Inertial motion capture in conjunction with an artificial neural network can differentiate the gait patterns of hemiparetic stroke patients compared with able-bodied counterparts

Computer Methods in Biomechanics and Biomedical Engineering

Volumn 15, Issue 3, 2012, Pages 285-294

  Scheffer, C ^a   Cloete, T ^a  

^a STELLENBOSCH UNIVERSITY   (South Africa)

Author keywords

Gait analysis; Hemiparetic stroke; Inertial motion capture; Neural network

Indexed keywords

BACK PROPAGATION ARTIFICIAL NEURAL NETWORK (BPANN); CLINICAL TOOLS; CONTROL SUBJECT; GAIT PATTERN; GAIT REHABILITATION; HEMIPARETIC STROKE; INERTIAL MOTIONS; NETWORK ACCURACY; NEUROMUSCULAR DISORDERS; PLANNING AND MONITORING; STROKE PATIENTS; TRAINING AND TESTING;

NEURAL NETWORKS; PATIENT TREATMENT;

GAIT ANALYSIS;

ACCELERATION; ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; FEMALE; HUMAN; MALE; METHODOLOGY; MIDDLE AGED; NEUROLOGIC DISEASE; PARESIS; PATHOPHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STROKE;

ACCELERATION; ADULT; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; GAIT DISORDERS, NEUROLOGIC; HUMANS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); PARESIS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STROKE;

EID: 84860771835     PISSN: 10255842     EISSN: 14768259     Source Type: Journal    
DOI: 10.1080/10255842.2010.527836     Document Type: Article

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