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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| Published in | Scientific data Vol. 11; no. 1; pp. 1091 - 9 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
05.10.2024
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2052-4463 2052-4463 |
| DOI | 10.1038/s41597-024-03950-5 |
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| Abstract | 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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| AbstractList | 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. 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.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. Abstract 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. |
| ArticleNumber | 1091 |
| Author | Li, Yong-Xian Zong, Shou-Xin Yao, Xin-Yu Mu, Si-Qi Shen, Yan-Fei Huang, Jiong-Ling |
| Author_xml | – sequence: 1 givenname: Yong-Xian orcidid: 0009-0007-5611-6917 surname: Li fullname: Li, Yong-Xian organization: Beijing Sport University, School of Sport Engineering, Beijing Sport University, China Sports Big Data Center – sequence: 2 givenname: Jiong-Ling surname: Huang fullname: Huang, Jiong-Ling organization: Beijing Sport University, School of Sport Engineering, Beijing Sport University, China Sports Big Data Center – sequence: 3 givenname: Xin-Yu surname: Yao fullname: Yao, Xin-Yu organization: Beijing Sport University, School of Sport Engineering, Beijing Sport University, China Sports Big Data Center – sequence: 4 givenname: Si-Qi surname: Mu fullname: Mu, Si-Qi email: musiqi@bsu.edu.cn organization: Beijing Sport University, School of Sport Engineering, Beijing Sport University, China Sports Big Data Center, Beijing Sport University, Key Laboratory of Exercise and Physical Fitness – sequence: 5 givenname: Shou-Xin surname: Zong fullname: Zong, Shou-Xin organization: Beijing Sport University, School of Sport Engineering, Beijing Sport University, China Sports Big Data Center – sequence: 6 givenname: Yan-Fei surname: Shen fullname: Shen, Yan-Fei organization: Beijing Sport University, School of Sport Engineering, Beijing Sport University, China Sports Big Data Center, Beijing Sport University, Engineering Research Center of Strength and Conditioning Training Key Core Technology Integrated System and Equipment, Ministry of Education |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39368975$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | 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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| Title | A ballistocardiogram dataset with reference sensor signals in long-term natural sleep environments |
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