DocumentCode
642703
Title
Analysis of myoelectric signals using a Field Programmable SoC
Author
Borbely, Bence J. ; Kineses, Zoltan ; Vorohazi, Zsolt ; Nagy, Zsolt ; Szolgay, Peter
Author_Institution
Fac. of Inf. Technol., Pazmany Peter Catholic Univ., Budapest, Hungary
fYear
2013
fDate
8-12 Sept. 2013
Firstpage
1
Lastpage
4
Abstract
A platform design for the analysis of human myoelectric signals (MES) is presented. Offline recorded multichannel signals of forearm muscles are processed with a Field Programmable SoC in order to classify different movement patterns to control human-assisting electromechanical systems with multiple degrees of freedom (e.g. a prosthetic hand). Benchmark results of an ANSI C implementation are shown to assess the raw performance of the built-in ARM cores of the SoC. Possible computational bottlenecks are located based on the results and custom hardware implementations are shown to fully utilize the flexibility and performance of the used hardware platform.
Keywords
electromyography; field programmable gate arrays; microprocessor chips; pattern recognition; system-on-chip; ANSI C implementation; ARM cores; field programmable SoC; forearm muscles; human myoelectric signals; offline recorded multichannel signals; Field programmable gate arrays; Process control; System-on-chip; Time-domain analysis; Training; Vector processors; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuit Theory and Design (ECCTD), 2013 European Conference on
Conference_Location
Dresden
Type
conf
DOI
10.1109/ECCTD.2013.6662255
Filename
6662255
Link To Document