Abstract
This paper addressing various denoising techniques of electrocardiogram signal (ECG) with basic filters both in time and frequency domain. The electrocardiogram (ECG) signal is vital for accurate diagnosing of heart disease. ECG modeling and noise reduction are rather essential for clinical applications also. The major issue is denoising of ECG signal which has been corrupted by equipment or by transmission process. Several methods have been applied for modeling and denoising of ECG signals with low-, high-, band-, notch-pass filters, etc. These methods demonstrated good performance; they can be sensitive to varying parameters. Denoising in frequency domain, the signal is transformed in the discrete wavelet transform domain, where thresholding (soft and hard thresholding)-based noise reduction algorithm is employed. Finally, the calculation of different performance measures enables us to choose an efficient technique. The accuracy and consistency of the proposed method are shown in experimental results.
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Hima Bindu, C. (2019). Performance Analysis of Denoising of ECG Signals in Time and Frequency Domain. In: Computational Intelligence and Big Data Analytics. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-13-0544-3_8
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DOI: https://doi.org/10.1007/978-981-13-0544-3_8
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0543-6
Online ISBN: 978-981-13-0544-3
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