EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking
Correct detection of peaks in electroencephalogram (EEG) signals is of essence due to the significant correlation of those potentials with cognitive performance and disorders. This paper proposes a novel and non-parametric approach to detect prediction error negativity (PEN) in cognitive conflict pr...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/9785809/ |
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| author | Tran Hiep Dinh Avinash Kumar Singh Nguyen Linh Trung Diep N. Nguyen Chin-Teng Lin |
| author_facet | Tran Hiep Dinh Avinash Kumar Singh Nguyen Linh Trung Diep N. Nguyen Chin-Teng Lin |
| author_sort | Tran Hiep Dinh |
| collection | DOAJ |
| description | Correct detection of peaks in electroencephalogram (EEG) signals is of essence due to the significant correlation of those potentials with cognitive performance and disorders. This paper proposes a novel and non-parametric approach to detect prediction error negativity (PEN) in cognitive conflict processing. The PEN candidates are first located from the input signal via an adaptation of a recent effective method for local maxima extraction, processed in a multi-scale manner. The found candidates are then fused and ranked based on their shape and location-based features. False positives caused by candidates’ magnitude are eliminated by rotating the sorted candidate list where the one with the second-best ranking score will be identified as PEN. The EEG data collected from a 3D object selection task have been used to verify the efficacy of the proposed approach. Compared with the state-of-the-art peak detection techniques, the proposed method shows an improvement of at least 2.67% in accuracy and 6.27% in sensitivity while requires only about 4 ms to process an epoch. The accuracy and computational efficiency of the proposed technique in the detection of PEN in cognitive conflict processing would lead to promising applications in performance improvement of brain-computer interfaces (BCIs). |
| format | Article |
| id | doaj-art-3b688517575d4cd3b59beea9b7523c87 |
| institution | OA Journals |
| issn | 1534-4320 1558-0210 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj-art-3b688517575d4cd3b59beea9b7523c872025-08-20T01:52:10ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1534-43201558-02102022-01-01301548155610.1109/TNSRE.2022.31792559785809EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based RankingTran Hiep Dinh0https://orcid.org/0000-0002-2317-0032Avinash Kumar Singh1https://orcid.org/0000-0002-6539-9695Nguyen Linh Trung2https://orcid.org/0000-0002-3103-994XDiep N. Nguyen3https://orcid.org/0000-0003-2659-8648Chin-Teng Lin4https://orcid.org/0000-0001-8371-8197JTIRC, University of Engineering and Technology, Vietnam National University, Cau Giay, Hanoi, VietnamFaculty of Engineering and Information Technology, School of Computer Science, Australian Artificial Intelligence Institute, University of Technology Sydney, Sydney, Ultimo, NSW, AustraliaAdvanced Institute of Engineering and Technology (AVITECH), University of Engineering and Technology, Vietnam National University, Cau Giay, Hanoi, VietnamFaculty of Engineering and Information Technology, School of Electrical and Data Engineering, University of Technology Sydney, Sydney, Ultimo, NSW, AustraliaFaculty of Engineering and Information Technology, School of Computer Science, Australian Artificial Intelligence Institute, University of Technology Sydney, Sydney, Ultimo, NSW, AustraliaCorrect detection of peaks in electroencephalogram (EEG) signals is of essence due to the significant correlation of those potentials with cognitive performance and disorders. This paper proposes a novel and non-parametric approach to detect prediction error negativity (PEN) in cognitive conflict processing. The PEN candidates are first located from the input signal via an adaptation of a recent effective method for local maxima extraction, processed in a multi-scale manner. The found candidates are then fused and ranked based on their shape and location-based features. False positives caused by candidates’ magnitude are eliminated by rotating the sorted candidate list where the one with the second-best ranking score will be identified as PEN. The EEG data collected from a 3D object selection task have been used to verify the efficacy of the proposed approach. Compared with the state-of-the-art peak detection techniques, the proposed method shows an improvement of at least 2.67% in accuracy and 6.27% in sensitivity while requires only about 4 ms to process an epoch. The accuracy and computational efficiency of the proposed technique in the detection of PEN in cognitive conflict processing would lead to promising applications in performance improvement of brain-computer interfaces (BCIs).https://ieeexplore.ieee.org/document/9785809/Summit navigatorpeak detectionspike detectionelectroencephalogram (EEG)cognitive conflictprediction error negativity (PEN) |
| spellingShingle | Tran Hiep Dinh Avinash Kumar Singh Nguyen Linh Trung Diep N. Nguyen Chin-Teng Lin EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking IEEE Transactions on Neural Systems and Rehabilitation Engineering Summit navigator peak detection spike detection electroencephalogram (EEG) cognitive conflict prediction error negativity (PEN) |
| title | EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking |
| title_full | EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking |
| title_fullStr | EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking |
| title_full_unstemmed | EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking |
| title_short | EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking |
| title_sort | eeg peak detection in cognitive conflict processing using summit navigator and clustering based ranking |
| topic | Summit navigator peak detection spike detection electroencephalogram (EEG) cognitive conflict prediction error negativity (PEN) |
| url | https://ieeexplore.ieee.org/document/9785809/ |
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