A novel prosthetic hand control approach based on genetic algorithm and wavelet transform features

Proceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011

Volumn , Issue , 2011, Pages 287-292

  Karimi, Mohammad ^a   Pourghassem, Hossein ^a   Shahgholian, Ghazanfar ^a  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

Electromyographic (EMG) signal; Feature extraction; genetic algorithm; neural network; Pattern recognition; wavelet packet transform

Indexed keywords

ARTIFICIAL NEURAL NETWORKS; BEST VALUE; DECOMPOSITION LEVEL; ELECTROMYOGRAPHIC SIGNAL; EMG SIGNAL; FEATURE VECTORS; HAND MOTION; HIDDEN LAYERS; HIGH-SPEED; MOTHER WAVELETS; PRACTICAL IMPLEMENTATION; PROSTHETIC HANDS; RECOGNITION ACCURACY; SMALL SIZE; STANDARD DEVIATION; TRAINING PURPOSE; TWO LAYERS; WAVELET PACKET ANALYSIS; WAVELET PACKET COEFFICIENT; WAVELET PACKET TRANSFORM;

FACE RECOGNITION; FEATURE EXTRACTION; NEURAL NETWORKS; OPTIMIZATION; PACKET NETWORKS; PATTERN RECOGNITION SYSTEMS; SIGNAL PROCESSING; WAVELET DECOMPOSITION;

GENETIC ALGORITHMS;

EID: 79957469903     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSPA.2011.5759889     Document Type: Conference Paper

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