Online Finger Gesture Recognition Using Surface Electromyography Signals
نویسندگان
چکیده
منابع مشابه
Online Finger Gesture Recognition Using Surface Electromyography Signals
The analysis on the online finger gesture recognition using multi-channel sEMG signals was explored in this paper. Nine types of gestures were applied to be identified, involving six kinds of numerical finger gestures and three kinds of hand gestures. The time domain parameters were extracted to be the features. And then, the probabilistic neural network was utilized to classify the proposed ge...
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Normal hand gesture recognition methods using surface Electromyography (sEMG) signals require designers to use digital signal processing hardware or ensemble methods as tools to solve real time hand gesture classification. These ways are easy to result in complicated computation models, inconvenience of circuit connection and lower online recognition rate. Therefore it is imperative to have goo...
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Normal hand gesture recognition methods using surface Electromyography (sEMG) signals require designers to use digital signal processing hardware or ensemble methods as tools to solve real time hand gesture classification. Some methods could also result in complicated computational models, complex circuit connection and lower online recognition rate. It is therefore imperative to have good meth...
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Although gestures and movement are a natural, everyday occurrence, it remains to be a complex event to interpret by modern day devices. Research has taken a step forward towards solving this problem by discovering alternative methods in an attempt to capture complex gestures. Usually, we interact with our devices by either physical touch or even voice. As these devices become more sophisticated...
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ژورنال
عنوان ژورنال: Journal of Signal and Information Processing
سال: 2013
ISSN: 2159-4465,2159-4481
DOI: 10.4236/jsip.2013.42013