Surface electromyography signal classification using gray system theory / 生物医学工程学杂志
J. biomed. eng
; Sheng wu yi xue gong cheng xue za zhi;(6): 901-904, 2004.
Article
en Zh
| WPRIM
| ID: wpr-342584
Biblioteca responsable:
WPRO
ABSTRACT
A new method based on gray correlation was introduced to improve the identification rate in artificial limb. The electromyography (EMG) signal was first transformed into time-frequency domain by wavelet transform. Singular value decomposition (SVD) was then used to extract feature vector from the wavelet coefficient for pattern recognition. The decision was made according to the maximum gray correlation coefficient. Compared with neural network recognition, this robust method has an almost equivalent recognition rate but much lower computation costs and less training samples.
Texto completo:
1
Base de datos:
WPRIM
Asunto principal:
Fisiología
/
Teoría de Sistemas
/
Procesamiento de Señales Asistido por Computador
/
Redes Neurales de la Computación
/
Músculo Esquelético
/
Electromiografía
/
Modelos Biológicos
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
Zh
Revista:
J. biomed. eng
/
Sheng wu yi xue gong cheng xue za zhi
Año:
2004
Tipo del documento:
Article