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Therefore, this paper proposes robust TQWT for automatically selecting optimum tuning parameters to decompose non-stationary EEG signals accurately. Three evolutionary optimization algorithms are explored for automating the tuning parameters of robust TQWT. The fitness function of the mean square error of decomposition is used. This paper also exploits channel selection using a Laplacian score for dominant channel selection. Important features elicited from sub-bands of robust TQWT are classified using different kernels of the least square support vector machine classifier. The radial basis function kernel has provided the highest accuracy of 99.78%, proving that the proposed method is superior to other state-of-the-art using the same database.<\/jats:p>","DOI":"10.3390\/s22218128","type":"journal-article","created":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T10:09:23Z","timestamp":1666606163000},"page":"8128","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["An Intelligent Motor Imagery Detection System Using Electroencephalography with Adaptive Wavelets"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8365-1092","authenticated-orcid":false,"given":"Smith K.","family":"Khare","sequence":"first","affiliation":[{"name":"Department of Electrical & Computer Engineering, Aarhus University, 8000 Aarhus, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6119-2099","authenticated-orcid":false,"given":"Nikhil","family":"Gaikwad","sequence":"additional","affiliation":[{"name":"Department of Electrical & Computer Engineering, Aarhus University, 8000 Aarhus, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3493-9302","authenticated-orcid":false,"given":"Neeraj Dhanraj","family":"Bokde","sequence":"additional","affiliation":[{"name":"Center for Quantitative Genetics and Genomics, Aarhus University, 8000 Aarhus, Denmark"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/S1388-2457(02)00387-5","article-title":"Clinical application of an EEG-based brain\u2013computer interface: A case study in a patient with severe motor impairment","volume":"114","author":"Neuper","year":"2003","journal-title":"Clin. 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