{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:44:53Z","timestamp":1792784693375,"version":"4.5.0"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Hefei University of Technology School of Artificial Inteligence: Hefei University of Technology School of Computer and Information Engineering","award":["62176083"],"award-info":[{"award-number":["62176083"]}],"id":[{"id":"https:\/\/ror.org\/02czkny70","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Anhui Agriculture University: Anhui Agricultural University","award":["62472005"],"award-info":[{"award-number":["62472005"]}],"id":[{"id":"https:\/\/ror.org\/0327f3359","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["CCF Trans. Pervasive Comp. Interact."],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1007\/s42486-026-00230-6","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T06:01:37Z","timestamp":1776751297000},"page":"520-540","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A multi-scale graph diffusion convolution method for EEG-based emotion recognition with temporal-frequency fusion"],"prefix":"10.1007","volume":"8","author":[{"given":"Xinjun","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiming","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenyu","family":"Yue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0390-4761","authenticated-orcid":false,"given":"Yindong","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,21]]},"reference":[{"issue":"2","key":"230_CR1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.0030017","volume":"3","author":"S Achard","year":"2007","unstructured":"Achard, S., Bullmore, E.: Efficiency and cost of economical brain functional networks. PLoS Comput. Biol. 3(2), e17 (2007)","journal-title":"PLoS Comput. Biol."},{"key":"230_CR2","doi-asserted-by":"crossref","unstructured":"Alhagry, S., Fahmy, A.A., El-Khoribi, R.A., et al.: Emotion recognition based on EEG using LSTM recurrent neural network. Int. J. Adv. Comput. Sci. Appl. 8(10) (2017)","DOI":"10.14569\/IJACSA.2017.081046"},{"key":"230_CR3","doi-asserted-by":"crossref","unstructured":"Arjun, A., Aniket, S.R., Mahesh, R.P.: Introducing attention mechanism for eeg signals: emotion recognition with vision transformers. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC, IEEE, pp. 5723\u20135726 (2021)","DOI":"10.1109\/EMBC46164.2021.9629837"},{"key":"230_CR4","unstructured":"Bruna, J., Zaremba, W., Szlam, A., et al.: spectral networks and locally connected networks on graphs. arXiv preprint arXiv:1312.6203 (2014)"},{"key":"230_CR5","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-024-04994-3","volume":"28","author":"M Cao","year":"2025","unstructured":"Cao, M., Dong, Y., Chen, D., et al.: EEG-based emotion recognition model using fuzzy adjacency matrix combined with convolutional multi-head graph attention mechanism. Cluster Comput 28, 274 (2025). https:\/\/doi.org\/10.1007\/s10586-024-04994-3","journal-title":"Cluster Comput"},{"issue":"01","key":"230_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.16812\/j.cnki.cn31-1945.2017.01.001","volume":"13","author":"Y Chen","year":"2017","unstructured":"Chen, Y., Cui, Y., Wang, S.: Review of emotion recognition based on physiological signals. Syst. Simul. Technol. 13(01), 1\u20135 (2017). https:\/\/doi.org\/10.16812\/j.cnki.cn31-1945.2017.01.001","journal-title":"Syst. Simul. Technol."},{"issue":"5","key":"230_CR7","doi-asserted-by":"publisher","first-page":"6672","DOI":"10.1109\/TCSS.2024.3412074","volume":"11","author":"C Cheng","year":"2024","unstructured":"Cheng, C., Liu, W.Z., Feng, L., et al.: Dense graph convolutional with joint cross-attention network for multimodal emotion recognition. IEEE Trans. Comput. Soc. Syst. 11(5), 6672\u20136683 (2024)","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"issue":"4","key":"230_CR8","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1162\/jocn.2007.19.4.577","volume":"19","author":"M Codispoti","year":"2007","unstructured":"Codispoti, M., Ferrari, V., Bradley, M.M.: Repetition and event-related potentials: distinguishing early and late processes in affective picture perception. J. Cogn. Neurosci. 19(4), 577\u2013586 (2007). https:\/\/doi.org\/10.1162\/jocn.2007.19.4.577","journal-title":"J. Cogn. Neurosci."},{"issue":"1","key":"230_CR9","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/79.911197","volume":"18","author":"R Cowie","year":"2001","unstructured":"Cowie, R., Douglas-Cowie, E., Tsapatsoulis, N., Votsis, G., Kollias, S., Fellenz, W., Taylor, J.G.: Emotion recognition in human-computer interaction. IEEE Signal Process. Mag. 18(1), 32\u201380 (2001)","journal-title":"IEEE Signal Process. Mag."},{"key":"230_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2024.102522","volume":"61","author":"C Fan","year":"2024","unstructured":"Fan, C., Wang, J., Huang, W., Yang, X., Pei, G., Li, T., Lv, Z.: Light-weight residual convolution-based capsule network for EEG emotion recognition. Adv. Eng. Inform. 61, 102522 (2024)","journal-title":"Adv. Eng. Inform."},{"key":"230_CR11","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1016\/j.ijpsycho.2016.07.496","volume":"111","author":"V Ferrari","year":"2017","unstructured":"Ferrari, V., Codispoti, M., Bradley, M.M.: Repetition and ERPs during emotional scene processing: a selective review. Int. J. Psychophysiol. 111, 170\u2013177 (2017)","journal-title":"Int. J. Psychophysiol."},{"key":"230_CR12","doi-asserted-by":"publisher","first-page":"1664","DOI":"10.1038\/nn.4135","volume":"18","author":"E Finn","year":"2015","unstructured":"Finn, E., Shen, X., Scheinost, D., et al.: Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nat. Neurosci. 18, 1664\u20131671 (2015). https:\/\/doi.org\/10.1038\/nn.4135","journal-title":"Nat. Neurosci."},{"issue":"10","key":"230_CR13","doi-asserted-by":"publisher","first-page":"5917","DOI":"10.1109\/JBHI.2024.3416944","volume":"28","author":"H Gao","year":"2024","unstructured":"Gao, H., Wang, X., Chen, Z., et al.: Graph convolutional network with connectivity uncertainty for EEG-based emotion recognition. IEEE J. Biomed. Health Inform. 28(10), 5917\u20135928 (2024)","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"000","key":"230_CR14","first-page":"38","volume":"105","author":"AV Geetha","year":"2024","unstructured":"Geetha, A.V., Mala, T., Priyanka, D., et al.: Multimodal emotion recognition with deep learning: advancements, challenges, and future directions. Inform. Fus. 105(000), 38 (2024)","journal-title":"Inform. Fus."},{"key":"230_CR15","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., et al.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"230_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106243","volume":"205","author":"C Heng","year":"2020","unstructured":"Heng, C., Aiping, L., Xu, Z., Xiang, C., Kongqiao, W., Xun, C.: EEG-based emotion recognition using an end-to-end regional-asymmetric convolutional neural network. Knowl.-Based Syst. 205, 106243 (2020)","journal-title":"Knowl.-Based Syst."},{"issue":"8","key":"230_CR17","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"issue":"1","key":"230_CR19","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1109\/MCI.2015.2501545","volume":"11","author":"V Jayaram","year":"2016","unstructured":"Jayaram, V., Alamgir, M., Altun, Y., et al.: Transfer learning in brain-computer interfaces. IEEE Comput. Intell. Mag. 11(1), 20\u201331 (2016)","journal-title":"IEEE Comput. Intell. Mag."},{"key":"230_CR20","doi-asserted-by":"publisher","first-page":"9070","DOI":"10.1109\/TMM.2024.3385676","volume":"26","author":"M Jin","year":"2024","unstructured":"Jin, M., Du, C.D., He, H.G., et al.: PGCN: pyramidal graph convolutional network for EEG emotion recognition. IEEE Trans. Multimed. 26, 9070\u20139082 (2024)","journal-title":"IEEE Trans. Multimed."},{"key":"230_CR21","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1109\/TNSRE.2024.3355750","volume":"32","author":"D Klepl","year":"2024","unstructured":"Klepl, D., Wu, M., He, F.: Graph neural network-based EEG classification: a survey. IEEE Trans. Neural Syst. Rehabil. Eng. 32, 493\u2013503 (2024)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"1","key":"230_CR22","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/T-AFFC.2011.15","volume":"3","author":"S Koelstra","year":"2011","unstructured":"Koelstra, S., Muhl, C., Soleymani, M., et al.: DEAP: a database for emotion analysis; using physiological signals. IEEE Trans. Affect. Comput. 3(1), 18\u201331 (2011)","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"4","key":"230_CR23","doi-asserted-by":"publisher","first-page":"1686","DOI":"10.1109\/TCDS.2022.3175538","volume":"15","author":"W Kong","year":"2022","unstructured":"Kong, W., Qiu, M., Li, M., et al.: Causal graph convolutional neural network for emotion recognition. IEEE Trans. Cogn. Dev. Syst. 15(4), 1686\u20131693 (2022)","journal-title":"IEEE Trans. Cogn. Dev. Syst."},{"issue":"11","key":"230_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., Bengio, Y., et al.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"key":"230_CR25","doi-asserted-by":"publisher","DOI":"10.3390\/s23031404","volume":"23","author":"M Li","year":"2023","unstructured":"Li, M., Qiu, M., Kong, W., Zhu, L., Ding, Y.: Fusion graph representation of EEG for emotion recognition. Sensors 23, 1404 (2023). https:\/\/doi.org\/10.3390\/s23031404","journal-title":"Sensors"},{"issue":"1","key":"230_CR26","first-page":"255","volume":"34","author":"JY Li","year":"2023","unstructured":"Li, J.Y., Du, X.B., Zhu, Z.L., Deng, X.M., Ma, C.X., Wang, H.A.: Deep learning for EEG-based emotion recognition: a survey. Ruan Jian Xue Bao\/J. Softw. 34(1), 255\u2013276 (2023). ((in Chinese))","journal-title":"Ruan Jian Xue Bao\/J. Softw."},{"key":"230_CR27","doi-asserted-by":"publisher","DOI":"10.1186\/s40708-024-00242-x","volume":"11","author":"R Li","year":"2024","unstructured":"Li, R., Yang, X., Lou, J., et al.: A temporal-spectral graph convolutional neural network model for EEG emotion recognition within and across subjects. Brain Inform. 11, 30 (2024). https:\/\/doi.org\/10.1186\/s40708-024-00242-x","journal-title":"Brain Inform."},{"issue":"10","key":"230_CR28","doi-asserted-by":"publisher","first-page":"5755","DOI":"10.1109\/JBHI.2024.3395622","volume":"28","author":"C Li","year":"2024","unstructured":"Li, C., Wang, F., Zhao, Z., et al.: Attention-based temporal graph representation learning for EEG based emotion recognition. IEEE J. Biomed. Health Inform. 28(10), 5755\u20135767 (2024)","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"230_CR29","unstructured":"Li, Y., Yu, R., Shahabi, C., et al.: Diffusion convolutional recurrent neural network: data-driven traffic forecasting. arXiv preprint arXiv:1707.01926 (2017)"},{"key":"230_CR30","doi-asserted-by":"crossref","unstructured":"Li, Y., Zheng, W.N., Cui, Z., Zhang, T., Zong, Y.: A novel neural network model based on cerebral hemispheric asymmetry for EEG emotion recognition. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence. Stockholm: ACM, 1561\u20131567 (2018)","DOI":"10.24963\/ijcai.2018\/216"},{"key":"230_CR31","doi-asserted-by":"crossref","unstructured":"Li, W., Dong, J., Liu, S., Fan, L., Wang, S.: Dynamic stream selection network for subject-independent EEG-based emotion recognition. IEEE Sens. J. (2024)","DOI":"10.1109\/JSEN.2024.3390799"},{"key":"230_CR32","doi-asserted-by":"crossref","unstructured":"Li, C., Tang, T., Pan, Y., et al.: An efficient graph learning system for emotion recognition inspired by the cognitive prior graph of EEG brain network. IEEE Trans. Neural Netw. Learn. Syst. (2024)","DOI":"10.1109\/TNNLS.2024.3405663"},{"issue":"1","key":"230_CR33","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/s10044-016-0567-6","volume":"21","author":"A Mert","year":"2018","unstructured":"Mert, A., Akan, A.: Emotion recognition from EEG signals by using multivariate empirical mode decomposition. Pattern Anal. Appl. 21(1), 81\u201389 (2018)","journal-title":"Pattern Anal. Appl."},{"key":"230_CR34","volume-title":"Affective neuroscience: the foundations of human and animal emotions","author":"J Panksepp","year":"2004","unstructured":"Panksepp, J.: Affective neuroscience: the foundations of human and animal emotions. Oxford University Press, New York (2004)"},{"issue":"4","key":"230_CR35","doi-asserted-by":"publisher","first-page":"722","DOI":"10.1109\/TAFFC.2018.2840973","volume":"11","author":"L Piho","year":"2020","unstructured":"Piho, L., Tjahjadi, T.: A mutual information based adaptive windowing of informative EEG for emotion recognition. IEEE Trans. Affect. Comput. 11(4), 722\u2013735 (2020)","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"9","key":"230_CR36","doi-asserted-by":"publisher","first-page":"1332","DOI":"10.1093\/cercor\/bhi016","volume":"15","author":"R Salvador","year":"2005","unstructured":"Salvador, R., Suckling, J., Coleman, M.R., et al.: Neurophysiological architecture of functional magnetic resonance images of human brain. Cereb. Cortex 15(9), 1332\u20131342 (2005)","journal-title":"Cereb. Cortex"},{"key":"230_CR37","doi-asserted-by":"crossref","unstructured":"Samal, P., Hashmi, M.F.: Role of machine learning and deep learning techniques in EEG-based BCI emotion recognition system: a review. Artif. Intell. Rev. 57(3) (2024)","DOI":"10.1007\/s10462-023-10690-2"},{"issue":"1","key":"230_CR38","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1109\/TNN.2008.2005605","volume":"20","author":"F Scarselli","year":"2008","unstructured":"Scarselli, F., Gori, M., Tsoi, A.C., et al.: The graph neural network model. IEEE Trans. Neural Netw. 20(1), 61\u201380 (2008)","journal-title":"IEEE Trans. Neural Netw."},{"key":"230_CR39","doi-asserted-by":"crossref","unstructured":"Singh, S., Srivastava, N.: Emotion recognition for mental health prediction using AI techniques: an overview. Int. J. Adv. Res. Comput. Sci. 14(3) (2023)","DOI":"10.26483\/ijarcs.v14i3.6975"},{"issue":"03","key":"230_CR40","first-page":"2701","volume":"34","author":"T Song","year":"2020","unstructured":"Song, T., Liu, S., Zheng, W., et al.: Instance-adaptive graph for EEG emotion recognition. Proc. AAAI Conf. Artif. Intell. (AAAI) 34(03), 2701\u20132708 (2020)","journal-title":"Proc. AAAI Conf. Artif. Intell. (AAAI)"},{"issue":"4","key":"230_CR41","doi-asserted-by":"publisher","first-page":"118","DOI":"10.15171\/icnj.2017.01","volume":"4","author":"MZ Soroush","year":"2017","unstructured":"Soroush, M.Z., Maghooli, K., Setarehdan, S.K., et al.: A review on EEG signals based emotion recognition. Int. Clin. Neurosci. J. 4(4), 118\u2013129 (2017)","journal-title":"Int. Clin. Neurosci. J."},{"issue":"11","key":"230_CR42","first-page":"1","volume":"56","author":"X Sun","year":"2020","unstructured":"Sun, X., Li, H.: Overview of speech emotion recognition. Comput. Eng. Appl. 56(11), 1\u20139 (2020)","journal-title":"Comput. Eng. Appl."},{"issue":"1","key":"230_CR43","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1109\/TAFFC.2020.3025777","volume":"14","author":"W Tao","year":"2020","unstructured":"Tao, W., Li, C., Song, R., Juan Cheng, Y., Liu, F.W., Chen, X.: EEG-based emotion recognition via channel-wise attention and self attention. IEEE Trans. Affect. Comput. 14(1), 382\u2013393 (2020)","journal-title":"IEEE Trans. Affect. Comput."},{"key":"230_CR44","unstructured":"Tong, Z., Liang, Y., Sun, C., et al.: Directed graph convolutional network. arXiv preprint arXiv:2004.13970 (2020)"},{"key":"230_CR45","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., et al.: Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)"},{"key":"230_CR46","doi-asserted-by":"publisher","first-page":"93711","DOI":"10.1109\/ACCESS.2019.2927768","volume":"7","author":"ZM Wang","year":"2019","unstructured":"Wang, Z.M., Tong, Y., Heng, X.: Phase-locking value based graph convolutional neural networks for emotion recognition. IEEE Access 7, 93711\u201393722 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2927768","journal-title":"IEEE Access"},{"key":"230_CR47","doi-asserted-by":"crossref","unstructured":"Wang, F., Zhong, S.-H., Peng, J., et al.: Data augmentation for EEG-based emotion recognition with deep convolutional neural networks. MultiMedia Model. (MMM) 82\u201393 (2018)","DOI":"10.1007\/978-3-319-73600-6_8"},{"key":"230_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.129315","volume":"622","author":"T Weilong","year":"2025","unstructured":"Weilong, T., Hongyi, Z., Yingbei, W., et al.: SEDA-EEG: a semi-supervised emotion recognition network with domain adaptation for cross-subject EEG analysis. Neurocomputing. 622, 129315 (2025). https:\/\/doi.org\/10.1016\/j.neucom.2024.129315","journal-title":"Neurocomputing."},{"issue":"4","key":"230_CR49","doi-asserted-by":"publisher","first-page":"2042","DOI":"10.1109\/TAFFC.2024.3394873","volume":"15","author":"HC Yan","year":"2024","unstructured":"Yan, H.C., Guo, K.L., Xing, X.F., et al.: Bridge graph attention based graph convolution network with multi-scale transformer for EEG emotion recognition. IEEE Trans. Affect. Comput. 15(4), 2042\u20132054 (2024)","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"2","key":"230_CR50","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1109\/TCDS.2017.2685338","volume":"10","author":"YM Yang","year":"2018","unstructured":"Yang, Y.M., Wu, Q.M.J., Zheng, W.L., Lu, B.L.: EEG-based emotion recognition using hierarchical network with subnetwork nodes. IEEE Trans. Cogn. Dev. Syst. 10(2), 408\u2013419 (2018). https:\/\/doi.org\/10.1109\/TCDS.2017.2685338","journal-title":"IEEE Trans. Cogn. Dev. Syst."},{"key":"230_CR51","doi-asserted-by":"publisher","unstructured":"Yang, Y.L., Wu, Q.F., Qiu, M., Wang, Y.D., Chen, X.W.: Emotion recognition from multi-channel EEG through parallel convolutional recurrent neural network. In: Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN). Rio de Janeiro: IEEE, 1\u20137. (2018) https:\/\/doi.org\/10.1109\/IJCNN.2018.8489331","DOI":"10.1109\/IJCNN.2018.8489331"},{"issue":"9","key":"230_CR52","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.1360\/N112018-00337","volume":"49","author":"GH Zhang","year":"2019","unstructured":"Zhang, G.H., Yu, M.J., Chen, G., Han, Y.H., Zhang, D., Zhao, G.Z., Liu, Y.J.: A review of EEG features for emotion recognition. Sci. Sin. Inform. 49(9), 1097\u20131118 (2019). https:\/\/doi.org\/10.1360\/N112018-00337. (in Chinese with English abstract)","journal-title":"Sci. Sin. Inform."},{"issue":"1","key":"230_CR53","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1109\/TAFFC.2021.3051332","volume":"14","author":"G Zhang","year":"2021","unstructured":"Zhang, G., Yu, M., Liu, Y.-J., et al.: SparseDGCNN: recognizing emotion from multichannel EEG signals. IEEE Trans. Affect. Comput. 14(1), 537\u2013548 (2021)","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"3","key":"230_CR54","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1109\/TAMD.2015.2431497","volume":"7","author":"WL Zheng","year":"2015","unstructured":"Zheng, W.L., Lu, B.L.: Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks. IEEE Trans. Auton. Mental Dev. 7(3), 162\u2013175 (2015)","journal-title":"IEEE Trans. Auton. Mental Dev."},{"issue":"3","key":"230_CR55","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1109\/TAFFC.2017.2712143","volume":"10","author":"WL Zheng","year":"2019","unstructured":"Zheng, W.L., Zhu, J.Y., Lu, B.L.: Identifying stable patterns over time for emotion recognition from EEG. IEEE Trans. Affect. Comput. 10(3), 417\u2013429 (2019). https:\/\/doi.org\/10.1109\/TAFFC.2017.2712143","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"3","key":"230_CR56","doi-asserted-by":"publisher","first-page":"1290","DOI":"10.1109\/TAFFC.2020.2994159","volume":"13","author":"P Zhong","year":"2020","unstructured":"Zhong, P., Wang, D., Miao, C.: EEG-based emotion recognition using regularized graph neural networks. IEEE Trans. Affect. Comput. 13(3), 1290\u20131301 (2020)","journal-title":"IEEE Trans. Affect. Comput."},{"key":"230_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2025.113752","author":"Y Zhou","year":"2025","unstructured":"Zhou, Y., Zhang, X., Sun, Y., Chen, G., Huang, L., Li, H.: EEG emotion recognition based on dynamic temporal causal graph convolutional network. Knowl. Based Syst. (2025). https:\/\/doi.org\/10.1016\/j.knosys.2025.113752","journal-title":"Knowl. Based Syst."}],"container-title":["CCF Transactions on Pervasive Computing and Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42486-026-00230-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42486-026-00230-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42486-026-00230-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T05:47:33Z","timestamp":1787809653000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42486-026-00230-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,21]]},"references-count":56,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["230"],"URL":"https:\/\/doi.org\/10.1007\/s42486-026-00230-6","relation":{},"ISSN":["2524-521X","2524-5228"],"issn-type":[{"value":"2524-521X","type":"print"},{"value":"2524-5228","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,21]]},"assertion":[{"value":"21 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 February 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The author declares that there are no conflicts of interest related to this study.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}}]}}