{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:07:28Z","timestamp":1775066848307,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,8,21]],"date-time":"2021-08-21T00:00:00Z","timestamp":1629504000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,8,21]],"date-time":"2021-08-21T00:00:00Z","timestamp":1629504000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2022,2]]},"DOI":"10.1007\/s13042-021-01414-5","type":"journal-article","created":{"date-parts":[[2021,8,21]],"date-time":"2021-08-21T06:02:26Z","timestamp":1629525746000},"page":"421-429","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["EEG-based Emotion Recognition with Feature Fusion Networks"],"prefix":"10.1007","volume":"13","author":[{"given":"Qiang","family":"Gao","sequence":"first","affiliation":[]},{"given":"Yi","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Qiaoju","family":"Kang","sequence":"additional","affiliation":[]},{"given":"Zekun","family":"Tian","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9295-7795","authenticated-orcid":false,"given":"Yu","family":"Song","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,8,21]]},"reference":[{"issue":"1","key":"1414_CR1","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/79.911197","volume":"18","author":"R Cowie","year":"2001","unstructured":"Cowie R et al (2001) Emotion recognition in human-computer interaction. IEEE Signal Process Mag 18(1):32\u201380","journal-title":"IEEE Signal Process Mag"},{"issue":"2","key":"1414_CR2","first-page":"126","volume":"47","author":"P Ekman","year":"1978","unstructured":"Ekman P, Friesen WV (1978) Facial action coding system (facs): a technique for the measurement of facial actions. Rivista Di Psichiatria 47(2):126\u201338","journal-title":"Rivista Di Psichiatria"},{"issue":"1","key":"1414_CR3","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/0005-7916(94)90063-9","volume":"25","author":"Margaret M Bradley","year":"1994","unstructured":"Bradley Margaret M, Lang PJ (1994) Measuring emotion: the self-assessment manikin and the semantic differential. J Behav Ther Exp Psychiatry 25(1):49\u201359","journal-title":"J Behav Ther Exp Psychiatry"},{"key":"1414_CR4","unstructured":"Mehrabian A, Russell JA (1974) An approach to environmental psychology[M]. MIT"},{"issue":"4","key":"1414_CR5","doi-asserted-by":"publisher","first-page":"373","DOI":"10.3233\/THC-181538","volume":"27","author":"D Li","year":"2019","unstructured":"Li D, Wang Z, Gao Q, Song Y, Yu X, Wang C (2019) Facial expression recognition based on Electroencephalogram and facial landmark localization. Technol Health Care 27(4):373\u2013387","journal-title":"Technol Health Care"},{"key":"1414_CR6","doi-asserted-by":"publisher","first-page":"61672","DOI":"10.1109\/ACCESS.2020.2984368","volume":"8","author":"N Ho","year":"2020","unstructured":"Ho N, Yang H, Kim S, Lee G (2020) Multimodal approach of speech emotion recognition using multi-level multi-attention-based recurrent neural network. IEEE Access 8:61672\u201361686","journal-title":"IEEE Access"},{"key":"1414_CR7","doi-asserted-by":"publisher","unstructured":"Yang Y, Gao Q, Song X, Song Y, Mao Z, Liu J (2021) Facial expression and EEG fusion for investigating continuous emotions of deaf subjects. IEEE Sens J  21(15):16894\u201316903. https:\/\/doi.org\/10.1109\/JSEN.2021.3078087","DOI":"10.1109\/JSEN.2021.3078087"},{"key":"1414_CR8","doi-asserted-by":"publisher","first-page":"155724","DOI":"10.1109\/ACCESS.2019.2949707","volume":"7","author":"D Li","year":"2019","unstructured":"Li D et al (2019) The fusion of electroencephalography and facial expression for continuous emotion recognition. IEEE Access 7:155724\u2013155736","journal-title":"IEEE Access"},{"key":"1414_CR9","doi-asserted-by":"crossref","unstructured":"Alarcao Soraia M, Fonseca Manuel J (2019) Emotions recognition using EEG signals: a survey. IEEE transactions on affective computing 10(3):374\u2013393","DOI":"10.1109\/TAFFC.2017.2714671"},{"issue":"5","key":"1414_CR10","doi-asserted-by":"publisher","first-page":"30","DOI":"10.5815\/ijigsp.2011.05.05","volume":"3","author":"SA Hosseini","year":"2011","unstructured":"Hosseini SA, Naghibi-Sistani MB (2011) Emotion recognition method using entropy analysis of EEG signals. Int J Image Graphics Signal Process 3(5):30","journal-title":"Int J Image Graphics Signal Process"},{"key":"1414_CR11","doi-asserted-by":"crossref","unstructured":"Duan R, Wang X, Lu B (2012) EEG-Based emotion recognition in listening music by using support vector machine and linear dynamic system. In: Proceedings of the 19th international conference on Neural Information Processing, pp 468\u2013475","DOI":"10.1007\/978-3-642-34478-7_57"},{"key":"1414_CR12","doi-asserted-by":"crossref","unstructured":"Duan R, Zhu J, Lu B (2013) Differential entropy feature for EEG-based emotion classification. In: 2013 6th International IEEE\/EMBS Conference on Neural Engineering (NER), pp 81\u201384","DOI":"10.1109\/NER.2013.6695876"},{"key":"1414_CR13","doi-asserted-by":"publisher","first-page":"162","DOI":"10.3389\/fnins.2018.00162","volume":"12","author":"X Li","year":"2018","unstructured":"Li X, Song D, Zhang P, Zhang Y, Hou Y, Hu B (2018) Exploring EEG features in cross-subject emotion recognition. Front Neurosci 12:162","journal-title":"Front Neurosci"},{"key":"1414_CR14","doi-asserted-by":"publisher","first-page":"53","DOI":"10.3389\/fncom.2019.00053","volume":"13","author":"F Yang","year":"2019","unstructured":"Yang F, Zhao X, Jiang W, Gao P, Liu G (2019) Multi-method fusion of cross-subject emotion recognition based on high-dimensional EEG features. Front Comput Neurosci 13:53","journal-title":"Front Comput Neurosci"},{"key":"1414_CR15","doi-asserted-by":"crossref","unstructured":"Suwicha, J, Setha, P. N, & Pasin, I (2014) Eeg-based emotion recognition using deep learning network with principal component based covariate shift adaptation. Sci World J: 627892","DOI":"10.1155\/2014\/627892"},{"key":"1414_CR16","doi-asserted-by":"crossref","unstructured":"S. Stober, A. Sternin, A. M. Owen, and J. A. Grahn (2015) Deep feature learning for EEG recordings 165:23\u201331.  arXiv:1511.04306","DOI":"10.1016\/j.neucom.2014.08.092"},{"key":"1414_CR17","doi-asserted-by":"crossref","unstructured":"Lawhern VJ, Solon AJ, Waytowich NR, Gordon S, Hung CP, Lance BJ (2018) EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces. J Neural Eng 15(5):056013.1\u2013056013.17","DOI":"10.1088\/1741-2552\/aace8c"},{"issue":"8","key":"1414_CR18","first-page":"329","volume":"9","author":"ES Salama","year":"2018","unstructured":"Salama ES, Elkhoribi RA, Shoman M, Shalaby MAW (2018) EEG-based emotion recognition using 3D convolutional neural networks. Int J Adv Comput Sci Appl 9(8):329\u2013337","journal-title":"Int J Adv Comput Sci Appl"},{"key":"1414_CR19","doi-asserted-by":"publisher","first-page":"49325","DOI":"10.1109\/ACCESS.2018.2868361","volume":"6","author":"B Nakisa","year":"2018","unstructured":"Nakisa B, Rastgoo MN, Rakotonirainy A, Maire F, Chandran V (2018) Long short term memory hyperparameter optimization for a neural network based emotion recognition framework. IEEE Access 6:49325\u201349338","journal-title":"IEEE Access"},{"key":"1414_CR20","doi-asserted-by":"crossref","unstructured":"Donmez H, Ozkurt N (2019) Emotion classification from EEG signals in convolutional neural networks 2019. In: Innovations in Intelligent Systems and Applications Conference (ASYU), pp 46364","DOI":"10.1109\/ASYU48272.2019.8946364"},{"key":"1414_CR21","doi-asserted-by":"crossref","unstructured":"Hwang S, Ki M, Hong K, Byun H (2020) Subject-independent EEG-based emotion recognition using adversarial learning. In: 2020 8th International Winter Conference on Brain-Computer Interface (BCI) pp 1\u20134","DOI":"10.1109\/BCI48061.2020.9061624"},{"issue":"1","key":"1414_CR22","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/T-AFFC.2011.15","volume":"3","author":"S Koelstra","year":"2012","unstructured":"Koelstra S et al (2012) DEAP: a database for emotion analysis: using physiological signals. IEEE Trans Affective Comput 3(1):18\u201331","journal-title":"IEEE Trans Affective Comput"},{"issue":"3","key":"1414_CR23","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1016\/0013-4694(70)90143-4","volume":"29","author":"B Hjorth","year":"1970","unstructured":"Hjorth B (1970) EEG analysis based on time domain properties. Electroencephalography Clin Neurophysiol 29(3):306\u2013310","journal-title":"Electroencephalography Clin Neurophysiol"},{"issue":"11","key":"1414_CR24","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y Lecun","year":"1998","unstructured":"Lecun Y, Bottou L (1998) Gradient-based learning applied to document recognition. Proc IEEE 86(11):2278\u20132324","journal-title":"Proc IEEE"},{"key":"1414_CR25","doi-asserted-by":"crossref","unstructured":"Xu H, Plataniotis KN (2016) \u201cEEG-based affect states classification using deep belief networks. In: Proc. Digit. Media Ind. Acad. Forum (DMIAF), pp 148\u2013153","DOI":"10.1109\/DMIAF.2016.7574921"},{"key":"1414_CR26","doi-asserted-by":"publisher","first-page":"118530","DOI":"10.1109\/ACCESS.2019.2936817","volume":"7","author":"JX Chen","year":"2019","unstructured":"Chen JX, Jiang DM, Zhang YN (2019) A hierarchical bidirectional GRU model with attention for EEG-based emotion classification. IEEE Access 7:118530\u2013118540","journal-title":"IEEE Access"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-021-01414-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-021-01414-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-021-01414-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T09:37:39Z","timestamp":1642757859000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-021-01414-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,21]]},"references-count":26,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,2]]}},"alternative-id":["1414"],"URL":"https:\/\/doi.org\/10.1007\/s13042-021-01414-5","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,21]]},"assertion":[{"value":"28 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 August 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}