Analysis and Prediction of Cycling Behavior's Effect on Sleep Quality by Means of Machine Learning
Year: 2025
Type: conference-paper
Study design: Observational Study
Abstract: Sleep quality is quite important for health nowadays, influencing how the body works and how it feels mentally. Physical activity can be an alternative without medication to make sleep better. But various kinds of exercise have unique effects on how sleep is helped. Cycling is common as moderate aerobic activity having special body and mind effects giving a big influence on sleep. We examined how cycling frequency, intensity, and duration affect sleep duration, trouble falling asleep, and how content one feels using surveys mixed with machine learning, developing many prediction models. Results are positive for cycling improving sleep factors, with random forest model being best for predicting cycling's sleep effect. Strong data for health and policy is provided by this study, showing why cycling matters for healthy life now.
Author: Jinqiang Huang
Institution: Zhangjiajie College
Language: English
Topic: Sleep and related disorders
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4412790027