Surface electromyogram denoising using adaptive wavelet thresholding / 生物医学工程学杂志
Journal of Biomedical Engineering
; (6): 723-728, 2014.
Article
in Chinese
| WPRIM (Western Pacific)
| ID: wpr-290685
Responsible library:
WPRO
ABSTRACT
Surface electromyogram (sEMG) may have low signal to noise ratios. An adaptive wavelet thresholding technique was developed in this study to remove noise contamination from sEMG signals. Compared with convention- al wavelet thresholding methods, the adaptive approach can adjust thresholds based on different signal to noise ratios of the processed signal, thus effectively removing noise contamination and reducing distortion of the EMG signal. The advantage of the developed adaptive thresholding method was demonstrated using simulated and experimental sEMG recordings.
Full text:
Available
Database:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Signal Processing, Computer-Assisted
/
Electromyography
/
Wavelet Analysis
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2014
Document type:
Article