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Mental health is a major societal challenge. In the US, approximately 1 in 5 adults (46.6 million) experiences mental illness in a given year; 1 in 5 youth aged 13–18 (21.4%) and 13% of children aged 8-15 experiences a severe mental disorder; over 30% of adolescents and 18.1% of adults experience an anxiety disorder. Engineering technologies have the potential to improve diagnosis, intervention, and treatment of mental illness. In the Viterbi School of Engineering, a growing number of faculty are exploring research relevant to mental health.

 

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Heather Culbertson

Wearable haptic devices for emotion regulation through virtual touch

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Gale Lucas

Virtual reality and computerized assessments for depression and anxiety; web resources for prevention around depression and anxiety

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Maja Mataric

Socially assistive robotics for anxiety and depression coping and companionship and machine learning for personalized anxiety-management wearable devices

 

Shri Narayanan1

Shri Narayanan

Bio-behavioral machine intelligence to support human and autonomous decision making; novel diagnostics, personalized interventions, and tracking treatment in mental and behavioral health

Maryam Shnechi1

Maryam Shanechi

Neurotechnology development; Closed-loop neuromodulation in depression, anxiety, chronic pain; Direct electrical brain stimulation; Neural decoding of mood; Brain network modeling; System identification for brain networks.

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Mohammad Soleymani

Computational mental health assessment from verbal and nonverbal behavior (depression, PTSD, alcohol abuse); conversational virtual agents for therapeutic interviewing.

Jennifer

Jennifer Treweek

Whole-organ molecular phenotyping and circuit-mapping to inform novel treatment modalities for stress-related disorders; non-invasive approaches for modulating depression-associated neural networks.

Phebe Vayanos 1

Phebe Vayanos

Robust and fair suicide prevention interventions for vulnerable populations.

 

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