@inproceedings{
 title = {P-300 rhythm detection using anfis algorithm and wavelet feature extraction in eeg signals},
 type = {inproceedings},
 year = {2010},
 volume = {1},
 websites = {http://www.iaeng.org/publication/WCECS2010/WCECS2010_pp619-623.pdf},
 publisher = {Proceedings of the 2010 Word Congress on Engineering and Computer Science(WCECS 2010)},
 id = {8a43f79a-c4d1-39b5-aed5-1564aca48c51},
 created = {2022-08-29T17:43:14.447Z},
 file_attached = {false},
 profile_id = {940dd160-7d67-3a5f-b9f8-935da0571367},
 group_id = {92fccab2-8d44-33bc-b301-7b94bb18523c},
 last_modified = {2022-08-29T17:43:14.447Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 source_type = {CONF},
 private_publication = {false},
 abstract = {P300 evoked potential is an electroencephalographic (EEG) signal obtained at the central-parietal region of the brain in response to rare or unexpectedevents. In this work, an experiment on the detection of a P-300 rhythmfor potential applications on brain computer interfaces (BCI)using an Adaptive Neuro Fuzzy algorithm (ANFIS) is presented. The P300 evoked potential is obtained from visual stimuli followed by a motor response from the subject. The EEG signals are obtained with a 14 electrodes Emotiv EPOC headset. Preprocessing of the signals includes denoising and blind source separation using an Independent Component Analysis algorithm. The P300 rhythm is detected usingthe discrete wavelet transform (DWT)applied on the preprocessed signal as afeature extractor, and further enteredto the ANFIS system. Experimental results are presented.},
 bibtype = {inproceedings},
 author = {Ramirez-Cortes, Juan Manuel and Alarcon-Aquino, Vicente and Rosas-Cholula, Gerardo and Gomez-Gil, Pilar and Escamilla-Ambrosio, Jorge},
 booktitle = {Proceedings of the 2010 Word Congress on Engineering and Computer Science(WCECS 2010)}
}

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