{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T16:46:27Z","timestamp":1791391587829,"version":"4.3.3"},"reference-count":66,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T00:00:00Z","timestamp":1730246400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The perception and recognition of objects around us empower environmental interaction. Harnessing the brain\u2019s signals to achieve this objective has consistently posed difficulties. Researchers are exploring whether the poor accuracy in this field is a result of the design of the temporal stimulation (block versus rapid event) or the inherent complexity of electroencephalogram (EEG) signals. Decoding perceptive signal responses in subjects has become increasingly complex due to high noise levels and the complex nature of brain activities. EEG signals have high temporal resolution and are non-stationary signals, i.e., their mean and variance vary overtime. This study aims to develop a deep learning model for the decoding of subjects\u2019 responses to rapid-event visual stimuli and highlights the major factors that contribute to low accuracy in the EEG visual classification task.The proposed multi-class, multi-channel model integrates feature fusion to handle complex, non-stationary signals. This model is applied to the largest publicly available EEG dataset for visual classification consisting of 40 object classes, with 1000 images in each class. Contemporary state-of-the-art studies in this area investigating a large number of object classes have achieved a maximum accuracy of 17.6%. In contrast, our approach, which integrates Multi-Class, Multi-Channel Feature Fusion (MCCFF), achieves a classification accuracy of 33.17% for 40 classes. These results demonstrate the potential of EEG signals in advancing EEG visual classification and offering potential for future applications in visual machine models.<\/jats:p>","DOI":"10.3390\/s24216965","type":"journal-article","created":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T09:11:24Z","timestamp":1730279484000},"page":"6965","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Decoding Brain Signals from Rapid-Event EEG for Visual Analysis Using Deep Learning"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9433-7258","authenticated-orcid":false,"given":"Madiha","family":"Rehman","sequence":"first","affiliation":[{"name":"Institute of Computer Science, Khwaja Fareed University of Engineering & Information Technology, Rahim Yar Khan 64200, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Humaira","family":"Anwer","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Khwaja Fareed University of Engineering & Information Technology, Rahim Yar Khan 64200, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0101-4781","authenticated-orcid":false,"given":"Helena","family":"Garay","sequence":"additional","affiliation":[{"name":"Universidad Europea del Atlantico, Isabel Torres 21, 39011 Santander, Spain"},{"name":"Universidade Internacional do Cuanza, Cuito EN 250, Angola"},{"name":"Universidad de La Romana, Edificio G&G, C\/H\u00e9ctor Ren\u00e9 Gil, Esquina C\/Francisco Castillo Marquez, La Romana 22000, Dominican Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9872-3082","authenticated-orcid":false,"given":"Josep","family":"Alemany-Iturriaga","sequence":"additional","affiliation":[{"name":"Universidad de La Romana, Edificio G&G, C\/H\u00e9ctor Ren\u00e9 Gil, Esquina C\/Francisco Castillo Marquez, La Romana 22000, Dominican Republic"},{"name":"Facultad de Ciencias Sociales y Humanidades, Universidad Europea del Atl\u00e1ntico, Isabel Torres 21, 39011 Santander, Spain"},{"name":"Departamento de Ciencias de Lenguaje, Educaci\u00f3n y Comunicaciones, Universidad Internacional Iberoamericana Arecibo, Arecibo, PR 00613, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isabel De la Torre","family":"D\u00edez","sequence":"additional","affiliation":[{"name":"Department of Signal Theory, Communications and Telematics Engineering, University of Valladolid, 47011 Valladolid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0671-2060","authenticated-orcid":false,"given":"Hafeez ur Rehman","family":"Siddiqui","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Khwaja Fareed University of Engineering & Information Technology, Rahim Yar Khan 64200, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3747-1263","authenticated-orcid":false,"given":"Saleem","family":"Ullah","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Khwaja Fareed University of Engineering & Information Technology, Rahim Yar Khan 64200, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Reyes, L.M., Rodr\u00edguez-Res\u00e9ndiz, J., Avecilla-Ram\u00edrez, G.N., and Garc\u00eda-Gomar, M.L. 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