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However, individual differences in the frequency ranges of brain activity during motor imagery tasks pose a challenge, limiting the manual feature extraction for motor imagery classification. To extract features that match specific subjects, we proposed a novel motor imagery classification model using distinctive feature fusion with adaptive structural LASSO. Specifically, we extracted spatial domain features from overlapping and multi-scale sub-bands of EEG signals and mined discriminative features by fusing the task relevance of features with spatial information into the adaptive LASSO-based feature selection. We evaluated the proposed model on public motor imagery EEG datasets, demonstrating that the model has excellent performance. Meanwhile, ablation studies and feature selection visualization of the proposed model further verified the great potential of EEG analysis.<\/jats:p>","DOI":"10.3390\/s24123755","type":"journal-article","created":{"date-parts":[[2024,6,10]],"date-time":"2024-06-10T08:59:06Z","timestamp":1718009946000},"page":"3755","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Motor Imagery EEG Signal Classification Using Distinctive Feature Fusion with Adaptive Structural LASSO"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2163-4574","authenticated-orcid":false,"given":"Weihai","family":"Huang","sequence":"first","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou 350100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyue","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Future Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weize","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou 350100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihua","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou 350100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiyan","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangzeng","family":"Kong","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou 350100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"108918","DOI":"10.1016\/j.jneumeth.2020.108918","article-title":"A comprehensive assessment of Brain Computer Interfaces: Recent trends and challenges","volume":"346","author":"Yadav","year":"2020","journal-title":"J. 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