A learning scheme for reach to grasp movements: On emg-based interfaces using task specific motion decoding models

IEEE Journal of Biomedical and Health Informatics

Volumn 17, Issue 5, 2013, Pages 915-921

  Liarokapis, Minas V ^a   Artemiadis, Panagiotis K ^b   Kyriakopoulos, Kostas J ^a   Manolakos, Elias S ^c  

^a NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^b Arizona State University   (United States)

^c UNIVERSITY OF ATHENS   (Greece)

Author keywords

Electromyography (EMG); learning scheme; random forests; task specificity

Indexed keywords

DECISION TREES; DECODING; ELECTROMYOGRAPHY; RANDOM FORESTS;

CLASSIFICATION DECISION; COMPLEX ENVIRONMENTS; LEARNING SCHEMES; MACHINE LEARNING TECHNIQUES; MULTI-CLASS PROBLEMS; REACH-TO-GRASP MOVEMENTS; TASK SPECIFICITY; TASK-SPECIFIC MODELS;

LEARNING SYSTEMS;

ADULT; ARTIFICIAL INTELLIGENCE; DECISION TREE; DEVICES; ELECTROMYOGRAPHY; FEMALE; HAND STRENGTH; HUMAN; LIMB PROSTHESIS; MALE; PHYSIOLOGY; PROCEDURES; ROBOTICS; SIGNAL PROCESSING; YOUNG ADULT;

ADULT; ARTIFICIAL INTELLIGENCE; ARTIFICIAL LIMBS; DECISION TREES; ELECTROMYOGRAPHY; FEMALE; HAND STRENGTH; HUMANS; MALE; ROBOTICS; SIGNAL PROCESSING, COMPUTER-ASSISTED; YOUNG ADULT;

EID: 84883887265     PISSN: 21682194     EISSN: None     Source Type: Journal    
DOI: 10.1109/JBHI.2013.2259594     Document Type: Article

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