI's Supporting Literature

2020

Massachusetts General Hospital / Harvard Medical School · MIT Media Lab · UC Berkeley

Monitoring Changes in Depression Severity Using Wearable and Mobile Sensors

Relevance: 31 patients with major depressive disorder wore wrist sensors recording ECG-derived heart rate variability, movement (IMU), and skin conductance for 22 hours a day. The model combining wearable and phone features tracked clinician-rated depression severity, with HRV and activity level among its strongest predictors.

2021

Chesnut, Harati, Paredes, Khan, Foudeh, Kim, Bao, Williams

Stanford University School of Medicine

Chronic Stress

Stress Markers for Mental States and Biotypes of Depression and Anxiety: A Scoping Review and Preliminary Illustrative Analysis

Relevance: Reviews the evidence linking chronic-stress physiology, especially reduced heart rate variability, to depression and anxiety, and proposes physiological "biotypes" as a more objective alternative to symptom checklists alone.

2025

Kargarandehkordi, Li, Lin, Phillips, Benzo, Washington

University of California, San Francisco

Biosensors

Fusing Wearable Biosensors with Artificial Intelligence for Mental Health Monitoring: A Systematic Review

Relevance: Systematic review of 48 studies combining wearable ECG, HRV, electrodermal activity, and accelerometer data with AI to detect depression, anxiety, and stress, supporting multi-signal sensing over any single channel.

2025

Unzueta Saavedra, Deaso, Austin, Cadavid, Kraff, Knowles

Harvard Medical School · Boston Children's Hospital

JMIR Formative Research

Smartphone Ecological Momentary Assessment and Wearable Activity Tracking in Pediatric Depression: Cohort Study

Relevance: Fitbit-tracked movement data (IMU) showed adolescents with major depressive disorder took meaningfully fewer daily steps than healthy controls, supporting passive movement sensing as an objective depression marker.

Our Scientific Rationale

Aggregate evidence from the research literature supporting the physiological biomarker approach to anxiety and depression monitoring.

Anxiety disorders are associated with lower resting heart rate variability across 36 studies covering more than 4,300 people. (Chalmers et al. 2014, Frontiers in Psychiatry)
Heart rate variability is also altered in major depression, shown in a 21-study meta-analysis (2,250 patients, 1,982 controls) restricted to unmedicated adults. (Koch et al. 2019, Psychological Medicine)
Muscle activity (EMG) was the second most sensitive of the physiological measures tested (d = 0.71) for anxiety in children and adolescents, in a 25-study meta-analysis of 2,502 participants. Skin conductance level ranked first (d = 0.83). (Ko et al. 2024, Stress and Health)
In a 359-person study, more depression and anxiety symptoms and diagnoses were associated with larger disturbances in sleep, circadian rhythm, and physical activity measured by a wrist-worn accelerometer. (Difrancesco et al. 2019, Depression and Anxiety)
Personalized deep learning models predicted most of the variation in anxiety symptoms (R² = 0.748) in a 32-person study using smartphone sensors. (Jacobson & Bhattacharya 2022, Behaviour Research and Therapy)
Wearable movement and sleep data predicted anxiety symptom deterioration over 17–18 years in 265 adults. (Jacobson et al. 2021, Journal of Affective Disorders)

Join CALI's Community

We are actively seeking psychiatric research institutions, academic medical centers, and clinical investigators interested in physiological monitoring for anxiety and depression. Collaborations for protocol development and multi-site study participation welcome.

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Study Status

Multi-site clinical study currently in planning phase. IRB protocol under preparation. Target participant population: adults with a confirmed DSM-5 anxiety disorder or major depressive disorder diagnosis, currently under psychiatric care.