We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Effect of multiscale PCA de-noising on EMG signal classification for diagnosis of neuromuscular disorders.
- Authors
Gokgoz, Ercan; Subasi, Abdulhamit
- Abstract
The article presents a study on the effect of multiscale principal component analysis (MSPCA) denoising method on electromyogram (EMG) signal classification. It discusses the retention of the principal components with highest variance under the MSPCA denoising method for the reconstruction of decomposed signals, the extraction of features using the multiple signal classification (MUSIC) method and finding indicating better performance with MSPCA denoising for neuromuscular disorder diagnosis.
- Subjects
NEUROMUSCULAR disease diagnosis; ALGORITHMS; ELECTROMYOGRAPHY; FACTOR analysis; ARTIFICIAL neural networks; NONPARAMETRIC statistics; SIGNAL processing; QUANTITATIVE research; RECEIVER operating characteristic curves
- Publication
Journal of Medical Systems, 2014, Vol 38, Issue 4, p1
- ISSN
0148-5598
- Publication type
Article
- DOI
10.1007/s10916-014-0031-3