Heart rate circadian phase and hyperarousal as wearable digital phenotyping of insomnia: An interpretable machine learning study

Objective This study evaluates ML approaches for insomnia classification using physiological and behavioral data from wearable devices. SHAP analysis identifies key predictors, highlighting the relationship between sleep disturbances and digital phenotypes and emphasizing clinical plausibility as a...

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Autors principals:	Minji Kim, Seojin Yun, Hyungju Kim BS, Emma Matsushita, Ji Won Yeom MD, PhD, Sujin Kim MD, Seung Pil Pack PhD, Heon-Jeong Lee MD, PhD, Taesu Cheong PhD, Chul-Hyun Cho MD, PhD
Format:	Artigo
Idioma:	Inglês
Publicat:	SAGE Publishing 2026-06-01
Col·lecció:	Digital Health
Accés en línia:	https://doi.org/10.1177/20552076261458929
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