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

ABSTRACT: BACKGROUND: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 various behavioral characteristics influence symptoms of insomnia collectively. OBJECTIVE:We aim to develop a neural-net based unsupervised user clustering method towards insomnia sufferers in order to clarify the unique traits for each derived groups. Unlike the current diagnosis of insomnia that requires qualitative analysis from interview results, the classification of individuals with insomnia by using various information modalities from smart bands and neural-nets can provide bette

SUBMITTER: Park S 

PROVIDER: S-EPMC6923760 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature