The classification results reveal that 97.7% of the inspected ASL gestures were correctly recognized using sEMG-based features, providing a promising solution ...
Abstract—In this work, analysis of the surface electromyogram (sEMG) signal is proposed for the recognition of American Sign Language (ASL) gestures.
The classification results reveal that 97.7% of the inspected ASL gestures were correctly recognized using sEMG-based features, providing a promising solution ...
Analysis of the surface electromyogram (sEMG) signal is proposed for the recognition of American sign language (ASL) gestures, providing a promising ...
The classification results reveal that 97.7% of the inspected ASL gestures were correctly recognized using sEMG-based features, providing a promising solution ...
In this work, analysis of the surface electromyogram (sEMG) signal is proposed for the recognition of American sign language (ASL) gestures.
In this study, an American Sign Language (ASL) recognition system was proposed by using the surface Electromyography (sEMG).
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Evaluation of surface EMG features for the recognition of American Sign Language gestures. scientific article published in January 2006. In more languages.
A comprehensive study on the methods, approaches, and projects utilizing EMG sensors for sign language handshape recognition.
Results of this study show that sEMG signal can be used for SLR systems and recognize the American Sign Language alphabet letters and allow users to spell ...