A novel myoelectric pattern recognition strategy for hand function restoration after incomplete cervical spinal cord injury

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Volumn 21, Issue 1, 2013, Pages 96-103

  Liu, Jie ^a   Zhou, Ping ^b,c  

^a REHABILITATION INSTITUTE OF CHICAGO   (United States)

^b UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^c NORTHWESTERN UNIVERSITY   (United States)

Author keywords

Myoelectic control; pattern recognition; spinal cord injury; surface electromyogram (EMG)

Indexed keywords

ASSISTIVE DEVICES; CERVICAL SPINAL CORD; CLASSIFICATION ACCURACY; CLINICAL FEASIBILITY; FEATURE SETS; HAND FUNCTION; HAND FUNCTION RESTORATION; HIGH DENSITY; MOTOR CONTROL; PARALYZED MUSCLES; PATTERN RECOGNITION ALGORITHMS; PATTERN RECOGNITION TECHNIQUES; RECOGNITION STRATEGIES; SPINAL CORD INJURIES (SCI); SPINAL INJURY; SURFACE ELECTROMYOGRAM;

PATIENT REHABILITATION; RESTORATION;

PATTERN RECOGNITION;

ADULT; ARTICLE; AUTOMATED PATTERN RECOGNITION; ELECTROMYOGRAPHY; FEMALE; HAND; HUMAN; MALE; METHODOLOGY; MIDDLE AGED; MOTOR DYSFUNCTION; MUSCLE CONTRACTION; PATHOPHYSIOLOGY; SKELETAL MUSCLE; SPINAL CORD INJURY;

ADULT; ELECTROMYOGRAPHY; FEMALE; HAND; HUMANS; MALE; MIDDLE AGED; MOVEMENT DISORDERS; MUSCLE CONTRACTION; MUSCLE, SKELETAL; PATTERN RECOGNITION, AUTOMATED; SPINAL CORD INJURIES;

MLCS; MLOWN;

EID: 84872143299     PISSN: 15344320     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNSRE.2012.2218832     Document Type: Article

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