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https://doi.org/10.1109/CCA.2007.4389275
Title: | Detection of epileptic spike-wave discharges using SVM | Authors: | Pan, Y. Ge, S.S. Tang, F.R. Al Mamun, A. |
Issue Date: | 2007 | Citation: | Pan, Y.,Ge, S.S.,Tang, F.R.,Al Mamun, A. (2007). Detection of epileptic spike-wave discharges using SVM. Proceedings of the IEEE International Conference on Control Applications : 467-472. ScholarBank@NUS Repository. https://doi.org/10.1109/CCA.2007.4389275 | Abstract: | In this work, support vector machine (SVM) is applied for detecting epileptic spikes and sharp waves in EEG signal. EEG data are obtained from two-channels EEG monitor on Swiss mice. Our technique maps these intracranial electroencephalogram (EEG) time series into corresponding novelty sequences by classifying short-time, energy based statistics computed from one-second windows of data. Numeric simulation studies demonstrate the effect of the SVM detection, and a comparison between SVM and artificial neural network with back-propagation algorithm is presented to show the advantages of SVM algorithm for detecting epileptic spikewave discharge in EEG time series. © 2007 IEEE. | Source Title: | Proceedings of the IEEE International Conference on Control Applications | URI: | http://scholarbank.nus.edu.sg/handle/10635/69889 | ISBN: | 1424404436 | DOI: | 10.1109/CCA.2007.4389275 |
Appears in Collections: | Staff Publications |
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