Classification of EEG-P300 signals using phase locking value and pattern recognition classifiers

Rupesh Kumar Chikara, Li-Wei Ko*

*Corresponding author for this work

研究成果: Conference contribution同行評審

3 引文 斯高帕斯(Scopus)

摘要

In this paper, we present a classification method based on electroencephalogram (EEG) signal during left hand and right hand response inhibition (stop success vs stop fail) from different participants. The system uses phase locking value (PLV) for the features extraction and pattern recognition algorithm for classification. There are four classifiers: QDC, KNNC, PARZENDC and LDC used in this paper to estimate the accuracy of our system. Based on the collected time-domain EEG signals, the phase locking value (PLV) from C3-CZ and C4-CZ electrodes are calculated and then used as the feature and input for the classifiers algorithm. The classification system demonstrate an accuracy of 92 % in LDC. The results of this study suggest the method could be utilized effectively for response inhibition identification.

原文English
主出版物標題TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence
發行者Institute of Electrical and Electronics Engineers Inc.
頁面367-372
頁數6
ISBN(電子)9781467396066
DOIs
出版狀態Published - 12 二月 2016
事件Conference on Technologies and Applications of Artificial Intelligence, TAAI 2015 - Tainan, Taiwan
持續時間: 20 十一月 201522 十一月 2015

出版系列

名字TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence

Conference

ConferenceConference on Technologies and Applications of Artificial Intelligence, TAAI 2015
國家Taiwan
城市Tainan
期間20/11/1522/11/15

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