Classification of EMG signals using combined features and soft computing techniques

Applied Soft Computing Journal

Volumn 12, Issue 8, 2012, Pages 2188-2198

  Subasi, Abdulhamit ^a  

^a INTERNATIONAL BURCH UNIVERSITY   (Bosnia and Herzegovina)

Author keywords

Adaptive neuro fuzzy inference system (ANFIS); Discrete Wavelet Transform (DWT); Dynamic Fuzzy Neural Network (DFNN); Electromyography (EMG); Motor unit action potentials (MUPs)

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; COMBINED FEATURES; COMPARATIVE ANALYSIS; DYNAMIC FUZZY NEURAL NETWORKS(D-FNN); ELECTROMYOGRAPHIC SIGNAL; EMG SIGNAL; FEATURE EXTRACTION METHODS; FREQUENCY DOMAINS; MOTOR UNIT ACTION POTENTIALS; MULTILAYER PERCEPTRON NEURAL NETWORKS; NEUROMUSCULAR DISORDERS; RECOGNITION RATES; SOFTCOMPUTING TECHNIQUES; TIME DOMAIN;

DISCRETE WAVELET TRANSFORMS; ELECTROMYOGRAPHY; ELECTROPHYSIOLOGY; FEATURE EXTRACTION; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; RELIABILITY ANALYSIS; SOFT COMPUTING;

TIME DOMAIN ANALYSIS;

EID: 84861850248     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2012.03.035     Document Type: Article

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