Prediction of ECG signals from ballistocardiography using deep learning for the unconstrained measurement of heartbeat intervals

Prediction of ECG signals from ballistocardiography using deep learning for the unconstrained measurement of heartbeat intervals

Abstract 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 bidirectional long short-term memory network...

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Bibliographic Details
Main Authors: Seiichi Morokuma, Tadashi Saitoh, Masatomo Kanegae, Naoyuki Motomura, Subaru Ikeda, Kyuichi Niizeki
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Ballistocardiogram
Bidirectional long short-term memory network
Interbeat interval detection
Online Access:https://doi.org/10.1038/s41598-024-84049-0
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https://doi.org/10.1038/s41598-024-84049-0

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