Classification of neuromuscular disorders using features extracted in the wavelet domain of sEMG sig...
Classification of neuromuscular disorders using features extracted in the wavelet domain of sEMG signals: a case study
About this item
Full title
Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
The present study introduces a method for detecting possible neuropathy or myopathy cases of a subject based on surface electromyograms signals; the same method has been developed as a classification tool for movements of the upper arm. This research is proposed for its capability to classify subjects from a clinical dataset in healthy, myopathic a...
Alternative Titles
Full title
Classification of neuromuscular disorders using features extracted in the wavelet domain of sEMG signals: a case study
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2919554542
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2919554542
Other Identifiers
ISSN
2190-7188
E-ISSN
2190-7196
DOI
10.1007/s12553-016-0153-3
