{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T14:11:48Z","timestamp":1779372708391,"version":"3.53.1"},"reference-count":39,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.eswa.2026.132708","type":"journal-article","created":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T23:31:33Z","timestamp":1778196693000},"page":"132708","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Channel-temporal separation for EEG signal extraction and classification in motor imagery tasks"],"prefix":"10.1016","volume":"327","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-8248-1860","authenticated-orcid":false,"given":"Yingjie","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5362-2450","authenticated-orcid":false,"given":"Xiu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihua","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaoying","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"8","key":"10.1016\/j.eswa.2026.132708_bib0001","doi-asserted-by":"crossref","first-page":"5789","DOI":"10.1007\/s10462-021-09958-2","article-title":"Transformer models for text-based emotion detection: a review of BERT-based approaches","volume":"54","author":"Acheampong","year":"2021","journal-title":"Artificial Intelligence Review"},{"key":"10.1016\/j.eswa.2026.132708_bib0002","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2020.102172","article-title":"Deep learning for motor imagery EEG-based classification: A review","volume":"63","author":"Al-Saegh","year":"2021","journal-title":"Biomedical Signal Processing and Control"},{"issue":"2","key":"10.1016\/j.eswa.2026.132708_bib0003","doi-asserted-by":"crossref","first-page":"2249","DOI":"10.1109\/TII.2022.3197419","article-title":"Physics-informed attention temporal convolutional network for EEG-based motor imagery classification","volume":"19","author":"Altaheri","year":"2022","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"10.1016\/j.eswa.2026.132708_bib0004","doi-asserted-by":"crossref","DOI":"10.3389\/fnins.2012.00039","article-title":"Filter bank common spatial pattern algorithm on BCI competition IV datasets 2a and 2b","volume":"6","author":"Ang","year":"2012","journal-title":"Frontiers in Neuroscience"},{"key":"10.1016\/j.eswa.2026.132708_bib0005","unstructured":"Bai, S., Kolter, J. Z., & Koltun, V. (2018). An empirical evaluation of generic convolutional and recurrent networks for sequence modeling.10.48550\/arXiv.1803.01271."},{"key":"10.1016\/j.eswa.2026.132708_bib0006","first-page":"1","article-title":"Bci competition 2008\u2013graz data set a","volume":"16","author":"Brunner","year":"2008","journal-title":"Institute for Knowledge Discovery (Laboratory of Brain-Computer Interfaces), Graz University of Technology"},{"key":"10.1016\/j.eswa.2026.132708_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.106092","article-title":"Ifbclnet: Spatio-temporal frequency feature extraction-based mi-eeg classification convolutional network","volume":"92","author":"Cao","year":"2024","journal-title":"Biomedical Signal Processing and Control"},{"issue":"14","key":"10.1016\/j.eswa.2026.132708_bib0008","doi-asserted-by":"crossref","DOI":"10.3390\/s23146434","article-title":"Electroencephalography signal processing: A comprehensive review and analysis of methods and techniques","volume":"23","author":"Chaddad","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.eswa.2026.132708_bib0009","series-title":"European conference on computer vision","first-page":"363","article-title":"Wavelet convolutions for large receptive fields","author":"Finder","year":"2025"},{"key":"10.1016\/j.eswa.2026.132708_bib0010","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1109\/RBME.2020.2969915","article-title":"A review on machine learning for EEG signal processing in bioengineering","volume":"14","author":"Hosseini","year":"2020","journal-title":"IEEE Reviews In Biomedical Engineering"},{"issue":"15","key":"10.1016\/j.eswa.2026.132708_bib0011","doi-asserted-by":"crossref","first-page":"12527","DOI":"10.1007\/s00521-022-07292-4","article-title":"Human emotion recognition from EEG-based brain\u2013computer interface using machine learning: A comprehensive review","volume":"34","author":"Houssein","year":"2022","journal-title":"Neural Computing and Applications"},{"issue":"5","key":"10.1016\/j.eswa.2026.132708_bib0012","doi-asserted-by":"crossref","DOI":"10.3390\/s25051400","article-title":"Deep learning approach for automatic heartbeat classification","volume":"25","author":"Guerra","year":"2025","journal-title":"Sensors"},{"key":"10.1016\/j.eswa.2026.132708_bib0013","series-title":"2020\u202fIEEE International conference on systems, man, and cybernetics (SMC)","first-page":"2958","article-title":"Eeg-tcnet: An accurate temporal convolutional network for embedded motor-imagery brain\u2013machine interfaces","author":"Ingolfsson","year":"2020"},{"key":"10.1016\/j.eswa.2026.132708_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.123975","article-title":"A learnable continuous wavelet-based multi-branch attentive convolutional neural network for spatio\u2013spectral\u2013temporal EEG signal decoding","volume":"251","author":"Kim","year":"2024","journal-title":"Expert Systems with Applications"},{"issue":"5","key":"10.1016\/j.eswa.2026.132708_bib0015","doi-asserted-by":"crossref","DOI":"10.1088\/1741-2552\/aace8c","article-title":"Eegnet: A compact convolutional neural network for eeg-based brain\u2013computer interfaces","volume":"15","author":"Lawhern","year":"2018","journal-title":"Journal of Neural Engineering"},{"key":"10.1016\/j.eswa.2026.132708_bib0016","first-page":"1","article-title":"Bci competition 2008\u2013graz data set b","volume":"16","author":"Leeb","year":"2008","journal-title":"Graz University of Technology, Austria"},{"key":"10.1016\/j.eswa.2026.132708_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.smrv.2022.101689","article-title":"Sleep quality and architecture in idiopathic generalized epilepsy: A systematic review and meta-analysis","volume":"65","author":"Lehner","year":"2022","journal-title":"Sleep Medicine Reviews"},{"issue":"4","key":"10.1016\/j.eswa.2026.132708_bib0018","doi-asserted-by":"crossref","first-page":"2302","DOI":"10.1109\/TSMC.2020.3048950","article-title":"Waveletkernelnet: An interpretable deep neural network for industrial intelligent diagnosis","volume":"52","author":"Li","year":"2021","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"key":"10.1016\/j.eswa.2026.132708_bib0019","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.112599","article-title":"Mas-dgat-net: A dynamic graph attention network with multibranch feature extraction and staged fusion for eeg emotion recognition","volume":"305","author":"Liu","year":"2024","journal-title":"Knowledge-Based Systems"},{"issue":"7963","key":"10.1016\/j.eswa.2026.132708_bib0020","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1038\/s41586-023-06094-5","article-title":"Walking naturally after spinal cord injury using a brain\u2013spine interface","volume":"618","author":"Lorach","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.eswa.2026.132708_bib0021","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.ijpsycho.2021.02.020","article-title":"Frontal brain areas are more involved during motor imagery than during motor execution\/preparation of a response sequence","volume":"164","author":"Van der Lubbe","year":"2021","journal-title":"International Journal of Psychophysiology"},{"issue":"86","key":"10.1016\/j.eswa.2026.132708_bib0022","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.eswa.2026.132708_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2021.102826","article-title":"Electroencephalography-based motor imagery classification using temporal convolutional network fusion","volume":"69","author":"Musallam","year":"2021","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.eswa.2026.132708_bib0024","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.neucom.2021.03.091","article-title":"A review on the attention mechanism of deep learning","volume":"452","author":"Niu","year":"2021","journal-title":"Neurocomputing"},{"issue":"11","key":"10.1016\/j.eswa.2026.132708_bib0025","doi-asserted-by":"crossref","first-page":"5391","DOI":"10.1002\/hbm.23730","article-title":"Deep learning with convolutional neural networks for EEG decoding and visualization","volume":"38","author":"Schirrmeister","year":"2017","journal-title":"Human Brain Mapping"},{"issue":"3","key":"10.1016\/j.eswa.2026.132708_bib0026","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1109\/TAFFC.2018.2817622","article-title":"Eeg emotion recognition using dynamical graph convolutional neural networks","volume":"11","author":"Song","year":"2018","journal-title":"IEEE Transactions on Affective Computing"},{"key":"10.1016\/j.eswa.2026.132708_bib0027","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1109\/TNSRE.2022.3230250","article-title":"Eeg conformer: Convolutional transformer for eeg decoding and visualization","volume":"31","author":"Song","year":"2022","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"issue":"3","key":"10.1016\/j.eswa.2026.132708_bib0028","doi-asserted-by":"crossref","DOI":"10.1063\/5.0236392","article-title":"Data collection, enhancement, and classification of functional near-infrared spectroscopy motor execution and imagery","volume":"96","author":"Sun","year":"2025","journal-title":"Review of Scientific Instruments"},{"key":"10.1016\/j.eswa.2026.132708_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.118373","article-title":"Theta but not beta power is positively associated with better explicit motor task learning","volume":"240","author":"Van Der Cruijsen","year":"2021","journal-title":"NeuroImage"},{"key":"10.1016\/j.eswa.2026.132708_bib0030","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.cogr.2021.04.001","article-title":"Review of the emotional feature extraction and classification using EEG signals","volume":"1","author":"Wang","year":"2021","journal-title":"Cognitive Robotics"},{"key":"10.1016\/j.eswa.2026.132708_bib0031","doi-asserted-by":"crossref","DOI":"10.3389\/fnhum.2025.1599960","article-title":"Multi-branch GAT-GRU-transformer for explainable EEG-based finger motor imagery classification","volume":"19","author":"Wang","year":"2025","journal-title":"Frontiers in Human Neuroscience"},{"key":"10.1016\/j.eswa.2026.132708_bib0032","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.104791","article-title":"Transformers in medical image segmentation: A review","volume":"84","author":"Xiao","year":"2023","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.eswa.2026.132708_bib0033","doi-asserted-by":"crossref","first-page":"6084","DOI":"10.1109\/ACCESS.2018.2889093","article-title":"Wavelet transform time-frequency image and convolutional network-based motor imagery EEG classification","volume":"7","author":"Xu","year":"2018","journal-title":"IEEE Access"},{"key":"10.1016\/j.eswa.2026.132708_bib0034","article-title":"Sagn: Sparse adaptive gated graph neural network with graph regularization for identifying dual-view brain networks","author":"Xue","year":"2024","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.eswa.2026.132708_bib0035","article-title":"Mcmtnet: Advanced network architectures for eeg-based motor imagery classification","author":"Yang","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.132708_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.108248","article-title":"Eeg emotion recognition using multi-dimensional features with attention-based inception capsule network","volume":"110","author":"Yu","year":"2025","journal-title":"Biomedical Signal Processing and Control"},{"issue":"3","key":"10.1016\/j.eswa.2026.132708_bib0037","doi-asserted-by":"crossref","DOI":"10.1088\/1741-2552\/abc902","article-title":"A survey on deep learning-based non-invasive brain signals: Recent advances and new frontiers","volume":"18","author":"Zhang","year":"2021","journal-title":"Journal of Neural Engineering"},{"issue":"1","key":"10.1016\/j.eswa.2026.132708_bib0038","article-title":"Ctnet: A convolutional transformer network for eeg-based motor imagery classification","volume":"14","author":"Zhao","year":"2024","journal-title":"Scientific Reports"},{"key":"10.1016\/j.eswa.2026.132708_bib0039","doi-asserted-by":"crossref","DOI":"10.1109\/TNSRE.2023.3323325","article-title":"A multi-domain convolutional neural network for EEG-based motor imagery decoding","author":"Zhi","year":"2023","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426016210?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426016210?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T13:40:34Z","timestamp":1779370834000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426016210"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":39,"alternative-id":["S0957417426016210"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132708","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Channel-temporal separation for EEG signal extraction and classification in motor imagery tasks","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132708","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"132708"}}