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A preliminary investigation into the analysis of electromyographic activity using a system of multiple neural networks

Caleb, P.; Caleb-Solly, Praminda; Sharpe, P. K.; Jones, R.

Authors

P. Caleb

Praminda Caleb-Solly

P. K. Sharpe

Ruth Jones Ruth.Jones@uwe.ac.uk
Senior Lecturer in Materials & Manufacturing



Contributors

Pedro Barahona
Editor

Mario Stefanelli
Editor

Jeremy Wyatt
Editor

Abstract

Electromyography (EMG) is widely used by clinicians and therapists for diagnosis of certain neuromuscular disorders. This paper describes a preliminary examination of the application of multiple neural networks in the analysis of surface electromyographic activity. The multiple neural network system that is currently being developed enables the signal to be actively monitored by tracking changes in clinical assessment indicators such as force levels, dynamic changes in the force and fatigue. The system has been tested on a small number of subjects and shown promising results.

Citation

Caleb, P., Caleb-Solly, P., Sharpe, P. K., & Jones, R. (1995). A preliminary investigation into the analysis of electromyographic activity using a system of multiple neural networks. Lecture Notes in Artificial Intelligence, 934 LNAI, 439-440. https://doi.org/10.1007/3-540-60025-6_177

Journal Article Type Conference Paper
Publication Date Dec 1, 1995
Journal Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 934 LNAI
Pages 439-440
Series Title Lecture Notes in Computer Science
Series Number 934
ISBN ;
DOI https://doi.org/10.1007/3-540-60025-6_177
Keywords electromyographic activity, multiple neural networks
Public URL https://uwe-repository.worktribe.com/output/1107258
Publisher URL http://dx.doi.org/10.1007/3-540-60025-6_177