A Cross-Modal Autoencoder for Contactless Electrocardiography Monitoring Using Frequency-Modulated Continuous Wave Radar

While traditional electrocardiogram (ECG) monitoring provides vital clinical information, its electrode-based setup restricts patient movement. To address this limitation, contactless ECG monitoring using frequency-modulated continuous-wave (FMCW) radar and deep learning has been developed. However,...

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Veröffentlicht in:	IEEE sensors journal Jg. 24; H. 24; S. 41462 - 41473
Hauptverfasser:	Liu, Kai-Chun, Peng, Sheng-Yu, Tsao, Yu, Liu, Che-Yu, Chen, Zhu-An, Han Han, Zong, Chen, Wen-Chi, Hsieh, Po-Quan, Li, You-Jin, Hsu, Yu-Juei, Hsu, Shun-Neng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 15.12.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Ablation Chirp Continuous wave radar Convolutional neural networks Cross correlation Cross-modal autoencoder Deep learning Effectiveness electrocardiogram (ECG) monitoring Electrocardiography frequency-modulated continuous-wave radar Machine learning Millimeter wave communication Millimeter waves Monitoring neural networks (NNs) Radar Radar detection Sensor phenomena and characterization Sensors Signal quality Spectrograms Vibrations Waveforms
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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