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<p>The unobtrusive collection of ballistocardiogram (BCG) data makes it a promising option for continuous, low-effort cardiovascular monitoring. Key heart rhythm metrics such as heart rate (HR), inter-beat interval (IBI), and heart rate variability (HRV) are widely recognized indicators of cardiovascular health. The primary clinical goal of BCG applications is to accurately estimate these metrics. Most previous studies have primarily examined healthy young adults, which contrasts significantly with high-risk populations, such as older adults or cardiac patients, who would benefit the most from long-term monitoring in everyday settings. To bridge this gap, we collected nighttime BCG recordings from 46 middle-aged and elderly participants during natural sleep. The subjects included individuals with atrial arrhythmias, ventricular arrhythmias, myocardial ischemia, and nonclinical sinus arrhythmias. This dataset also contains synchronized Holter monitor recordings, which may enhance the use of BCG in assessing cardiac rhythms and detecting early cardiovascular diseases, while also testing the generalizability of BCG algorithms in real-world scenarios involving various health conditions.</p>

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A ballistocardiogram dataset with reference ECG signals for bed-based heart rhythm assessment

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月17日

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  • Jiafeng Qiu,
  • Tan Lyu,
  • Libing Liu,
  • Jiayi Cheng,
  • Peilin Lu,
  • Biyong Zhang,
  • Gang Shen

摘要

The unobtrusive collection of ballistocardiogram (BCG) data makes it a promising option for continuous, low-effort cardiovascular monitoring. Key heart rhythm metrics such as heart rate (HR), inter-beat interval (IBI), and heart rate variability (HRV) are widely recognized indicators of cardiovascular health. The primary clinical goal of BCG applications is to accurately estimate these metrics. Most previous studies have primarily examined healthy young adults, which contrasts significantly with high-risk populations, such as older adults or cardiac patients, who would benefit the most from long-term monitoring in everyday settings. To bridge this gap, we collected nighttime BCG recordings from 46 middle-aged and elderly participants during natural sleep. The subjects included individuals with atrial arrhythmias, ventricular arrhythmias, myocardial ischemia, and nonclinical sinus arrhythmias. This dataset also contains synchronized Holter monitor recordings, which may enhance the use of BCG in assessing cardiac rhythms and detecting early cardiovascular diseases, while also testing the generalizability of BCG algorithms in real-world scenarios involving various health conditions.