Comparative Analysis of EMG Bio Signal Based on Empirical Wavelet Transform for Medical Diagnosis

M. Karthick, C. Jeyalakshmi and B. Murugeshwari
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M. Karthick: K. Ramakrishnan College of Engineering, Department of ECE
C. Jeyalakshmi: K. Ramakrishnan College of Engineering, Department of ECE
B. Murugeshwari: K. Ramakrishnan College of Engineering, Department of ECE

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1087-1093 from Springer

Abstract: Abstract The high quality and resolution of the time-frequency representation of Bio signals is one of the important area to depict geological structures which are used to reveal the valuable information hidden in them. In this paper, we proposed time-frequency analysis of Bio signal EMG using the empirical wavelet transform (EWT) which is a new approach for analyzing multichannel Bio signals. Comparative results of the EWT, STFT (short time Fourier transform) and CWT (continuous wavelet transform) were analyzed in MATLAB. Overall comparison of the results based on EMT with those obtained from STFT and CWT signals, revealed that PSNR values has been reasonably increased for EWT. In addition, it was observed that presence of EWT-based instantaneous frequency spectra can produce much sparser representation and much higher time frequency resolution than the traditional CWT approach. This emphasizes the feature of empirical wavelet transform.

Keywords: Continuous wavelet transform (CWT); Empirical wavelet transform (EWT); Instantaneous frequency; Sparse representation; Time-frequency analysis (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_110

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DOI: 10.1007/978-3-030-41862-5_110

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