Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Citado por Google
- Similares en SciELO
- Similares en Google
Compartir
Revista Facultad de Ingeniería
versión impresa ISSN 0121-1129
Resumen
GARCIA-PINZON, Jorge Andrés; MENDOZA, Luis Enrique y FLOREZ, Elkin Gregorio. Electronic control arm using electromyographic signals. Rev. Fac. ing. [online]. 2015, vol.24, n.39, pp.71-84. ISSN 0121-1129.
The studies focused in pattern extractions of electromyography signals (SEMG) has been growing, due to their multiple applications. This paper presents an electronic system implementation for the SEMG recording of a subject upper extremity in order to remotely control an electronic arm. Initially, we performed a signals preprocessing, to remove the less important information and to recognize the interest areas. Then the patterns were extracted and classified. The techniques used were: The wavelet analysis (AW), the principal components analysis (PCA), the Fourier transformed (FT), the discrete cosine transformed (DCT), the support vector machines (SVM) and the artificial neural networks (ANR). In this paper we demonstrated, that the methodology stated, allows to realize a process of classification with a superior performance to 95%. There were recorded more than four thousands signals.
Palabras clave : Electronic Arm Control; Electromyography; ANR; SVM; Patterns Extraction; Wavelet Transformed.