Research on EEG Recognition Algorithm Based on SVM Classifier

Zhang Chao, Zhao Xilu, Pan Su, Yang Yudan
<span title="2016-12-31">2016</span> <i title="Science and Engineering Research Support Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ym6wyoim55h6lliru6w4ssplki" style="color: black;">International Journal of Signal Processing, Image Processing and Pattern Recognition</a> </i> &nbsp;
As more and more insight into the human brain, EEG is not only for application, processing and analysis of EEG in science and engineering field, it will also be very important in the physical, psychological and pathological studies in humans. The EEG brain -machine interface technologies to achieve the human brain and the computer or other human interface devices to communicate and control, it can provide a special kind of information exchange and live entertainment, is also disabled and a new
more &raquo; ... ay of control. In this paper, the collection of information preprocessing electroencephalogram (EEG) signals is proposed wavelet packet transform feature extraction method, using SVM classifier, classification based on the operation mode to achieve recognition of the EEG signal. For different individuals turn, the next turn, show fist, fist four kinds of hand motion recognition experiments show that the average recognition rate of over 80%, significantly better than the other methods to identify results.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijsip.2016.9.12.19">doi:10.14257/ijsip.2016.9.12.19</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7a6nz5iwl5d5hensqbf2mfp42i">fatcat:7a6nz5iwl5d5hensqbf2mfp42i</a> </span>
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