A Comparative Study of Wavelet Denoising of Surface Electromyographic Signals
- Resource Type
- Conference
- Authors
- Jiang, Ching-Fen; Kuo, Shou-Long
- Source
- 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE. :1868-1871 Aug, 2007
- Subject
- Bioengineering
Noise reduction
Surface waves
Wavelet analysis
Continuous wavelet transforms
Signal analysis
Electromyography
Signal processing
Muscles
Frequency
Wavelet transforms
- Language
- ISSN
- 1094-687X
1558-4615
This study intends to explore the wavelet denoising for optimal MUAP detection through the wavelet analysis of surface electromyographic (SEMG) signals. We first derive an estimator for signal to noise ratio and show that this estimator correlates to the quality of the reconstructed simulated signal. When applying this estimator to evaluate the SEMG signal, we find that the reconstructed signal is insensitive to the selection of denoising methods. This finding is further confirmed by the identical plots of those reconstructed SEMG data. In addition, the close correspondence of MUAP occurrences in the reconstructed signal and those in the original signal suggests that the denoising procedure can preserve the features of MUAP in the original SEMG signals.