1. Comparison on denoising of electro cardiogram signal using deep learning techniques.
- Author
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Manimegalai, P., Pamela, D., Michael, Prawin Angel, Nigel, K. Gerard Joe, Stanley, P. Kingston, and Jenny, Judith Rachel
- Subjects
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DEEP learning , *SIGNAL denoising , *MYOCARDIAL infarction , *CORONARY artery disease , *ARRHYTHMIA - Abstract
Heartbeat is visualized as a series of electrical waves on the display. ECG signal conveys information about structure and functions of heart. To check the heart's electrical activity and rhythm a test called Electrocardiogram (ECG) is used An ECG helps to analyze symptoms of heart problems such as chest pain, Arrhythmias, shortness of breath, Coronary Artery Diseases, Heart Attacks etc. Artifacts and noises may get added to the signals and leads to a wrong diagnosis. Therefore, it is necessary to remove these noises to get proper diagnosis. ECG signals are low frequency signals in the range of 0.5Hz-100Hz. This paper discusses various ECG denoising techniques and also compares existing signal processing Algorithms for Denoising of ECG Signal Using Deep Learning. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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