Machine learning-based prediction of restless legs syndrome using digital phenotypes from wearables and smartphone data

Machine learning-based prediction of restless legs syndrome using digital phenotypes from wearables and smartphone data

Abstract Restless legs syndrome (RLS) is a relatively common neurosensory disorder that causes an irresistible urge for leg movement. RLS causes sleep disturbances and reduced quality of life, but accurate diagnosis remains challenging owing to the reliance on subjective reporting. This study aimed...

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Bibliographic Details
Main Authors: Jingyeong Jeong, Yoonseo Jeon, Hyungju Kim, Ji Won Yeom, Yu-Bin Shin, Sujin Kim, Seung Pil Pack, Heon-Jeong Lee, Taesu Cheong, Chul-Hyun Cho
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Restless legs syndrome
Digital phenotypes
Circadian rhythm
Machine learning
Prediction
Online Access:https://doi.org/10.1038/s41598-025-01215-8
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https://doi.org/10.1038/s41598-025-01215-8

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