JOURNAL ARTICLE

Uterine electromyography signals denoising using discrete wavelet transform

Abstract

This paper introduces the application of the discrete wavelet transform in noise reduction of real uterine Electromyography (EMG) signals. With the appropriate choice of the wavelet function and the selection of the suitable decomposition level, it's possible to remove interference noise effectively. Signal to Noise Ratio (SNR) values are calculated to evaluate the global performance of noise reduction. Results show that wavelet function db4 at three level of decomposition performs denoising best out of the other wavelets. Furthermore, a comparative analysis using the band-pass Butterworth filter demonstrates the superior denoising performance of the proposed algorithm.

Keywords:
Noise reduction Wavelet Wavelet packet decomposition Discrete wavelet transform Pattern recognition (psychology) Second-generation wavelet transform Noise (video) Computer science Stationary wavelet transform Artificial intelligence Wavelet transform Speech recognition Filter (signal processing) Video denoising Mathematics Algorithm Computer vision

Metrics

12
Cited By
0.52
FWCI (Field Weighted Citation Impact)
21
Refs
0.67
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Non-Invasive Vital Sign Monitoring
Physical Sciences →  Engineering →  Biomedical Engineering
Ultrasound Imaging and Elastography
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging
Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
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