Recent Advances in Brain-Computer Interface Systems by Reza Fazel

By Reza Fazel

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In the third block three different Hidden Markov Models are trained, one for each cognitive activity, considering pre-assignation sequences of nine elements. • Finally in the fourth block the validation procedure is performed and the results saved. 4. 44 Fig. 13. Experimental procedure for LDA. Recent Advances in Brain-Computer Interface Systems Applied Advanced Classifiers for Brain Computer Interface Fig. 14. Experimental procedure for ANN classifiers. 45 46 Recent Advances in Brain-Computer Interface Systems Fig.

3. 3 Procedure for RBF-HMM bi-stage classifier The Figure 15 represents the activity diagram for the experimental procedure used with the RBF-HMM classifier. It is composed by four different blocks: • The first block generates the different data sets for learning and testing, considering the three different cognitive tasks. The cross validation procedure is used for the results, ten different repetitions of cross validation are considered, in each repetition a different data set session is reserved for the validation, employing the rest data sets for learning and testing.

Test of system devices. It checks the correct level of battery, and state of the electrodes. • System assembly. tec), acquisition signal card (PCI-MIO-16/E-4 by National Instrument), computer. 28 Recent Advances in Brain-Computer Interface Systems Fig. 2. Diagram of the experiment realization. • System test. Verifies the correct operation of the whole system. To minimise noise from the electrical network the Notch filter (50Hz) of the bio-amplifier is switched on. • Subject preparation for the experiment.

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