单线大腿心电图数据集 (tOLIet) 分析了BMI对心脏信号质量的影响
Aline Santos Silva1,2,3, Miguel Velhote Correia4, Sérgio Matoso Laranjo5
1INESC TEC, Faculdade de Engenharia, Universidade do Porto. R. Dr. Roberto Frias., 4200-465, Porto, Portugal. aline.s.silva@inesctec.pt.
Scientific data
|March 13, 2026
概括
我们开发了一种新的马桶座电心电图 (ECG) 系统,用于方便的心血管监测. 这一数据集推进了以大腿为基础的心电图分析,以改善健康评估.
科学领域:
- 生物医学工程 生物医学工程
- 心血管健康 心血管健康
- 医疗信息学 医疗信息学
背景情况:
- 之前的研究引入了一种"隐形"心电图 (ECG) 系统,使用集成在所座椅中的电极.
- 该系统捕获来自大腿的心电图信号,为心血管监测提供一种非侵入性的方法.
研究的目的:
- 引入tOLIet数据集,包括单线大腿心电图,以促进心血管评估的进步.
- 为探索远程和不引人注目的生理监测新方法的研究人员提供一个有价值的资源.
主要方法:
- tOLIet数据集包括来自86个人的149个单线大腿心电图记录.
- 每个记录包含来自所座椅电极的四个差分信号和来自医院级12心电图的参考数据.
- 进行了性别特定的分析,将有效的信号百分比与身体质量指数 (BMI) 进行比较.
主要成果:
- 这项研究提供了一个全面的数据集,用于基于大腿的心电图分析.
- 对BMI进行了信号质量评估和性别特异性分析.
- 启动了对影响大腿ECG获取的因素的探索.
结论:
- tOLIet数据集支持使用新型,集成的所座椅心电图技术推进心血管评估.
- 结果指导系统设计和定制,以提高不同人群的信号可靠性.
- 这项工作突出了不引人注目的传感对于广泛的心血管健康监测的潜力.
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