Using recurrent artificial neural network model to estimate voluntary elbow torque in dynamic situations

Medical and Biological Engineering and Computing

Volumn 43, Issue 4, 2005, Pages 473-480

  Song, R ^a   Tong, K Y ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Inverse dynamic model; Musculoskeletal modelling; Recurrent artificial neural network; Voluntary movement

Indexed keywords

ALGORITHMS; BIOMECHANICS; DIFFERENTIAL EQUATIONS; ELECTROMYOGRAPHY; KINEMATICS; MATHEMATICAL MODELS; MUSCLE; MUSCULOSKELETAL SYSTEM; TORQUE;

ELBOW; INVERSE DYNAMIC MODEL; MUSCULOSKELETAL MODELLING; ROOT MEAN SQUARED ERROR; VOLUNTARY MOVEMENT;

RECURRENT NEURAL NETWORKS;

ACCURACY; ARM MOVEMENT; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; ELBOW FLEXION; ELECTROMYOGRAPHY; HAND; HUMAN; KINEMATICS; MATHEMATICAL MODEL; MOTION; MOVEMENT (PHYSIOLOGY); NORMAL HUMAN; SIGNAL PROCESSING; TORQUE; VOLUNTARY MOVEMENT; WEIGHT BEARING;

ADULT; BIOMECHANICS; ELBOW JOINT; ELECTROMYOGRAPHY; HUMANS; MALE; MODELS, BIOLOGICAL; MUSCLE, SKELETAL; NEURAL NETWORKS (COMPUTER); SIGNAL PROCESSING, COMPUTER-ASSISTED; TORQUE;

EID: 27744438666     PISSN: 01400118     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF02344728     Document Type: Article

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