SEMG-based hand motion recognition using cumulative residual entropy and extreme learning machine

Medical and Biological Engineering and Computing

Volumn 51, Issue 4, 2013, Pages 417-427

  Shi, Jun ^a   Cai, Yin ^a   Zhu, Jie ^a   Zhong, Jin ^a   Wang, Fei ^b  

^a SHANGHAI UNIVERSITY   (China)

^b IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

Classification; Cumulative residual entropy; Extreme learning machine; Surface electromyography (SEMG)

Indexed keywords

CLASSIFICATION ACCURACY; CUMULATIVE RESIDUAL ENTROPIES; EXTREME LEARNING MACHINE; LINEAR DISCRIMINANT ANALYSIS; MEASURE OF UNCERTAINTY; MULTIFUNCTIONAL PROSTHESIS; SINGLE-HIDDEN LAYER FEEDFORWARD NEURAL NETWORKS; SURFACE ELECTROMYOGRAPHY;

CLASSIFICATION (OF INFORMATION); IMAGE RETRIEVAL; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; REAL TIME CONTROL;

ENTROPY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFIER; DISCRIMINANT ANALYSIS; ELECTRODE; ELECTROMYOGRAPHY; ENTROPY; FUZZY SYSTEM; HAND MOVEMENT; HAND PROSTHESIS; HUMAN; HUMAN EXPERIMENT; INTERMETHOD COMPARISON; MACHINE LEARNING; MEASUREMENT ACCURACY; MYOELECTRIC CONTROL; NORMAL HUMAN; PATTERN RECOGNITION; SUPPORT VECTOR MACHINE; AUTOMATED PATTERN RECOGNITION; HAND; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY; PROCEDURES; SIGNAL PROCESSING; METHODOLOGY;

ELECTROMYOGRAPHY; ENTROPY; HAND; HUMANS; MOVEMENT; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUPPORT VECTOR MACHINES;

EID: 84885628994     PISSN: 01400118     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11517-012-1010-9     Document Type: Article

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