{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T11:36:47Z","timestamp":1780573007457,"version":"3.54.1"},"reference-count":58,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T00:00:00Z","timestamp":1606694400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003621","name":"Ministry of Science, ICT and Future Planning","doi-asserted-by":"publisher","award":["NRF-2018R1A2B6006046"],"award-info":[{"award-number":["NRF-2018R1A2B6006046"]}],"id":[{"id":"10.13039\/501100003621","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2020,11,30]]},"abstract":"<jats:p>One of the serious mental disorders where people interpret reality in an abnormal state is schizophrenia. A combination of extremely disordered thinking, delusion, and hallucination is caused due to schizophrenia, and the daily functions of a person are severely disturbed because of this disorder. A wide range of problems are caused due to schizophrenia such as disturbed thinking and behaviour. In the field of human neuroscience, the analysis of brain activity is quite an important research area. For general cognitive activity analysis, electroencephalography (EEG) signals are widely used as a low-resolution diagnosis tool. The EEG signals are a great boon to understand the abnormality of the brain disorders, especially schizophrenia. In this work, schizophrenia EEG signal classification is performed wherein, initially, features such as Detrend Fluctuation Analysis (DFA), Hurst Exponent, Recurrence Quantification Analysis (RQA), Sample Entropy, Fractal Dimension (FD), Kolmogorov Complexity, Hjorth exponent, Lempel Ziv Complexity (LZC), and Largest Lyapunov Exponent (LLE) are extracted initially. The extracted features are, then, optimized for selecting the best features through four types of optimization algorithms here such as Artificial Flora (AF) optimization, Glowworm Search (GS) optimization, Black Hole (BH) optimization, and Monkey Search (MS) optimization, and finally, it is classified through certain classifiers. The best results show that, for normal cases, a classification accuracy of 87.54% is obtained when BH optimization is utilized with Support Vector Machine-Radial Basis Function (SVM-RBF) kernel, and for schizophrenia cases, a classification accuracy of 92.17% is obtained when BH optimization is utilized with SVM-RBF kernel.<\/jats:p>","DOI":"10.1155\/2020\/8853835","type":"journal-article","created":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T13:09:07Z","timestamp":1606741747000},"page":"1-14","source":"Crossref","is-referenced-by-count":41,"title":["Schizophrenia EEG Signal Classification Based on Swarm Intelligence Computing"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4019-2345","authenticated-orcid":true,"given":"Sunil Kumar","family":"Prabhakar","sequence":"first","affiliation":[{"name":"Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harikumar","family":"Rajaguru","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathyamangalam 638402, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6081-0852","authenticated-orcid":true,"given":"Sun-Hee","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/0165-1781(94)02641-u"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/0165-1781(94)90064-7"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1001\/archpsyc.1982.04290070025006"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/0920-9964(95)00067-4"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1037\/0894-4105.12.2.289"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-015-9430-4"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.23711"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0059331"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.2975848"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2950220"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.2316\/p.2012.764-137"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2008.01.104"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1088\/0967-3334\/30\/8\/005"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2009.03.003"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2004.02.015"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2016.05.007"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1177\/1550059417715388"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.4306\/pi.2008.5.2.115"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1016\/s0925-4927(00)00052-4"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2011.04.011"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.02.009"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2007.11.020"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neulet.2014.12.064"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1186\/s40810-016-0017-0"},{"key":"25","article-title":"A data driven approach for resting-state eeg signal classification of schizophrenia with control participants using random matrix theory","author":"H. Liu","year":"2017"},{"key":"26","first-page":"1","article-title":"Individual recognition in schizophrenia using deep learning methods with random forest and voting classifiers: insights from resting state EEG streams","author":"L. Chu","year":"2017"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.14569\/ijacsa.2019.0101067"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2019.8857946"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1109\/BICTA.2010.5645097"},{"key":"30","first-page":"1","article-title":"Complexity of EEG Signals in Schizophrenia Syndromes","author":"I. E. Kutepov"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.3233\/thc-181497"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.07.145"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0188629"},{"key":"34","doi-asserted-by":"publisher","DOI":"10.1103\/physreve.64.011114"},{"key":"35","doi-asserted-by":"publisher","DOI":"10.3233\/bme-130902"},{"key":"36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-09531-8_9"},{"key":"37","doi-asserted-by":"publisher","DOI":"10.1152\/ajpheart.2000.278.6.h2039"},{"key":"38","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/132625"},{"key":"39","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.88.6.2297"},{"key":"40","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2178-y"},{"key":"41","doi-asserted-by":"publisher","DOI":"10.1142\/s0218127407019652"},{"key":"42","doi-asserted-by":"publisher","DOI":"10.1080\/00207166808803030"},{"issue":"12","key":"43","first-page":"3461","article-title":"Improvement of constraint conditions and new constructional method for intuitionistic fuzzy entropy","volume":"35","author":"F. Zhao","year":"2015","journal-title":"Journal of Computer Applications"},{"key":"44","doi-asserted-by":"publisher","DOI":"10.1016\/s0167-8655(98)00002-6"},{"key":"45","doi-asserted-by":"publisher","DOI":"10.1016\/s0020-0190(02)00343-5"},{"key":"46","doi-asserted-by":"publisher","DOI":"10.1016\/0013-4694(70)90143-4"},{"key":"47","doi-asserted-by":"publisher","DOI":"10.1109\/tit.1977.1055714"},{"key":"48","doi-asserted-by":"publisher","DOI":"10.1109\/iccis.2008.4670889"},{"key":"49","doi-asserted-by":"publisher","DOI":"10.3390\/app8030329"},{"key":"50","doi-asserted-by":"publisher","DOI":"10.1007\/s12213-011-0038-5"},{"key":"51","doi-asserted-by":"publisher","DOI":"10.1007\/s11047-016-9576-z"},{"key":"52","doi-asserted-by":"publisher","DOI":"10.1088\/0964-1726\/21\/10\/105033"},{"key":"53","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.3006197"},{"key":"54","doi-asserted-by":"publisher","DOI":"10.1109\/34.824819"},{"key":"55","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.3006154"},{"key":"56","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics10100763"},{"issue":"1","key":"57","first-page":"63","article-title":"Linear discriminatory analysis on coal and gas outburst danger and its critical value","volume":"29","author":"C. L. Jiang","year":"2000","journal-title":"Journal of China University of Mining & Technology"},{"key":"58","doi-asserted-by":"publisher","DOI":"10.1137\/0602035"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2020\/8853835.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2020\/8853835.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2020\/8853835.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T13:09:12Z","timestamp":1606741752000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cin\/2020\/8853835\/"}},"subtitle":[],"editor":[{"given":"Ant\u00f3nio","family":"Dourado","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2020,11,30]]},"references-count":58,"alternative-id":["8853835","8853835"],"URL":"https:\/\/doi.org\/10.1155\/2020\/8853835","relation":{},"ISSN":["1687-5273","1687-5265"],"issn-type":[{"value":"1687-5273","type":"electronic"},{"value":"1687-5265","type":"print"}],"subject":[],"published":{"date-parts":[[2020,11,30]]}}}