曾虹

• • Early diagnosis of cognitive dysfunction in the elderly, with a gender dimension,2024-03-07,2021-07-01,在研,国家科技支撑计划,计算机学院（软件学院）,计算机科学技术,50

  • 脑机协同智能省重点实验室运行经费,2021-09-09,在研,其他课题,计算机学院（软件学院）,计算机科学技术,20

  • 面向情感识别的关键脑电节律与脑区发掘方法研究,2020-07-17,结题,自选课题（校内项目）,计算机学院（软件学院）,计算机科学技术,20

  • 掌上社工最优路径推荐算法研究，2022-01-18，结题，计算机学院（软件学院），计算机科学与技术，5

  • 基于AI的敏感数据识别算法模型设计,2024-10,在研，计算机学院（软件学院），计算机科学与技术，20

  
  

[1] Zeng, H., Xia, N., Tao, M., Pan, D., Zheng, H., Wang, C., ... & Dai, G. (2023). DCAE: A dual conditional autoencoder framework for the reconstruction from EEG into image. Biomedical Signal Processing and Control, 81, 104440.

[2] Zeng, H., Wu, Q., Jin, Y., Zheng, H., Li, M., Zhao, Y., ... & Kong, W. (2022). Siam-GCAN: a Siamese Graph Convolutional Attention Network for EEG Emotion Recognition. IEEE Transactions on Instrumentation and Measurement.

[3] Zeng, H., & Zakaria, W. (2022). A new common spatial pattern-based unified channels algorithm for driver’s fatigue EEG signals classification. Neural Computing and Applications, 1-23.

[4] Zeng, H., Fang, X., Zhao, Y., Wu, J., Li, M., Zheng, H., ... & Dai, G. (2022). EMCI: A Novel EEG-Based Mental Workload Assessment Index of Mild Cognitive Impairment. IEEE Transactions on Biomedical Circuits and Systems.

[5] Zhao, Y., Dai, G., Fang, X., Wu, Z., Xia, N., Jin, Y., & Zeng, H. (2022). E3GCAPS: Efficient EEG-based multi-capsule framework with dynamic attention for cross-subject cognitive state detection. China Communications, 19(2), 73-89.

[6] Zeng, H., Jin, Y., Wu, Q., Pan, D., Xu, F., Zhao, Y., ... & Kong, W. (2022). EEG-FCV: An EEG-Based Functional Connectivity Visualization Framework for Cognitive State Evaluation. Frontiers in Psychiatry, 13.

[7] Di Flumeri, G., Ronca, V., Giorgi, A., Vozzi, A., Aricò, P., Sciaraffa, N., ... & Borghini, G. (2022). EEG-Based Index for Timely Detecting User’s Drowsiness Occurrence in Automotive Applications. Frontiers in Human Neuroscience, 16.

[8] Zhao, Y., Dai, G., Borghini, G., Zhang, J., Li, X., Zhang, Z., ... & Zeng, H.（Corresponding Author） (2021). Label-Based Alignment Multi-Source Domain Adaptation for Cross-Subject EEG Fatigue Mental State Evaluation. Frontiers in Human Neuroscience, 546.

[9] Zeng, H., Li X, Borghini G, et al. An EEG-Based Transfer Learning Method for Cross-Subject Fatigue Mental State Prediction[J]. Sensors, 2021, 21(7): 2369.

[10] Zeng, H., Zhang, J., Zakaria, W., Babiloni, F., Gianluca, B., Li, X., & Kong, W. (2020). InstanceEasyTL: An Improved Transfer-Learning Method for EEG-Based Cross-Subject Fatigue Detection. Sensors, 20(24), 7251.

[11] Shen, F., Dai, G., Lin, G., Zhang, J., Kong, W., & Zeng, H. (Corresponding author) (2020). EEG-based emotion recognition using 4D convolutional recurrent neural network. Cognitive Neurodynamics, 1-14. 

[12] Jing, X., Zeng, H., Wang, S., & Xu, J. (2020) (Joint first author). A Web-Based Protocol for Interprotein Contact Prediction by Deep Learning. In Protein-Protein Interaction Networks (pp. 67-80). Humana, New York, NY. (2020)

[13] Zhenhua Wu, Hong Zeng, Yue Zhao, Xiufeng Li, Jiaming Zhang, and Motonobu Hattori, Cross-subject EEG Channel Optimization by Domain Adversarial Sparse Learning Model, in Proceeding on BIBM'2020 

[14] Hong Zeng, Jiaming Zhang, Wael Zakaria, Fabio Babiloni *, Gianluca Borghini, Xiufeng Li, Wanzeng Kong, InstanceEasyTL: An Improved Transfer Learning Method for EEG-based Cross-subject Fatigue Detection, Sensors, 2020 

[15] Zeng, H., Wu, Z., Zhang, J., Yang, C., Zhang, H., Dai, G., & Kong, W. (2019). EEG Emotion Classification Using an Improved SincNet-Based Deep Learning Model. Brain sciences, 9(11), 326. 

[16] Zeng, H., Yang, C., Zhang, H., Wu, Z., Zhang, J., Dai, G., ... & Kong, W. (2019). A lightGBM-based EEG ****ysis method for driver mental states classification. Computational intelligence and neuroscience, 2019.

[17] Kong, W., Fu, S., Deng, B., Zeng, H., Zhang, J., & Guo, S. (2019). Embedded BCI Rehabilitation System for Stroke. Journal of Beijing Institute of Technology, (1), 5.

[18] Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo. A web server for inter-protein contact prediction using deep learning[J]，Nucleic Acids Research

[19] Zeng H, Yang C, Dai G, et al. EEG Classification of driver mental states by deep learning[J]. Cognitive Neurodynamics. 

[20] Zeng, Hong, Dai Guojun, Kong Wanzeng, et al (2017). A Novel Nonlinear Dynamic Method for Stroke Rehabilitation Effect Evaluation using EEG[J]. IEEE Transactions on Neural Systems & Rehabilitation Engineering

[21] Kong W, Guo S, Long Y, Zeng H, et al (2018). Weighted extreme learning machine for P300 detection with application to brain computer interface[J]. Journal of Ambient Intelligence & Humanized Computing

[22] Lei X, Wang L, Kong W, Zeng H, et al (2017). Identification of EEG features in stroke patients based on common spatial pattern and sparse representation classification[C]// International IEEE/EMBS Conference on Neural Engineering. IEEE.

[23] Hong Zeng, Yidan Hu, Jin Fan, Haiyang Hu, Zhigang Gao, and Qiming Fang (2016). Arm motion recognition and exercise coaching system for remote interaction[J], Mobile Information Systems.

[24] Hong Zeng, Jianhui Zhang, Guojun Dai, Zhigang Gao, and Haiyang Hu (2014). Security Visiting: RFID-based smartphone indoor guiding system[J], International Journal of Distributed Sensor Networks.

[25] Hong Zeng, Jianhui Zhang, and Guojun Dai (2013). Construction of low weighted and fault-tolerant topology for wireless ad hoc and sensor network[J], International Journal of Sensor Network.

[26] Zhao Y, Zeng H(*), Zheng H, et al (2023). A bidirectional interaction-based hybrid network architecture for EEG cognitive recognition[J]. Computer Methods and Programs in Biomedicine, 238: 107593. 

[27] Hong Zeng, Nianzhang Xia, Dongguan Qian, Motonobu Hattori, Chu Wang and Wanzeng Kong (2023). DM-RE2I: A framework based on Diffusion Model for the Reconstruction from EEG to Image, Biomedical Signal Processing and Control.

[28] Pan, D., Zheng, H., Xu, F., Ouyang, Y., Jia, Z., Wang, C., & Zeng H, (2023). MSFR-GCN: A Multi-scale Feature Reconstruction Graph Convolutional Network for EEG Emotion and Cognition Recognition. IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[29] Xu, F., Pan, D., Zheng, H., Ouyang, Y., Jia, Z., & Zeng, H*. (2024). EESCN: A Novel Spiking Neural Network Method for EEG-based Emotion Recognition. Computer Methods and Programs in Biomedicine, 107927.

[30] Wang, Z., Ouyang, Y., & Zeng, H. (2024). ARFN: An Attention-Based Recurrent Fuzzy Network for EEG Mental Workload Assessment. IEEE Transactions on Instrumentation and Measurement.

[31]  Qian, D., Zeng, H., Cheng, W., Liu, Y., Bikki, T., & Pan, J. (2024). NeuroDM: Decoding and visualizing human brain activity with EEG-guided diffusion model. Computer Methods and Programs in Biomedicine, 108213.

[32]  H Zeng, Y Zhao, F Babiloni, M Tao, W Kong, G Dai (2024). A General DNA-like Hybrid Symbiosis Framework: An EEG Cognitive Recognition Method, IEEE Journal of Biomedical and Health Informatics

[33] Ouyang, Y., Liu, Y., Shan, L., Jia, Z., Qian, D., Zeng, T., & Zeng, H*. (2025). DAEEGViT: A domain adaptive vision transformer framework for EEG cognitive state identification. Biomedical Signal Processing and Control, 100, 107019.