Surface Electromyography-Based Action Recognition and Manipulator Control
نویسندگان
چکیده
منابع مشابه
Towards Speaker-adaptive Speech Recognition based on Surface Electromyography
We present our recent advances in silent speech interfaces using electromyographic signals that capture the movements of the human articulatory muscles at the skin surface for recognizing continuously spoken speech. Previous systems were limited to speakerand session-dependent recognition tasks on small amounts of training and test data. In this paper we present speaker-independent and speaker-...
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Problem statement: Facial expression recognition has been improved recently and it has become a significant issue in diagnostic and medical fields, particularly in the areas of assistive technology and rehabilitation. Apart from their usefulness, there are some problems in their applications like peripheral conditions, lightening, contrast and quality of video and images. Approach: Facial Actio...
متن کاملSpeaker-Adaptive Speech Recognition Based on Surface Electromyography
We present our recent advances in silent speech interfaces using electromyographic signals that capture the movements of the human articulatory muscles at the skin surface for recognizing continuously spoken speech. Previous systems were limited to speakerand session-dependent recognition tasks on small amounts of training and test data. In this article we present speakerindependent and speaker...
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We present our research on continuous speech recognition of the surface electromyographic signals that are generated by the human articulatory muscles. Previous research on electromyographic speech recognition was limited to isolated word recognition because it was very difficult to train phoneme-based acoustic models for the electromyographic speech recognizer. In this paper, we demonstrate ho...
متن کاملFacial Expression Recognition using Surface Electromyography
Facial expressions are an essential part of human communication. The integration of information transferred by these expressions into the human-computer interaction can lead to affective systems that are able to adapt their behavior according to reactions shown by the user. In this thesis we propose a system to detect and classify facial expressions based on surface electromyography (sEMG) sign...
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ژورنال
عنوان ژورنال: Applied Sciences
سال: 2020
ISSN: 2076-3417
DOI: 10.3390/app10175823