Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures

Movement Disorders

Volumn 31, Issue 9, 2016, Pages 1314-1326

  Kubota, Ken J ^a   Chen, Jason A ^b,c   Little, Max A ^d,e  

^a TranSMART Foundation   (United States)

^b Verge Genomics   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d ASTON UNIVERSITY   (United Kingdom)

^e MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

artificial intelligence; data science; digital sensors; machine learning; wearables

Indexed keywords

ACCELERATION; ACCURACY; ALGORITHM; ARTICLE; BLOOD VOLUME; DISEASE SEVERITY ASSESSMENT; ELECTRONIC SENSOR; HUMAN; LIGHT; MACHINE LEARNING; MULTIFACTOR DIMENSIONALITY REDUCTION; NEUROLOGY; PARKINSON DISEASE; PREDICTION; PRIORITY JOURNAL; QUALITY CONTROL; SIGNAL PROCESSING; SKIN TEMPERATURE; SOUND PRESSURE; SUPERVISED MACHINE LEARNING; TREATMENT RESPONSE; UNSUPERVISED MACHINE LEARNING; WEARABLE SENSOR;

EID: 84985931042     PISSN: 08853185     EISSN: 15318257     Source Type: Journal    
DOI: 10.1002/mds.26693     Document Type: Article

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