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In recent years Microelectrode recording (MER) analysis has proved to be a powerful localization tool of basal ganglia for Parkinson disease's treatment, especially the Subthalamic Nucleus (STN). In this paper, a signal-dependent method is presented for identification of the STN and other brain zones in Parkinsonian patients. The proposed method, refereed as optimal wavelet feature extraction method...
A Brain Computer Interface is a system that provides an artificial communication between the human brain and the external world. The paradigm based on event related evoked potentials is used in this work. Our main goal was to efficiently solve a binary classification problem: presence or absence of P300 in the registers. Genetic Algorithms and Support Vector Machines were used in a wrapper configuration...
The critical issues in brain-computer interface (BCI) research is how to translate a person's intention into brain signals for controlling computer program or wheelchair. In this paper, we used a new method: relative wavelet energy (RWE) for feature selection in BCIs design and linear discriminant analysis (LDA) and support vector machine (SVM) were utilized to classify the pattern of left and right...
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