Clustering Insomnia Patterns by Data From Wearable Devices: Algorithm Development and Validation Study

As societies become more complex, larger populations suffer from insomnia. In 2014, the US Centers for Disease Control and Prevention declared that sleep disorders should be dealt with as a public health epidemic. However, it is hard to provide adequate treatment for each insomnia sufferer, since va...

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Bibliographic Details
Published in:	JMIR mHealth and uHealth Vol. 7; no. 12; p. e14473
Main Authors:	Park, Sungkyu, Lee, Sang Won, Han, Sungwon, Cha, Meeyoung
Format:	Journal Article
Language:	English
Published:	Canada JMIR Publications 05.12.2019
Subjects:	Age Body mass index Brain research Calories Cluster analysis Clustering Disease Efficiency Experiments Insomnia Machine learning Magnetic resonance imaging Medical research Mental disorders Multimedia Neural networks Original Paper Psychiatry Sleep Wearable computers precision psychiatry time-series data cluster analysis convolutional autoencoder insomnia unsupervised learning
ISSN:	2291-5222, 2291-5222
Online Access:	Get full text
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