Title :
A control unit for myoelectrically controlled prosthesis
Author :
Martínez, R. ; Munoz, R. ; Leija, L. ; Hernández, P.R. ; Alvarez, Ja.
Author_Institution :
Dept. de Ingenieria Electric-Bioelectron., CINVESTAV-IPN, Mexico City, Mexico
Abstract :
The long time for getting an acceptable response in myoelectric prosthesis has been a problem. Thanks to DSP processors, the myoelectric signal (MES) processing time has had a drastic reduction. This paper describes a control unit for a myoelectric prosthesis using statistic variables related to contraction force. ANOVA analysis was used to seek the best separable characteristic set. A MES stationarity detector was implemented and a perceptron artificial neural network was used as classifier. A dedicated system was built using a DSP processor and it has a fast response
Keywords :
biocontrol; biomedical equipment; feedback; medical signal processing; multilayer perceptrons; neuromuscular stimulation; prosthetics; signal classification; ANOVA analysis; DSP processor based dedicated system; biofeedback; contraction force; control unit; multilayer perceptron ANN classifier; myoelectrically controlled prosthesis; stationarity detector; statistic variables; Analysis of variance; Artificial neural networks; Detectors; Digital signal processing; Electrodes; Neural prosthesis; Prosthetics; Signal detection; Signal processing; Statistics;
Conference_Titel :
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.802719