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

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.

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Publication Details

Journal
Scientific Data
Published
2025-10-17
DOI
https://doi.org/10.1038/s41597-025-05936-3
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Peilin Lu, Biyong Zhang, Libing Liu, Tan Lyu et al.
Scientific Data
Heart Rate Variability and Autonomic Control
article

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

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

Abstract

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.

Scientific DataVol. 12(1)
Sir Run Run Shaw Hospital (CN), Suzhou University of Science and Technology (CN), Huazhong University of Science and Technology (CN), Eindhoven University of Technology (NL)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 55%
Heart Rate Variability and Autonomic Control
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A ballistocardiogram dataset with reference ECG signals for bed-based heart rhythm assessment — Peilin Lu, Biyong Zhang, et al. · Scientific Data (2025) | TGRS Research Map | TGRS