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Author Notes:

Eric Reinertsen: erikr@mit.edu

Subjects:

Research Funding:

The authors acknowledge the support of the National Science Foundation Award 1636933; National Institutes of Health (Grants P50 HL117929 and R01HL136205).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Technology
  • Biophysics
  • Engineering, Biomedical
  • Physiology
  • Engineering
  • neurology
  • psychiatry
  • mobile health
  • sensors
  • heart rate variability
  • machine learning
  • accelerometry
  • HEART-RATE-VARIABILITY
  • POSTTRAUMATIC-STRESS-DISORDER
  • PATIENT HEALTH QUESTIONNAIRE
  • DEPRESSION RATING-SCALE
  • POWER SPECTRUM ANALYSIS
  • PARKINSONS-DISEASE
  • MENTAL-HEALTH
  • BIPOLAR DISORDER
  • ALZHEIMERS-DISEASE
  • PSYCHOLOGICAL STRESS

A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses

Tools:

Journal Title:

Physiological Measurement

Volume:

Volume 39, Number 5

Publisher:

, Pages 05TR01-05TR01

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Physiological, behavioral, and psychological changes associated with neuropsychiatric illness are reflected in several related signals, including actigraphy, location, word sentiment, voice tone, social activity, heart rate, and responses to standardized questionnaires. These signals can be passively monitored using sensors in smartphones, wearable accelerometers, Holter monitors, and multimodal sensing approaches that fuse multiple data types. Connection of these devices to the internet has made large scale studies feasible and is enabling a revolution in neuropsychiatric monitoring. Currently, evaluation and diagnosis of neuropsychiatric disorders relies on clinical visits, which are infrequent and out of the context of a patient's home environment. Moreover, the demand for clinical care far exceeds the supply of providers. The growing prevalence of context-aware and physiologically relevant digital sensors in consumer technology could help address these challenges, enable objective indexing of patient severity, and inform rapid adjustment of treatment in real-time. Here we review recent studies utilizing such sensors in the context of neuropsychiatric illnesses including stress and depression, bipolar disorder, schizophrenia, post traumatic stress disorder, Alzheimer's disease, and Parkinson's disease.

Copyright information:

© 2018 Institute of Physics and Engineering in Medicine

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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