SCS 2003. International Symposium on Signals, Circuits and Systems. Proceedings (Cat. No.03EX720)
DOI: 10.1109/scs.2003.1227084
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Classification of EEG signals represented by AR models for cognitive tasks - a neural network based method

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Cited by 6 publications
(6 citation statements)
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“…A variety of studies such as Keirn and Aunon (1990b), Anderson et al (1995aAnderson et al ( ,b, 1998Anderson et al ( , 2006, Anderson and Sijerčić (1996), Anderson (1997), Palaniappan et al (2000aPalaniappan et al ( ,b,c, 2002, Palaniappan and Raveendran (2001), Bhatti et al (2001), Maiorescu et al (2003), Garrett et al (2003), Liu et al (2003aLiu et al ( ,b, 2005a, Wu and Guo (2003), Xue et al (2003), Barreto et al (2004), Daud and Yunus (2004), , , Rao and Derakhshani (2005), Palaniappan (2005aPalaniappan ( ,b, 2006, Huan and Palaniappan (2005), Palaniappan and Huan (2005), Rezaei et al (2005), Jiang et al (2005), Setban and Dobrea (2005), Gope et al (2005), Yan et al (2006), Abdollahi and Motie-Nasrabadi (2006), Nakayama and Inagaki (2006), , , Nakayama et al (2007), Zhiwei and Minfen (2007), Skinner et al (2007), Abdollahi et al (2007), Hema et al (2007), Hosni et al (2007), and Paulraj et al (2007) have employed this dataset. Most of them classify mental tasks to some extent, but only a few of them report the resultant false positive rate or the confusion matrix (Palaniappan, 2005a;…”
Section: Introductionmentioning
confidence: 99%
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“…A variety of studies such as Keirn and Aunon (1990b), Anderson et al (1995aAnderson et al ( ,b, 1998Anderson et al ( , 2006, Anderson and Sijerčić (1996), Anderson (1997), Palaniappan et al (2000aPalaniappan et al ( ,b,c, 2002, Palaniappan and Raveendran (2001), Bhatti et al (2001), Maiorescu et al (2003), Garrett et al (2003), Liu et al (2003aLiu et al ( ,b, 2005a, Wu and Guo (2003), Xue et al (2003), Barreto et al (2004), Daud and Yunus (2004), , , Rao and Derakhshani (2005), Palaniappan (2005aPalaniappan ( ,b, 2006, Huan and Palaniappan (2005), Palaniappan and Huan (2005), Rezaei et al (2005), Jiang et al (2005), Setban and Dobrea (2005), Gope et al (2005), Yan et al (2006), Abdollahi and Motie-Nasrabadi (2006), Nakayama and Inagaki (2006), , , Nakayama et al (2007), Zhiwei and Minfen (2007), Skinner et al (2007), Abdollahi et al (2007), Hema et al (2007), Hosni et al (2007), and Paulraj et al (2007) have employed this dataset. Most of them classify mental tasks to some extent, but only a few of them report the resultant false positive rate or the confusion matrix (Palaniappan, 2005a;…”
Section: Introductionmentioning
confidence: 99%
“…Most of them classify mental tasks to some extent, but only a few of them report the resultant false positive rate or the confusion matrix (Palaniappan, 2005a;Nakayama and Inagaki, 2006;Anderson et al, 2006;. Some report the classification error (Maiorescu et al, 2003;Rao and Derakhshani, 2005;Nakayama et al, 2007). The remaining studies report the correct classification rates for the different mental tasks.…”
Section: Introductionmentioning
confidence: 99%
“…the C3, C4, P3, P4, 01 and 02 positions on the scalp. During For this test we used the same BEG database that was also these recordings the 4 involved subjects performed (without used by us in two other previous studies [10], [11], and that verbalization, with eyes closed) the following mental tasks:…”
Section: Initializations Given Directly (As Function Arguments Ormentioning
confidence: 99%
“…matrix (representing the data flow between the features In order to classify the tasks -having as final goal the aim extractions and the classification dynamic link library) -were to test the EEG bio-instrumental system and not to obtain the only steps required to dynamically implement the new better performances -, we used the same approach presented structure. As a result, we obtained a different system having in [10]. For each channel 6 AR coefficients were extracted; different characteristics.…”
Section: Initializations Given Directly (As Function Arguments Ormentioning
confidence: 99%
“…The most frequently used features in the BCI systems are: AR coefficients [3], [4], [5], [6], AR models with exogenous inputs [6], power spectral parameters [8], [7], [9], [10], [11], statistic phase synchronization [8], [9], spatial filtering [12], mean value of the phase coherence [8], discharge frequency of a neuronal group [15], P300 wave [12], [13], [14] etc. This paper focuses on the same issue, namely that of finding more appropriate EEG features for cognitive tasks applications.…”
Section: Introductionmentioning
confidence: 99%