面向睡眠研究的生理信号开源数据集综述

doi:10.3969/j.issn.0258-8021.2024.03.011

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Abstract The collection and labeling of clinical polysomnography data are time-consuming and costly, and the differences between different populations, collection devices, and expert labeling create challenges for sleep-related research. The open-source datasets provide rich data resources and a unified comparison platform for global researchers to conduct sleep studies. This paper reviewed the characteristics and applications of 18 open-source datasets commonly used in the field of sleep. The datasets include electroencephalogram (EEG), electrocardiogram (ECG),electro-oculogram (EOG), electromyography (EMG), etc., covering multiple clinical fields such as sleep disorders, cardiovascular diseases, obesity, etc., promoting in-depth research in the field of sleep medicine. This paper also summarized the limitations of existing sleep open-source datasets in terms of data quality, data standards, data security, sample representation and external validity, and put forward specific suggestions and prospects.

Key words： multimodal physiological signals sleep open-source datasets physiological measurement

Received: 28 April 2023

PACS:

R318

Corresponding Authors: ^* E-mail: chengyu@seu.edu.cn

About author:: ^#Member,Chinese Society of Biomedical Engineering

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	Lu Jingyi
	Yan Chang
	Yu Guangyi
	Li Jianqing
	Liu Chengyu

Cite this article:

Lu Jingyi,Yan Chang,Yu Guangyi, et al. A Review of Open-Source Datasets of Physiological Signals for Sleep Research[J]. Chinese Journal of Biomedical Engineering, 2024, 43(3): 358-368.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2024.03.011 OR http://cjbme.csbme.org/EN/Y2024/V43/I3/358

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