{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T16:51:59Z","timestamp":1777049519582,"version":"3.51.4"},"reference-count":32,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"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":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.bspc.2026.110365","type":"journal-article","created":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T13:06:27Z","timestamp":1777035987000},"page":"110365","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["STF-CGT with multi-level anchored distillation for emotion-induced EEG-based class-incremental person identification"],"prefix":"10.1016","volume":"122","author":[{"given":"Shunchang","family":"Su","sequence":"first","affiliation":[]},{"given":"Shuai","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Manjie","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Liping","family":"Wei","sequence":"additional","affiliation":[]},{"given":"Zhengang","family":"Yan","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.bspc.2026.110365_b1","doi-asserted-by":"crossref","DOI":"10.1155\/2021\/5229576","article-title":"Review on EEG-based authentication technology","volume":"2021","author":"Zhang","year":"2021","journal-title":"Comput. Intell. Neurosci."},{"issue":"1","key":"10.1016\/j.bspc.2026.110365_b2","doi-asserted-by":"crossref","first-page":"74","DOI":"10.3390\/axioms12010074","article-title":"EEG-based person identification and authentication using deep convolutional neural network","volume":"12","author":"Alsumari","year":"2023","journal-title":"Axioms"},{"key":"10.1016\/j.bspc.2026.110365_b3","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.neunet.2020.12.003","article-title":"A comprehensive study of class incremental learning algorithms for visual tasks","volume":"135","author":"Belouadah","year":"2021","journal-title":"Neural Netw."},{"issue":"3","key":"10.1016\/j.bspc.2026.110365_b4","doi-asserted-by":"crossref","DOI":"10.1088\/1741-2552\/aab2f2","article-title":"A review of classification algorithms for EEG-based brain\u2013computer interfaces: a 10 year update","volume":"15","author":"Lotte","year":"2018","journal-title":"J. Neural Eng."},{"key":"10.1016\/j.bspc.2026.110365_b5","series-title":"2020 International Joint Conference on Neural Networks","first-page":"1","article-title":"TSception: A deep learning framework for emotion detection using EEG","author":"Ding","year":"2020"},{"issue":"3","key":"10.1016\/j.bspc.2026.110365_b6","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1109\/TCDS.2019.2924648","article-title":"Affective EEG-based person identification using the deep learning approach","volume":"12","author":"Wilaiprasitporn","year":"2020","journal-title":"IEEE Trans. Cogn. Dev. Syst."},{"issue":"1","key":"10.1016\/j.bspc.2026.110365_b7","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1186\/s13634-015-0251-9","article-title":"A review of channel selection algorithms for EEG signal processing","volume":"2015","author":"Alotaiby","year":"2015","journal-title":"EURASIP J. Adv. Signal Process."},{"issue":"1","key":"10.1016\/j.bspc.2026.110365_b8","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1007\/s00521-022-07795-0","article-title":"Biometric identification system using EEG signals","volume":"35","author":"Tatar","year":"2023","journal-title":"Neural Comput. Appl."},{"issue":"35","key":"10.1016\/j.bspc.2026.110365_b9","doi-asserted-by":"crossref","first-page":"83205","DOI":"10.1007\/s11042-024-18693-z","article-title":"Person identification using autoencoder-CNN approach with multitask-based EEG biometric","volume":"83","author":"Bandana Das","year":"2024","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.bspc.2026.110365_b10","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.patrec.2023.08.010","article-title":"AITST\u2014Affective EEG-based person identification via interrelated temporal\u2013spatial transformer","volume":"174","author":"Cai","year":"2023","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.bspc.2026.110365_b11","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121323","article-title":"Visgin: Visibility graph neural network on one-dimensional data for biometric authentication","volume":"237","author":"Aslan","year":"2024","journal-title":"Expert Syst. Appl."},{"issue":"1","key":"10.1016\/j.bspc.2026.110365_b12","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1007\/s11517-025-03452-5","article-title":"Impact of fatigue levels on EEG-based personal recognition","volume":"64","author":"Shao","year":"2026","journal-title":"Med. Biol. Eng. Comput."},{"key":"10.1016\/j.bspc.2026.110365_b13","series-title":"The Thirteenth International Conference on Learning Representations","article-title":"Brainuicl: An unsupervised individual continual learning framework for EEG applications","author":"Zhou","year":"2025"},{"issue":"3","key":"10.1016\/j.bspc.2026.110365_b14","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":"2020","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"9","key":"10.1016\/j.bspc.2026.110365_b15","first-page":"3804","article-title":"A multi-dimensional convolutional attention transformer for EEG-based classification","volume":"33","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"12","key":"10.1016\/j.bspc.2026.110365_b16","doi-asserted-by":"crossref","first-page":"2935","DOI":"10.1109\/TPAMI.2017.2773081","article-title":"Learning without forgetting","volume":"40","author":"Li","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.bspc.2026.110365_b17","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"2001","article-title":"iCaRL: Incremental classifier and representation learning","author":"Rebuffi","year":"2017"},{"key":"10.1016\/j.bspc.2026.110365_b18","series-title":"Deep class-incremental learning: A survey","author":"Zhou","year":"2023"},{"key":"10.1016\/j.bspc.2026.110365_b19","series-title":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"12981","article-title":"Cross-subject EEG emotion recognition based on interconnected dynamic domain adaptation","author":"An","year":"2024"},{"key":"10.1016\/j.bspc.2026.110365_b20","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"3913","article-title":"Fetril: Feature translation for exemplar-free class-incremental learning","author":"Petit","year":"2023"},{"key":"10.1016\/j.bspc.2026.110365_b21","series-title":"Proceedings of the 35th International Conference on Machine Learning","first-page":"2825","article-title":"Explicit inductive bias for transfer learning with convolutional networks","volume":"vol. 80","author":"Li","year":"2018"},{"key":"10.1016\/j.bspc.2026.110365_b22","first-page":"15920","article-title":"Dark experience for general continual learning: A strong, simple baseline","volume":"vol. 33","author":"Buzzega","year":"2020"},{"key":"10.1016\/j.bspc.2026.110365_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.118819","article-title":"Similar brains blend emotion in similar ways: Neural representations of individual difference in emotion profiles","volume":"247","author":"Hu","year":"2022","journal-title":"NeuroImage"},{"issue":"3","key":"10.1016\/j.bspc.2026.110365_b24","doi-asserted-by":"crossref","first-page":"2496","DOI":"10.1109\/TAFFC.2022.3164516","article-title":"Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition","volume":"14","author":"Shen","year":"2023","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"3","key":"10.1016\/j.bspc.2026.110365_b25","doi-asserted-by":"crossref","first-page":"1110","DOI":"10.1109\/TCYB.2018.2797176","article-title":"EmotionMeter: A multimodal framework for recognizing human emotions","volume":"49","author":"Zheng","year":"2019","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.bspc.2026.110365_b26","article-title":"Emotion recognition from EEG using a deep learning framework with multi-view features","volume":"334","author":"Zhao","year":"2020","journal-title":"J. Neurosci. Methods"},{"key":"10.1016\/j.bspc.2026.110365_b27","series-title":"CL-LoRA: Continual low-rank adaptation for rehearsal-free class-incremental learning","author":"He","year":"2025"},{"issue":"2","key":"10.1016\/j.bspc.2026.110365_b28","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1080\/09540099550039318","article-title":"Catastrophic forgetting, rehearsal and pseudorehearsal","volume":"7","author":"Robins","year":"1995","journal-title":"Connect. Sci."},{"issue":"10","key":"10.1016\/j.bspc.2026.110365_b29","doi-asserted-by":"crossref","first-page":"77","DOI":"10.3991\/ijoe.v15i10.10880","article-title":"EEG based biometric identification using correlation and MLPNN models","volume":"15","author":"Waili","year":"2019","journal-title":"Int. J. Online Biomed. Eng. (IJOE)"},{"key":"10.1016\/j.bspc.2026.110365_b30","doi-asserted-by":"crossref","first-page":"10655","DOI":"10.1007\/s11042-019-7258-4","article-title":"EEG-based biometric identification with convolutional neural network","volume":"79","author":"Chen","year":"2020","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.bspc.2026.110365_b31","first-page":"1","article-title":"Affective EEG-based person identification using channel attention convolutional neural dense connection network","volume":"2021","author":"Zhang","year":"2021","journal-title":"Secur. Commun. Netw."},{"issue":"3","key":"10.1016\/j.bspc.2026.110365_b32","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1109\/TCDS.2019.2924648","article-title":"Affective EEG-based person identification using the deep learning approach","volume":"12","author":"Wilaiprasitporn","year":"2020","journal-title":"IEEE Trans. Cogn. Dev. Syst."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426009195?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426009195?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T16:19:31Z","timestamp":1777047571000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426009195"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":32,"alternative-id":["S1746809426009195"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110365","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"STF-CGT with multi-level anchored distillation for emotion-induced EEG-based class-incremental person identification","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110365","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":"110365"}}