Paper Info
Title
Subset Selection of Myoelectric Channels - A Genetic Algorithm for Subset Selection of Myoelectric Channels for Patients Following TMR Surgery
Abstract
State of the art self powered prostheses make use of the surface myoelectric signal for motor control. With increasing height of the amputation, control by residual muscles becomes less intuitive and physiologic. Targeted muscle reinnervation (TMR), a surgery technique to increase the number of control sites available in combination with multichannel surface electromyography allows for improved prosthesis control. This paper presents a genetic algorithm that determines a channel subset with high classification accuracy out of a given number of channels recorded from the reinnervated area of a patient.
Year
Venue
Keywords
2009
BIOSIGNALS 2009: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING
Electromyogram,Pattern Recognition,Genetic Algorithm
Field
DocType
Citations 
Prosthesis,Amputation,Pattern recognition,Computer science,Electromyography,Communication channel,Speech recognition,Motor control,Artificial intelligence,Surgery,Genetic algorithm,Reinnervation
Conference
1
PageRank 
References 
Authors
0.35
3
2
Name
Order
Citations
PageRank
Gernot Kvas110.35
Rosemarie Velik2455.87