A hybrid motion classification approach for EMG-based human - Robot interfaces using bayesian and neural networks

IEEE Transactions on Robotics

Volumn 25, Issue 3, 2009, Pages 502-511

  Bu, Nan ^a   Okamoto, Masaru ^b   Tsuji, Toshio ^c  

^a NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

^b HIROSHIMA CITY UNIVERSITY   (Japan)

^c HIROSHIMA UNIVERSITY   (Japan)

Author keywords

Bayesian network (BN); Electromyogram (EMG) signal; Human robot interfaces; Motion classification; Motion prediction

Indexed keywords

BAYESIAN; CLASSIFICATION PERFORMANCE; CONTEXT INFORMATION; ELECTROMYOGRAM; ELECTROMYOGRAM (EMG) SIGNAL; EMG SIGNAL; HUMAN INTERFACE; HUMAN-ROBOT INTERFACE; HUMAN-ROBOT INTERFACES; MOTION CLASSIFICATION; MOTION PREDICTION; OCCURRENCE PROBABILITY; PROBABILISTIC NEURAL NETWORKS; PROSTHETIC DEVICES; ROBOT MANIPULATION; STABILITY OF MOTIONS; TASK MODELS;

DISTRIBUTED PARAMETER NETWORKS; EXPERIMENTS; INFERENCE ENGINES; INTELLIGENT NETWORKS; MOTION PLANNING; NEURAL NETWORKS; ROBOTS; ROBUSTNESS (CONTROL SYSTEMS); SPEECH ANALYSIS; USER INTERFACES;

BAYESIAN NETWORKS;

EID: 67649300723     PISSN: 15523098     EISSN: None     Source Type: Journal    
DOI: 10.1109/TRO.2009.2019782     Document Type: Article

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