Predicting sleep quality with digital biomarkers and artificial neural networks.

ABSTRACT:

Introduction

Modern society's increasing stress and irregular lifestyles have led to rising insomnia prevalence, making sleep quality assessment crucial for health management. This study investigates the relationship between heart rate variability (HRV) collected from wearable devices and sleep quality, specifically focusing on wake-after-sleep-onset (WASO) as a critical marker of sleep fragmentation. We aimed to develop predictive models for next-day sleep quality using continuous digital biomarkers.

Methods

We conducted two experiments (winter and summer 2023) with 82 participants who wore Samsung Galaxy Watch Active 2 devices during wakefulness. Biometric data including HRV signals, daily step counts, and physiological indicators were collected alongside subjective questi

SUBMITTER: Lee H 

PROVIDER: S-EPMC12308496 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature