Quantifying pattern recognition- based myoelectric control of multifunctional transradial prostheses

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Volumn 18, Issue 2, 2010, Pages 185-192

  Li, Guanglin ^a   Schultz, Aimee E ^b   Kuiken, Todd A ^b,c,d  

^a SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY   (China)

^b REHABILITATION INSTITUTE OF CHICAGO   (United States)

^c NORTHWESTERN UNIVERSITY   (United States)

^d Northwestern University   (United States)

Author keywords

Electromyography; Multifunctional prosthesis; Pattern recognition; Real time control; Transradial amputation

Indexed keywords

CLASSIFICATION ACCURACY; HAND MOVEMENT; HAND MUSCLES; MULTIFUNCTIONAL PROSTHESIS; MYOELECTRIC CONTROL; MYOELECTRIC PROSTHESIS; VALUE OF INFORMATION; WRIST MOVEMENTS;

ARTIFICIAL LIMBS; ELECTROMYOGRAPHY; MUSCLE; PATTERN RECOGNITION; REAL TIME CONTROL;

MYOELECTRICALLY CONTROLLED PROSTHETICS;

ADULT; AGED; ALGORITHM; AMPUTATION; ARM; ARTICLE; AUTOMATED PATTERN RECOGNITION; ELECTRODE; FOREARM; HAND; HAND STRENGTH; HUMAN; INNERVATION; LEARNING; LIMB PROSTHESIS; MIDDLE AGED; MOTION; PHYSIOLOGY; PILOT STUDY; PROSTHESIS; RADIUS; SKELETAL MUSCLE; STATISTICS; WRIST;

ADULT; AGED; ALGORITHMS; AMPUTATION; ARM; ARTIFICIAL LIMBS; ELECTRODES, IMPLANTED; FOREARM; HAND; HAND STRENGTH; HUMANS; LEARNING; MIDDLE AGED; MOTION; MUSCLE, SKELETAL; PATTERN RECOGNITION, AUTOMATED; PILOT PROJECTS; PROSTHESIS DESIGN; RADIUS; WRIST;

EID: 77951893489     PISSN: 15344320     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNSRE.2009.2039619     Document Type: Article

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