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A Framework for Hand Gesture Recognition Based on Accelerometer and EMG Sensors
2011
IEEE transactions on systems, man and cybernetics. Part A. Systems and humans
This paper presents a framework for hand gesture recognition based on the information fusion of a three-axis accelerometer (ACC) and multichannel electromyography (EMG) sensors. In our framework, the start and end points of meaningful gesture segments are detected automatically by the intensity of the EMG signals. A decision tree and multistream hidden Markov models are utilized as decision-level fusion to get the final results. For sign language recognition (SLR), experimental results on the
doi:10.1109/tsmca.2011.2116004
fatcat:75htoj7h5nfe5n2ahktmj4sara