{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T04:25:58Z","timestamp":1777955158149,"version":"3.51.4"},"reference-count":28,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,8]],"date-time":"2022-03-08T00:00:00Z","timestamp":1646697600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The electroencephalogram (EEG) introduced a massive potential for user identification. Several studies have shown that EEG provides unique features in addition to typical strength for spoofing attacks. EEG provides a graphic recording of the brain\u2019s electrical activity that electrodes can capture on the scalp at different places. However, selecting which electrodes should be used is a challenging task. Such a subject is formulated as an electrode selection task that is tackled by optimization methods. In this work, a new approach to select the most representative electrodes is introduced. The proposed algorithm is a hybrid version of the Flower Pollination Algorithm and \u03b2-Hill Climbing optimizer called FPA\u03b2-hc. The performance of the FPA\u03b2-hc algorithm is evaluated using a standard EEG motor imagery dataset. The experimental results show that the FPA\u03b2-hc can utilize less than half of the electrode numbers, achieving more accurate results than seven other methods.<\/jats:p>","DOI":"10.3390\/s22062092","type":"journal-article","created":{"date-parts":[[2022,3,9]],"date-time":"2022-03-09T01:50:53Z","timestamp":1646790653000},"page":"2092","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["EEG Channel Selection Based User Identification via Improved Flower Pollination Algorithm"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4228-9298","authenticated-orcid":false,"given":"Zaid Abdi Alkareem","family":"Alyasseri","sequence":"first","affiliation":[{"name":"ECE Department, Faculty of Engineering, University of Kufa, Najaf 54001, Iraq"},{"name":"Information Technology Research and Development Center (ITRDC), University of Kufa, Najaf 54001, Iraq"}]},{"given":"Osama Ahmad","family":"Alomari","sequence":"additional","affiliation":[{"name":"MLALP Research Group, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6494-7514","authenticated-orcid":false,"given":"Jo\u00e3o P.","family":"Papa","sequence":"additional","affiliation":[{"name":"Department of Computing, UNESP\u2014S\u00e3o Paulo State University, Bauru 19060-560, Brazil"}]},{"given":"Mohammed Azmi","family":"Al-Betar","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman P.O. Box 20550, United Arab Emirates"},{"name":"Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, Al-Huson, Irbid 21110, Jordan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7302-2049","authenticated-orcid":false,"given":"Karrar Hameed","family":"Abdulkareem","sequence":"additional","affiliation":[{"name":"College of Agriculture, Al-Muthanna University, Samawah 66001, Iraq"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9030-8102","authenticated-orcid":false,"given":"Mazin Abed","family":"Mohammed","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Technology, University of Anbar, Ramadi 31001, Iraq"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1939-4842","authenticated-orcid":false,"given":"Seifedine","family":"Kadry","sequence":"additional","affiliation":[{"name":"Department of Applied Data Science, Norrof University College, 4608 Kristiansand, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1664-0059","authenticated-orcid":false,"given":"Orawit","family":"Thinnukool","sequence":"additional","affiliation":[{"name":"College of Arts, Media, and Technology, Chiang Mai University, Chiang Mai 50200, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4993-949X","authenticated-orcid":false,"given":"Pattaraporn","family":"Khuwuthyakorn","sequence":"additional","affiliation":[{"name":"College of Arts, Media, and Technology, Chiang Mai University, Chiang Mai 50200, Thailand"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.eswa.2016.06.006","article-title":"EEG-based person identification through binary flower pollination algorithm","volume":"62","author":"Rodrigues","year":"2016","journal-title":"Expert Syst. 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