A Review of Open-Source Datasets of Physiological Signals for Sleep Research
Lu Jingyi1&, Yan Chang1&, Yu Guangyi1, Li Jianqing1,2, Liu Chengyu1#*
1(State Key Laboratory of Digital Medical Engineering, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China) 2(School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China)
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.
陆敬怡, 颜昌, 于广义, 李建清, 刘澄玉. 面向睡眠研究的生理信号开源数据集综述[J]. 中国生物医学工程学报, 2024, 43(3): 358-368.
Lu Jingyi, Yan Chang, Yu Guangyi, Li Jianqing, Liu Chengyu. A Review of Open-Source Datasets of Physiological Signals for Sleep Research. Chinese Journal of Biomedical Engineering, 2024, 43(3): 358-368.
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