A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses. (15th May 2018)

• Record Type: Journal Article
• Authors: Reinertsen, Erik; Clifford, Gari D
• Is Part Of: Physiological measurement. Volume 39:Number 5(2018:May)
• Publication Date: 2018-05-15
• Subjects: neurology -- psychiatry -- mobile health -- sensors -- heart rate variability -- machine learning -- accelerometry; Physiology -- Measurement -- Periodicals; Patient monitoring -- Periodicals; 612
• DOI: 10.1088/1361-6579/aabf64
• Languages: English
• ISSNs: 0967-3334

Abstract

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.