2006 SICE-ICASE International Joint Conference 2006
DOI: 10.1109/sice.2006.315553
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Real-Time Hand Motion Estimation Using EMG Signals with Support Vector Machines

Abstract: Various interfaces using Electromyogram (EMG) signals for controlling a robot hand have been developed. However, there are few researches that apply Support Vector Machines (SVMs) to EMG signal classification for estimating operator's hand motions. There is a possibility that the SVMs are effective classifiers. This paper proposes a real-time hand motion estimation method using the EMG signals with the SVMs. This method consists of two phases for the hand motion estimation. The first phase is the hand motion c… Show more

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Cited by 47 publications
(30 citation statements)
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“…Previous researches have reported number of approaches based on Artificial Neural Networks, Fuzzy Logic, Gaussian Mixture Model and Hidden Murkov Model for EMG signal pattern classification [10,30]. SVM based EMG classification accuracy has outperforms the other methods.…”
Section: Grasp Recognitionmentioning
confidence: 99%
“…Previous researches have reported number of approaches based on Artificial Neural Networks, Fuzzy Logic, Gaussian Mixture Model and Hidden Murkov Model for EMG signal pattern classification [10,30]. SVM based EMG classification accuracy has outperforms the other methods.…”
Section: Grasp Recognitionmentioning
confidence: 99%
“…With surface electrodes placed directly on the skin, it is for instance possible to measure functional motor activities such as washing teeth or writing [5]. Applications for controlling a robot hand with EMG signals have also been developed [6]. Now, it becomes possible to control computers without joysticks or keyboards.…”
Section: Myoelectic Prosthesesmentioning
confidence: 99%
“…Therefore, before control system design, the relation between the bend angle of the wrist and the myoelectricity should be known. There are many relevant works which study humanmachine interface using myoelectricity, for example, [5], [6], [7].…”
Section: Preliminaries: the Relation Between Myoelectricity And mentioning
confidence: 99%