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A Mechanomyography (MMG) based hand-motion patterns recognition approach was proposed in this paper. With the MMG signal acquired in the upper arm via a single sensor, eleven original features were extracted, and they were further processed by principal components analysis (PCA) in order to reduce the dimension of the feature space. Quadratic discriminant analysis (QDA) was used for four hand-motion...
In this paper, a method for extracting and classifying movement-related brain signals is proposed. A single-trial MEG observation is first processed with a pre-whitening filter so that strong stationary interference is eliminated. Next, a brain signal effective for classification is extracted using an adaptive spatial filter. The extracted signal is then classified with a support vector machine. From...
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