A ballistocardiogram dataset with reference sensor signals in long-term natural sleep environments

To facilitate unobtrusive and continuous sleep monitoring and promote intelligent sleep quality assessment, we present a dataset that includes multiple nights of continuous ballistocardiogram (BCG) data collected using piezoelectric film sensors from 32 subjects in their regular sleep environments....

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Bibliographic Details
Published inScientific data Vol. 11; no. 1; pp. 1091 - 9
Main Authors Li, Yong-Xian, Huang, Jiong-Ling, Yao, Xin-Yu, Mu, Si-Qi, Zong, Shou-Xin, Shen, Yan-Fei
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 05.10.2024
Nature Publishing Group
Nature Portfolio
Subjects
692/53
692/700/478
Accuracy
Algorithms
Ballistocardiography
Data Descriptor
Datasets
Electrocardiography
Electroencephalography
Environmental monitoring
Heart Rate
Humanities and Social Sciences
Humans
Insomnia
multidisciplinary
Physiology
Quality control
Respiration
Science
Science (multidisciplinary)
Sensors
Sleep
Sleep disorders
Vital signs
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Summary:To facilitate unobtrusive and continuous sleep monitoring and promote intelligent sleep quality assessment, we present a dataset that includes multiple nights of continuous ballistocardiogram (BCG) data collected using piezoelectric film sensors from 32 subjects in their regular sleep environments. Besides, the referenced heart rate and respiratory data are also recorded by reference sensors to validate the accuracy of the cardiac and respiratory components extracted from the BCG signals. The dataset serves as a foundation for research on unobtrusive vital sign monitoring based on BCG signals, offering data support for the evaluation and optimization of sleep quality.
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ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-024-03950-5