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Comparison of performance of different feature extraction methods in detection of P300

Amini Z., Abootalebi V., Sadeghi M. T.

Biocybernetics and Biomedical Engineering

2013

Vol. 33, no. 1

3--20

The aim of this paper is to design a pattern recognition based system to detect the P300 component in the EEG trials. This system has two main blocks, feature extraction and classification. In the feature extraction block, in addition to morphological features, some new features including intelligent segmentation, common spatial pattern (CSP) and combined features (CSP + Segmentation) have also been used. Two criteria were used for the feature evaluation. Firstly, a t-test has been applied. Secondly, each of these four groups of features was evaluated by a Linear Discriminant Analysis (LDA) classifier. Afterwards, the best set of features was selected by using Stepwise Linear Discriminant Analysis (SWLDA). In the classification phase, the LDA was used as a linear classifier. The algorithm described here was tested with dataset II from the BCI competition 2005. In this research, the best result for the P300 detection was 97.4% .This result has proven to be more accurate than the results of previous works carried out in this filed.

Wykorzystanie potencjałów mózgowych P300 do sterowania awatarem

Majkowski A., Kołodziej M., Rak R. J.

Pomiary Automatyka Kontrola

2012

R. 58, nr 4

352-354

W artykule przedstawiono system BCI umożliwiający sterowanie awatarem w wirtualnym świecie gry Second Life z wykorzystaniem potencjału mózgowego P300. Do budowy systemu autorzy wykorzystali ogólnodostępne oprogramowanie BCI2000 oraz własne oprogramowanie umożliwiające sterowanie zewnętrzną aplikacją poprzez symulację naciśnięć przycisków klawiatury. Użytkownik w komfortowy sposób może sterować kierunkiem ruchu awatara. System jest uniwersalny i po drobnych modyfikacjach pozwala na sterowanie dowolnym urządzeniem. Docelowo autorzy chcą wykorzystać autorskie oprogramowanie do sterowania kierunkiem ruchu wózka inwalidzkiego.

In the paper there is presented a BCI system which enables control of avatar movement in the virtual world of the Second Life game. The system consists of two PCs connected via LAN. On the first computer the BCI200 system was launched with a modified Dochin board (Fig. 5). The interface enables choosing the direction of avatar movement (forward, backward, right, left). Next, the BCI2000 system sends the information about the avatar movement direction via UDP / IP protocol to the second computer. On that computer a program created by the authors is running. Its task is to receive information about the movement direction, and then to send the appropriate commands, in the form of simulated keystrokes, to the game. The program was written in C # (Visual Studio 2005). An important advantage of the proposed interface is that a user does not have to learn the proper generation of the EEG signal. With only one calibration session it was possible to collect features of P300 potential for a user and correctly train the classifier. The system is universal and after minor modifications can control any device. Ultimately, the authors want to use the software to control the direction of wheelchair movement.