AIMC Topic: Ballistocardiography
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Reconstruction of ECG from ballistocardiogram using generative adversarial networks with attention.
Biomedical physics & engineering express
Mar 12, 2025
Electrocardiogram (ECG) is widely used to provide early warning signals for cardiovascular diseases. However, traditional twelve-lead ECG monitoring methods and smartwatch-based home solutions are unable to achieve daily long-term monitoring. Therefo...
Identification of People in a Household Using Ballistocardiography Signals Through Deep Learning.
Sensors (Basel, Switzerland)
Mar 11, 2025
BACKGROUND: Various sensor technologies have been developed to monitor the health of older adults; however, most of them require attachment to the skin. This study aimed to develop a health monitoring system, using a non-adhesive, non-invasive polyvi...
Prediction of ECG signals from ballistocardiography using deep learning for the unconstrained measurement of heartbeat intervals.
Scientific reports
Jan 6, 2025
We developed a deep learning-based extraction of electrocardiographic (ECG) waves from ballistocardiographic (BCG) signals and explored their use in R-R interval (RRI) estimation. Preprocessed BCG and reference ECG signals were inputted into the bidi...
Ballistocardial Signal-Based Personal Identification Using Deep Learning for the Non-Invasive and Non-Restrictive Monitoring of Vital Signs.
Sensors (Basel, Switzerland)
Apr 15, 2024
Owing to accelerated societal aging, the prevalence of elderly individuals experiencing solitary or sudden death at home has increased. Therefore, herein, we aimed to develop a monitoring system that utilizes piezoelectric sensors for the non-invasiv...
Classification of health deterioration by geometric invariants.
Computer methods and programs in biomedicine
May 26, 2023
BACKGROUND AND OBJECTIVES: Prediction of patient deterioration is essential in medical care, and its automation may reduce the risk of patient death. The precise monitoring of a patient's medical state requires devices placed on the body, which may c...
Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review.
Sensors (Basel, Switzerland)
Dec 6, 2022
Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body's center of mass and on the chest, respectively. Since their inception, their potenti...
ResNet-BiLSTM: A Multiscale Deep Learning Model for Heartbeat Detection Using Ballistocardiogram Signals.
Journal of healthcare engineering
Jan 27, 2022
As the heartbeat detection from ballistocardiogram (BCG) signals using force sensors is interfered by respiratory effort and artifact motion, advanced signal processing algorithms are required to detect the J-peak of each BCG signal so that beat-to-b...
Heart rate estimation from ballistocardiographic signals using deep learning.
Physiological measurement
Jul 28, 2021
Ballistocardiography (BCG) is an unobtrusive approach for cost-effective and patient-friendly health monitoring. In this work, deep learning methods are used for heart rate estimation from BCG signals and are compared against five digital signal proc...
Ballistocardiogram Artifact Reduction in Simultaneous EEG-fMRI Using Deep Learning.
IEEE transactions on bio-medical engineering
Dec 21, 2020
OBJECTIVE: The concurrent recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a technique that has received much attention due to its potential for combined high temporal and spatial resolution. However, the ...
End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism.
Sensors (Basel, Switzerland)
Apr 20, 2020
Blood pressure (BP) is a vital sign that provides fundamental health information regarding patients. Continuous BP monitoring is important for patients with hypertension. Various studies have proposed cuff-less BP monitoring methods using pulse trans...
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