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Several studies defined the EEG with unique features, universality, and natural robustness to be used as a new track to prevent spoofing attacks. The EEG signals are a visual recording of the brain\u2019s electrical activities, measured by placing electrodes (channels) in various scalp positions. However, traditional EEG-based systems lead to high complexity with many channels, and some channels have critical information for the identification system while others do not. Several studies have proposed a single objective to address the EEG channel for person identification. Unfortunately, these studies only focused on increasing the accuracy rate without balancing the accuracy and the total number of selected EEG channels. The novelty of this paper is to propose a multiobjective binary version of the cuckoo search algorithm (MOBCS-KNN) to find optimal EEG channel selections for person identification. The proposed method (MOBCS-KNN) used a weighted sum technique to implement a multiobjective approach. In addition, a KNN classifier for EEG-based biometric person identification is used. It is worth mentioning that this is the initial investigation of using a multiobjective technique with EEG channel selection problem. A standard EEG motor imagery dataset is used to evaluate the performance of the MOBCS-KNN. The experiments show that the MOBCS-KNN obtained accuracy of<jats:inline-formula><a:math xmlns:a=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><a:mn>93.86<\/a:mn><a:mo>%<\/a:mo><\/a:math><\/jats:inline-formula>using only 24 sensors with<jats:inline-formula><c:math xmlns:c=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><c:mtext>AR<\/c:mtext><c:mn>20<\/c:mn><\/c:math><\/jats:inline-formula>autoregressive coefficients. Another critical point is that the MOBCS-KNN finds channels not too close to each other to capture relevant information from all over the head. In conclusion, the MOBCS-KNN algorithm achieves the best results compared with metaheuristic algorithms. Finally, the recommended approach can draw future directions to be applied to different research areas.<\/jats:p>","DOI":"10.1155\/2022\/5974634","type":"journal-article","created":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T23:20:17Z","timestamp":1642029617000},"page":"1-18","source":"Crossref","is-referenced-by-count":20,"title":["EEG Channel Selection Using Multiobjective Cuckoo Search for Person Identification as Protection System in Healthcare Applications"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4228-9298","authenticated-orcid":true,"given":"Zaid","family":"Abdi Alkareem Alyasseri","sequence":"first","affiliation":[{"name":"ITRDC, University of Kufa, P.O. 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Box 4051, Gaza, State of Palestine"},{"name":"Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, UAE"}]},{"given":"Karrar","family":"Hameed Abdulkareem","sequence":"additional","affiliation":[{"name":"College of Agriculture, Al-Muthanna University, Samawah 66001, Iraq"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9030-8102","authenticated-orcid":true,"given":"Mazin","family":"Abed Mohammed","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Technology, University of Anbar, Anbar 31001, Iraq"}]},{"given":"Seifedine","family":"Kadry","sequence":"additional","affiliation":[{"name":"Department of Applied Data Science, Noroff University College, 4608 Kristiansand, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3897-4460","authenticated-orcid":true,"given":"V.","family":"Rajinikanth","sequence":"additional","affiliation":[{"name":"Department of Electronics and Instrumentation Engineering, St. Joseph\u2019s College of Engineering, Chennai 600119, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1936-6785","authenticated-orcid":true,"given":"Seungmin","family":"Rho","sequence":"additional","affiliation":[{"name":"Department of Industrial Security, Chung-Ang University, Seoul, Republic of Korea"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.06.006"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.01.016"},{"key":"3","first-page":"1","article-title":"Identity privacy preserving biometric based authentication scheme for naked healthcare environment","author":"T. 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