A Multi-Pathology Ballistocardiogram Dataset for Cardiac Function Monitoring and Arrhythmia Assessment
Cardiac dysfunction plays a critical role in clinical diagnostics and treatment. Although traditional methods like echocardiography and blood biomarkers are effective, their limitations highlight the need for noninvasive and continuous monitoring solutions. Ballistocardiography (BCG), which captures subtle body vibrations generated by cardiac mechanical activity, has emerged as a promising tool for remote cardiovascular monitoring. This study presents a multi-pathology BCG dataset comprising recordings from healthy participants, patients with heart failure (HF), and those with arrhythmias such as atrial fibrillation (AF), premature ventricular contractions (PVCs), and premature atrial contractions (PACs). Synchronized electrocardiogram (ECG) and M-mode echocardiography recordings are also included, providing a comprehensive overview of cardiac function under diverse physiological and pathological conditions. The dataset aims to support the development of advanced algorithms and promote clinical validation of BCG as a tool for noninvasive cardiovascular monitoring.
Authors
- Zhengying Li (ORCID: https://orcid.org/0000-0002-4600-2795)
- Zhibing Lu (ORCID: https://orcid.org/0000-0002-7950-3465)
- Kewei Chen (ORCID: https://orcid.org/0000-0002-3351-7714)
- Xiaoyan Wu
- Tao Zhao (ORCID: https://orcid.org/0000-0002-5047-3776)
- Chao Zhang (ORCID: https://orcid.org/0000-0002-8329-8249)
- Jing Zhan
Institutions
- Wuhan University of Technology (CN)
- Wuhan University (CN)
- Zhongnan Hospital of Wuhan University (CN)
- Hubei University (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2025-06-09
- DOI
- https://doi.org/10.1038/s41597-025-05287-z
- Citations
- 2
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- National Natural Science Foundation of China