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In this study, we perform an analysis of electroencephalography complexity measures by quantifying features efficiency in differentiating patients in different consciousness levels. Several measures of complexity have been proposed to quantify the complexity of signals. Our aim is to lay the foundation of a system that will objectively define the level of consciousness by performing a complexity analysis of Electroencephalogram (EEG) signals. Therefore, a nonlinear analysis of EEG signals obtained with a recording scheme proposed by us from 39 patients with Glasgow Coma Scale (GCS) between 3 and 8 was performed. Various entropy values (approximate entropy, permutation entropy, etc.) obtained from different algorithms, Hjorth parameters, Lempel\u2013Ziv complexity and Kolmogorov complexity values were extracted from the signals as features. The features were analyzed statistically and the success of features in classifying different levels of consciousness was measured by various classifiers. Consequently, levels of consciousness in deep coma (GCS between 3 and 8) were classified with an accuracy of 90.3%. To the authors\u2019 best knowledge, this is the first demonstration of the discriminative nonlinear features extracted from tactile and auditory stimuli EEG signals in distinguishing different GCSs of comatose patients. <\/jats:p>","DOI":"10.1142\/s0129065722500186","type":"journal-article","created":{"date-parts":[[2022,3,18]],"date-time":"2022-03-18T05:52:55Z","timestamp":1647582775000},"source":"Crossref","is-referenced-by-count":15,"title":["Classification of Depth of Coma Using Complexity Measures and Nonlinear Features of Electroencephalogram Signals"],"prefix":"10.1142","volume":"32","author":[{"given":"\u00c7i\u011fdem G\u00fcl\u00fczar","family":"Alt\u0131ntop","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Erciyes University, Turkey"}]},{"given":"Fatma","family":"Latifo\u011flu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Erciyes University, Turkey"}]},{"given":"Aynur Karayol","family":"Ak\u0131n","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Reanimation, Erciyes University, Turkey"}]},{"given":"Adnan","family":"Bayram","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Reanimation, Erciyes University, Turkey"}]},{"given":"Murat","family":"\u00c7ift\u00e7i","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Erciyes University, Turkey"}]}],"member":"219","published-online":{"date-parts":[[2022,3,17]]},"reference":[{"key":"S0129065722500186BIB001","first-page":"961","volume-title":"UKACC Int. 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