Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning

Annual Review of Clinical Psychology

Volumn 13, Issue , 2017, Pages 23-47

  Mohr, David C ^a   Zhang, Mi ^b   Schueller, Stephen M ^a  

^a NORTHWESTERN UNIVERSITY   (United States)

^b Michigan State University   (United States)

Author keywords

Machine learning; Mental health; MHealth; Pervasive health; Sensors; Wearables

Indexed keywords

BIOLOGICAL MARKER;

ACTIVE MACHINE LEARNING; ARTICLE; BEHAVIOR; BEHAVIOR THERAPY; BIPOLAR DISORDER; COMPUTER; DATA ANALYSIS; DATA EXTRACTION; DATA MINING; DEEP MACHINE LEARNING; DEPRESSION; EPIDEMIOLOGICAL DATA; ETHICS; EXPIRATION DATE; GENERAL DEVICE; HUMAN; INFORMATION PROCESSING; INTEGRATION; KNOWLEDGE; MACHINE LEARNING; MEASUREMENT ACCURACY; MEDICAL TECHNOLOGY; MENTAL HEALTH; MENTAL HEALTH CARE; MOBILE PHONE; MOOD; NONHUMAN; PRIVACY; QUALITY CONTROL; REPRODUCIBILITY; SCHIZOPHRENIA; SEMISUPERVISED MACHINE LEARNING; SENSOR; SLEEP; SOCIAL ENVIRONMENT; SOCIAL MEDIA; STRESS; SUPERVISED MACHINE LEARNING; UNCERTAINTY; UNSUPERVISED MACHINE LEARNING; WEARABLE DEVICE; MENTAL DISEASE; NEUROPHYSIOLOGICAL MONITORING; TELEMEDICINE;

HUMANS; MACHINE LEARNING; MENTAL DISORDERS; NEUROPHYSIOLOGICAL MONITORING; TELEMEDICINE;

EID: 85019136128     PISSN: 15485943     EISSN: 15485951     Source Type: Book Series    
DOI: 10.1146/annurev-clinpsy-032816-044949     Document Type: Article

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