Classification of surface EMG signal with fractal dimension / 浙江大学学报(英文版)(B辑:生物医学和生物技术)
Journal of Zhejiang University. Science. B
;
(12): 844-848, 2005.
Artículo
en Inglés
| WPRIM
| ID: wpr-263290
ABSTRACT
Surface EMG (electromyography) signal is a complex nonlinear signal with low signal to noise ratio (SNR). This paper is aimed at identifying different patterns of surface EMG signals according to fractal dimension. Two patterns of surface EMG signals are respectively acquired from the right forearm flexor of 30 healthy volunteers during right forearm supination (FS) or forearm pronation (FP). After the high frequency noise is filtered from surface EMG signal by a low-pass filter, fractal dimension is calculated from the filtered surface EMG signal. The results showed that the fractal dimensions of filtered FS surface EMG signals and those of filtered FP surface EMG signals distribute in two different regions, so the fractal dimensions can represent different patterns of surface EMG signals.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Fisiología
/
Algoritmos
/
Procesamiento de Señales Asistido por Computador
/
Reconocimiento de Normas Patrones Automatizadas
/
Diagnóstico por Computador
/
Fractales
/
Electromiografía
/
Métodos
/
Contracción Muscular
Tipo de estudio:
Estudio diagnóstico
Límite:
Humanos
Idioma:
Inglés
Revista:
Journal of Zhejiang University. Science. B
Año:
2005
Tipo del documento:
Artículo
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