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

• 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

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...