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 :
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