ArticleFrontiers in physiology2023
Non-invasive monitoring of cardiac function through Ballistocardiogram: an algorithm integrating short-time Fourier transform and ensemble empirical mode decomposition.
Article in Frontiers in physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Applications of Ballistocardiogram in the Diagnosis of Coronary Heart Disease: Systematic Review.JMIR cardio · 2025Pooled it
- Observational
- Wearable Flexible Sensors for Cardiovascular Disease Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- AI-Enabled Sensor Technologies for Remote Arrhythmic Monitoring in High-Risk Cardiomyopathy Genotypes.Sensors (Basel, Switzerland) · 2026Review
- Study on Multimodal Sensor Fusion for Heart Rate Estimation Using BCG and PPG Signals.Sensors (Basel, Switzerland) · 2026Article
- Detection of Atrial Fibrillation Using Multi-Site Ballistocardiogram with Piezoelectric Rubber Sheet Sensors.Sensors (Basel, Switzerland) · 2025Article
- Comparative analysis of heart rate variability indices from ballistocardiogram and electrocardiogram: a study on measurement agreement.Heart and vessels · 2025Article
- A Multi-Pathology Ballistocardiogram Dataset for Cardiac Function Monitoring and Arrhythmia Assessment.Scientific data · 2025Article
- Clinical Application of Monitoring Vital Signs in Dogs Through Ballistocardiography (BCG).Veterinary sciences · 2025Article
- Enhancing sleep stage classification with ballistocardiogram signals: feature selection using attention mechanism and XGBoost.Frontiers in public health · 2025Article
- A Framework for Selecting and Assessing Wearable Sensors Deployed in Safety Critical Scenarios.Sensors (Basel, Switzerland) · 2024Review
- Nonlinear Heart Rate Variability Analysis for Sleep Stage Classification Using Integration of Ballistocardiogram and Apple Watch.Nature and science of sleep · 2024Article
- Unobstructive Heartbeat Monitoring of Sleeping Infants and Young Children Using Sheet-Type PVDF Sensors.Sensors (Basel, Switzerland) · 2023Article
- Solving variability: Accurately extracting feature components from ballistocardiograms.Digital healthArticle
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Ballistocardiogram (BCG) is a vibration signal that is generated by the displacement of the entire body due to the injection of blood during each heartbeat. It has been extensively utilized to monitor heart rate. The morphological features of the BCG signal serve as effective indicators for the identification of atrial fibrillation and heart failure, holding great significance for BCG signal analysis. The IJK-complex identification allows for the estimation of inter-beat intervals (IBI) and enables a more detailed analysis of BCG amplitude and interval waves. This study presents a novel algorithm for identifying the IJK-complex in BCG signals, which is an improvement over most existing algorithms that only perform IBI estimation. The proposed algorithm employs a short-time Fourier transform and summation across frequencies to initially estimate the occurrence of the J wave using peak finding, followed by Ensemble Empirical Mode Decomposition and a regional search to precisely identify the J wave. The algorithm's ability to detect the morphological features of BCG signals and estimate heart rates was validated through experiments conducted on 10 healthy subjects and 2 patients with coronary heart disease. In comparison to commonly used methods, the presented scheme ensures accurate heart rate estimation and exhibits superior capability in detecting BCG morphological features. This advancement holds significant value for future applications involving BCG signals.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.