Feasibility of using an artificial neural network model to estimate the elbow flexion force from mechanomyography

Journal of Neuroscience Methods

Volumn 194, Issue 2, 2011, Pages 386-393

  Youn, Wonkeun ^a   Kim, Jung ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

Artificial neural network; Cross subject validation test; Elbow flexion; Force estimation; Mechanomyogram; Multiple linear regression

Indexed keywords

ACCURACY; ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; BICEPS BRACHII MUSCLE; CORRELATION COEFFICIENT; ELBOW FLEXION; FEASIBILITY STUDY; HUMAN; MALE; MUSCLE ISOMETRIC CONTRACTION; MYOGRAPHY; NORMAL HUMAN; PRIORITY JOURNAL; RELIABILITY; SIGNAL NOISE RATIO; SIGNAL TRANSDUCTION; VALIDATION STUDY;

ADULT; ELBOW JOINT; FEASIBILITY STUDIES; HUMANS; LINEAR MODELS; MALE; MUSCLE CONTRACTION; MUSCLE, SKELETAL; MYOGRAPHY; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED; SPECTRUM ANALYSIS; YOUNG ADULT;

EID: 78650509653     PISSN: 01650270     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2010.11.003     Document Type: Article

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