{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:04:43Z","timestamp":1784203483635,"version":"3.55.0"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"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":["Neural Networks"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.neunet.2026.109072","type":"journal-article","created":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T00:44:55Z","timestamp":1777941895000},"page":"109072","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Real-time emotion recognition based on EEG signals using a hybrid batch-stream architecture"],"prefix":"10.1016","volume":"202","author":[{"given":"Mohammad Hosein","family":"Houshmand","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7933-221X","authenticated-orcid":false,"given":"Boshra","family":"Pishgoo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"11","key":"10.1016\/j.neunet.2026.109072_bib0023","doi-asserted-by":"crossref","first-page":"6553","DOI":"10.3390\/su14116553","article-title":"Predict students\u2019 attention in online learning using EEG data","volume":"14","author":"Al-Nafjan","year":"2022","journal-title":"Sustainability"},{"key":"10.1016\/j.neunet.2026.109072_bib0024","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.107674","article-title":"Emotion recognition in virtual and non-virtual environments using EEG signals: Dataset and evaluation","volume":"106","author":"Babu","year":"2025","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.neunet.2026.109072_bib0032","series-title":"Proc. 2007 SIAM Int. Conf. Data Mining (SDM)","first-page":"443","article-title":"Learning from time-changing data with adaptive windowing","author":"Bifet","year":"2007"},{"key":"10.1016\/j.neunet.2026.109072_bib0031","series-title":"Proc. 8th Int. Symp. Intelligent Data Analysis (IDA \u201909)","first-page":"249","article-title":"Adaptive learning from evolving data streams","author":"Bifet","year":"2009"},{"issue":"1319574","key":"10.1016\/j.neunet.2026.109072_bib0008","first-page":"1","article-title":"Real-time EEG-based emotion recognition for neurohumanities: Perspectives from principal component analysis and tree-based algorithms","volume":"18","author":"Blanco-Rios","year":"2024","journal-title":"Frontiers in Human Neuroscience"},{"key":"10.1016\/j.neunet.2026.109072_bib0026","series-title":"Classification and regression trees","author":"Breiman","year":"1984"},{"issue":"107060","key":"10.1016\/j.neunet.2026.109072_bib0022","first-page":"1","article-title":"Emotion recognition using multi-scale EEG features through graph convolutional attention network","volume":"184","author":"Cao","year":"2025","journal-title":"Neural Network"},{"key":"10.1016\/j.neunet.2026.109072_bib0010","first-page":"1","article-title":"LRCOMF: A Learn-Review-Challenge Online Meta Learning Framework for EEG Emotion Recognition with Unlabeled Online Samples","author":"Chen","year":"2025","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"10.1016\/j.neunet.2026.109072_bib0005","first-page":"1769","article-title":"From online to batch learning with cutoff-averaging","volume":"17","author":"Dekel","year":"2009","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.neunet.2026.109072_bib0017","doi-asserted-by":"crossref","unstructured":"Y. Ding, Y. Zhang, B. Liu, and S.J. Pan, \u201cTSception: A deep learning framework for emotion detection using EEG,\u201d 2020 International Joint Conference on Neural Networks (IJCNN), 2020.","DOI":"10.1109\/IJCNN48605.2020.9206750"},{"issue":"106338","key":"10.1016\/j.neunet.2026.109072_bib0009","first-page":"1","article-title":"Online continual decoding of streaming EEG signal with a balanced and informative memory buffer","volume":"176","author":"Duan","year":"2024","journal-title":"Neural Networks"},{"issue":"1","key":"10.1016\/j.neunet.2026.109072_bib0027","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","article-title":"Extremely randomized trees","volume":"63","author":"Geurts","year":"2006","journal-title":"Machine Learning"},{"issue":"9","key":"10.1016\/j.neunet.2026.109072_bib0030","doi-asserted-by":"crossref","first-page":"1469","DOI":"10.1007\/s10994-017-5642-8","article-title":"Adaptive random forests for evolving data stream classification","volume":"106","author":"Gomes","year":"2017","journal-title":"Machine Learning"},{"issue":"2","key":"10.1016\/j.neunet.2026.109072_bib0002","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1145\/3373464.3373470","article-title":"Machine learning for streaming data: State of the art, challenges, and opportunities","volume":"21","author":"Gomes","year":"2019","journal-title":"ACM SIGKDD Explorations Newsletter"},{"key":"10.1016\/j.neunet.2026.109072_bib0016","series-title":"Proc. Int. Conf. Neural Information Processing (ICONIP)","first-page":"117","article-title":"Challenges in representation learning: A report on three machine learning contests","author":"Goodfellow","year":"2013"},{"issue":"12","key":"10.1016\/j.neunet.2026.109072_bib0003","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.neucom.2021.04.112","article-title":"Online learning: A comprehensive survey","volume":"459","author":"Hoi","year":"2021","journal-title":"Neurocomputing"},{"issue":"4","key":"10.1016\/j.neunet.2026.109072_bib0020","first-page":"1","article-title":"A novel DE-CNN-BiLSTM multi-fusion model for EEG emotion recognition","volume":"10","author":"Jiang","year":"2022","journal-title":"Mathematics"},{"issue":"1","key":"10.1016\/j.neunet.2026.109072_bib0012","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/T-AFFC.2011.15","article-title":"DEAP: A database for emotion analysis using physiological signals","volume":"3","author":"Koelstra","year":"2012","journal-title":"IEEE Transactions on Affective Computing"},{"key":"10.1016\/j.neunet.2026.109072_bib0033","series-title":"International Joint Conference of Artificial Intelligence","first-page":"1137","article-title":"A study of cross-validation and bootstrap for accuracy estimation and model selection","volume":"14(2)","author":"Kohavi","year":"1995"},{"issue":"6","key":"10.1016\/j.neunet.2026.109072_bib0004","doi-asserted-by":"crossref","first-page":"2367","DOI":"10.1109\/TNNLS.2017.2677970","article-title":"Online learning algorithms can converge comparably fast as batch learning","volume":"29","author":"Lin","year":"2018","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"2","key":"10.1016\/j.neunet.2026.109072_bib0013","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1109\/TCDS.2021.3071170","article-title":"Comparing recognition performance and robustness of multimodal deep learning models for multimodal emotion recognition","volume":"14","author":"Liu","year":"2021","journal-title":"IEEE Transactions on Cognitive and Developmental Systems"},{"issue":"102610","key":"10.1016\/j.neunet.2026.109072_bib0001","first-page":"1","article-title":"Cognitive neuroscience and robotics: Advancements and future research directions","volume":"85","author":"Liu","year":"2024","journal-title":"Robotics and Computer\u2013Integrated Manufacturing"},{"key":"10.1016\/j.neunet.2026.109072_bib0011","first-page":"1","article-title":"Online Sequential EEG Emotion Recognition with Prototypical Alignment Based Transfer Model","author":"Liu","year":"2025","journal-title":"Annu Int Conference on IEEE Engineering and Medical Biology Society"},{"issue":"2","key":"10.1016\/j.neunet.2026.109072_bib0014","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1109\/TAFFC.2018.2884461","article-title":"AMIGOS: A dataset for affect, personality and mood research on individuals and groups","volume":"12","author":"Miranda-Correa","year":"2018","journal-title":"IEEE Transactions on Affective Computing"},{"issue":"5","key":"10.1016\/j.neunet.2026.109072_bib0006","doi-asserted-by":"crossref","first-page":"2387","DOI":"10.3390\/s23052387","article-title":"Online learning for wearable EEG-based emotion classification","volume":"23","author":"Moontaha","year":"2023","journal-title":"Sensors"},{"issue":"5","key":"10.1016\/j.neunet.2026.109072_bib0007","doi-asserted-by":"crossref","first-page":"1589","DOI":"10.3390\/s21051589","article-title":"Real-time emotion classification using EEG data stream in e-learning contexts","volume":"21","author":"Nandi","year":"2021","journal-title":"Sensors"},{"issue":"12","key":"10.1016\/j.neunet.2026.109072_bib0015","doi-asserted-by":"crossref","first-page":"1424","DOI":"10.1109\/34.895976","article-title":"Automatic analysis of facial expressions: The state of the art","volume":"22","author":"Pantic","year":"2000","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"131","key":"10.1016\/j.neunet.2026.109072_bib0034","first-page":"1","article-title":"A review on EEG-based multimodal learning for emotion recognition","volume":"58","author":"Pillalamarri","year":"2025","journal-title":"Artificial Intelligence Review"},{"key":"10.1016\/j.neunet.2026.109072_bib0028","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.ins.2020.07.026","article-title":"A hybrid distributed batch-stream processing approach for anomaly detection","volume":"543","author":"Pishgoo","year":"2021","journal-title":"Information Sciences"},{"key":"10.1016\/j.neunet.2026.109072_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.109749","article-title":"A dynamic feature selection and intelligent model serving for hybrid batch-stream processing","volume":"256","author":"Pishgoo","year":"2022","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109072_bib0019","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 Transactions on Affective Computing"},{"key":"10.1016\/j.neunet.2026.109072_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.104999","article-title":"STILN: A novel spatial-temporal information learning network for EEG-based emotion recognition","volume":"85","author":"Tang","year":"2023","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.neunet.2026.109072_bib0025","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/j.sna.2017.07.012","article-title":"A real-time wearable emotion detection headband based on EEG measurement","volume":"263","author":"Wei","year":"2017","journal-title":"Sensors and Actuators A: Physical"},{"issue":"37","key":"10.1016\/j.neunet.2026.109072_bib0021","first-page":"1","article-title":"SAE+LSTM: A new framework for emotion recognition from multi-channel EEG","volume":"13","author":"Zhang","year":"2019","journal-title":"Frontiers in Neurorobotics"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026005320?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026005320?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T11:15:17Z","timestamp":1784200517000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026005320"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":34,"alternative-id":["S0893608026005320"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109072","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Real-time emotion recognition based on EEG signals using a hybrid batch-stream architecture","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109072","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":"109072"}}