[1] Maiseli, Baraka, Abdi T. Abdalla, Libe V. Massawe, Mercy Mbise, Khadija Mkocha, Nassor Ally Nassor, Moses Ismail, James Michael, and Samwel Kimambo. "Brain–computer interface: trend, challenges, and threats." Brain informatics 10, no. 1 (2023): 20.
[2] Saha, Simanto, Khondaker A. Mamun, Khawza Ahmed, Raqibul Mostafa, Ganesh R. Naik, Sam Darvishi, Ahsan H. Khandoker, and Mathias Baumert. "Progress in brain computer interface: Challenges and opportunities." Frontiers in systems neuroscience 15 (2021): 578875.
[3] Mishra, Shubhra, Osama Mahmudi, and Amin Jalali. "Motor imagery signal classification using adversarial learning: A systematic literature review." IEEE Access 12 (2024): 91053-91074.
[4] Xu, Fangzhou, Yitai Lou, Yunqing Deng, Zhixiao Lun, Pengcheng Zhao, Di Yan, Zhe Han et al. "Motor imagery EEG decoding based on TS-former for spinal cord injury patients." Brain Research Bulletin 224 (2025): 111298.
[5] Xu, Xiaoqi, Nicolas Drougard, and Raphaëlle N. Roy. "Does topological data analysis work for EEG-based brain–computer interfaces?." Journal of Neural Engineering 22, no. 3 (2025): 036026.
[6] Zhang, Jing, Xuxu Yang, Zilin Liang, Huanzhi Lou, Tong Cui, Cheng Shen, and Zhijun Gao. "A brain–computer interface system for lower-limb exoskeletons based on motor imagery and stacked ensemble approach." Review of Scientific Instruments 96, no. 1 (2025).
[7] Al-Saegh, Ali, Shefa A. Dawwd, and Jassim M. Abdul-Jabbar. "Deep learning for motor imagery EEG-based classification: A review." Biomedical Signal Processing and Control 63 (2021): 102172.
[8] Zarbafi, Sahar, Kourosh Kiani, and Razieh Rastgoo. "Spoken Persian digits recognition using deep learning." Journal of Modeling in Engineering 21, no. 74 (2023): 163-172.
[9] Anwar, Ayman, Yassin Khalifa, James L. Coyle, and Ervin Sejdic. "Transformers in biosignal analysis: A review." Information Fusion 114 (2025): 102697.
[10] Ali, Omair, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, and Christian Klaes. "ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data." Computers in Biology and Medicine 168 (2024): 107649.
[11] Vafaei, Elnaz, and Mohammad Hosseini. "Transformers in EEG Analysis: A review of architectures and applications in motor imagery, seizure, and emotion classification." Sensors 25, no. 5 (2025): 1293.
[12] Bagherzadeh, Fahimeh, and Razieh Rastgoo. "Deepfake image detection using a deep hybrid convolutional neural network." Journal of Modeling in Engineering 21, no. 75 (2023): 19-28.
[13] Rastgoo, Razieh, and Kourosh Kiani. "Face recognition using fine-tuning of Deep Convolutional Neural Network and transfer learning." Journal of Modeling in Engineering 17, no. 58 (2019): 103-111.
[14] Alinezhad, Fatemeh, Kourosh Kiani, and Razieh Rastgoo. "A Deep Learning-based Model for Gender Recognition in Mobile Devices." Journal of AI and Data Mining 11, no. 2 (2023): 229-236.
[15] Li, Duan, Keyun Li, Yongquan Xia, Jianhua Dong, and Ronglei Lu. "Joint hybrid recursive feature elimination based channel selection and ResGCN for cross session MI recognition." Scientific Reports 14, no. 1 (2024): 23549.
[16] Deng, Xin, Daijiang Xu, Huaxiang Huo, Xinyi Hong, and Bin Liu. "Multi-level hierarchical dynamic graph convolutional networks for motor imagery EEG analysis." Neurocomputing 626 (2025): 129594.
[17] Hamidi, Arezoo, and Kourosh Kiani. "Motor Imagery EEG signals classification using a Transformer-GCN approach." Applied Soft Computing 170 (2025): 112686.
[18] Shi, Ji, Jiaming Tang, Zhihuan Lu, Ruolin Zhang, Jun Yang, Qiuquan Guo, and Dongxing Zhang. "A brain topography graph embedded convolutional neural network for EEG-based motor imagery classification." Biomedical Signal Processing and Control 95 (2024): 106401.
[19] Wu, Yelan, Pugang Cao, Meng Xu, Yue Zhang, Xiaoqin Lian, and Chongchong Yu. "Adaptive GCN and Bi-GRU-Based Dual Branch for Motor Imagery EEG Decoding." Sensors 25, no. 4 (2025): 1147.
[20] Chen, Yuanling, Peisen Liu, and Duan Li. "MST-DGCN: A multi-scale spatio-temporal and dynamic graph convolution fusion network for electroencephalogram recognition of motor imagery." Electronics 13, no. 11 (2024): 2174.
[21] Kabir, Md Humaun, Shabbir Mahmood, Abdullah Al Shiam, Abu Saleh Musa Miah, Jungpil Shin, and Md Khademul Islam Molla. "Investigating feature selection techniques to enhance the performance of EEG-based motor imagery tasks classification." Mathematics 11, no. 8 (2023): 1921.
[22] Lin, Ruijing, Chaoyi Dong, Peng Zhou, Pengfei Ma, Shuang Ma, Xiaoyan Chen, and Huanzi Liu. "Motor imagery EEG task recognition using a nonlinear Granger causality feature extraction and an improved Salp swarm feature selection." Biomedical Signal Processing and Control 88 (2024): 105626.
[23] Fan, Chengcheng, Banghua Yang, Xiaoou Li, and Peng Zan. "Temporal-frequency-phase feature classification using 3D-convolutional neural networks for motor imagery and movement." Frontiers in Neuroscience 17 (2023): 1250991.
[24] Djamal, E. C., and R. D. Putra. "Brain–computer interface of focus and motor imagery using wavelet and recurrent neural networks." Telkomnika 18, no. 5 (2020): 2748–2756.
[25] Fahimi, Fatemeh, Strahinja Dosen, Kai Keng Ang, Natalie Mrachacz-Kersting, and Cuntai Guan. "Generative adversarial networks-based data augmentation for brain–computer interface." IEEE transactions on neural networks and learning systems 32, no. 9 (2020): 4039-4051.
[26] Lawhern, Vernon J., Amelia J. Solon, Nicholas R. Waytowich, Stephen M. Gordon, Chou P. Hung, and Brent J. Lance. "EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces." Journal of neural engineering 15, no. 5 (2018): 056013.
[27] Sharma, Neha, Avinash Upadhyay, Manoj Sharma, and Amit Singhal. "Deep temporal networks for EEG-based motor imagery recognition." Scientific Reports 13, no. 1 (2023): 18813
[28] Zhang, Dongxue, Huiying Li, and Jingmeng Xie. "MI-CAT: A transformer-based domain adaptation network for motor imagery classification." Neural Networks 165 (2023): 451-462.
[29] Huang, Yuxuan, Jianxu Zheng, Binxing Xu, Xuhang Li, Yu Liu, Zijian Wang, Hua Feng, and Shiqi Cao. "An improved model using convolutional sliding window-attention network for motor imagery EEG classification." Frontiers in Neuroscience 17 (2023): 1204385.
[30] Chowdhury, Radia Rayan, Yar Muhammad, and Usman Adeel. "Enhancing cross-subject motor imagery classification in EEG-based brain–computer interfaces by using multi-branch CNN." Sensors 23, no. 18 (2023): 7908.
[31] Xie, Jin, Jie Zhang, Jiayao Sun, Zheng Ma, Liuni Qin, Guanglin Li, Huihui Zhou, and Yang Zhan. "A transformer-based approach combining deep learning network and spatial-temporal information for raw EEG classification." IEEE Transactions on Neural Systems and Rehabilitation Engineering 30 (2022): 2126-2136.
[32] Zhang, Jiayang, Kang Li, Banghua Yang, and Zhengrun Zhao. "Cross-dataset motor imagery decoding—A transfer learning assisted graph convolutional network approach." Biomedical Signal Processing and Control 102 (2025): 107213.
[33] Shirodkar, Vaishali, Damodar Reddy Edla, and Annu Kumari. "Generative Adversarial Networks for Motor Imagery Classification using Wavelet Packet Decomposition and Complex Morlet Transform." Multimedia Tools and Applications (2025): 1-24.
[34] Esfandiari, Nura, Kourosh Kiani, and Razieh Rastgoo. "A conditional generative chatbot using transformer model." Journal of Modeling in Engineering 23, no. 82 (2025): 99–113.
[35] Esfandiari, Nura, Kourosh Kiani, and Razieh Rastgoo. "Transformer-based generative chatbot using reinforcement learning." Journal of AI and Data Mining 12, no. 3 (2025): 349–358.
[36] Ahmadi, Amir Mohammad, Kourosh Kiani, and Razieh Rastgoo. "A transformer-based model for abnormal activity recognition in video." Journal of Modeling in Engineering 22, no. 76 (2024): 213–221.
[37] Schalk, Gerwin, Dennis J. McFarland, Thilo Hinterberger, Niels Birbaumer, and Jonathan R. Wolpaw. "BCI2000: a general-purpose brain-computer interface (BCI) system." IEEE Transactions on biomedical engineering 51, no. 6 (2004): 1034-1043.
[38] Wang, Xiaying, Michael Hersche, Batuhan Tömekce, Burak Kaya, Michele Magno, and Luca Benini. "An accurate eegnet-based motor-imagery brain–computer interface for low-power edge computing." In 2020 IEEE international symposium on medical measurements and applications (MeMeA), pp. 1-6. IEEE, 2020.
[39] Moaveninejad, Sadaf, Valentina D'Onofrio, Franca Tecchio, Francesco Ferracuti, Sabrina Iarlori, Andrea Monteriù, and Camillo Porcaro. "Fractal Dimension as a discriminative feature for high accuracy classification in motor imagery EEG-based brain-computer interface." Computer Methods and Programs in Biomedicine 244 (2024): 107944.
[40] Xie, Xin, Feng Huang, Yefeng Long, Youyuan Peng, and Wenjuan Zhou. "An optimized informer model design for electric vehicle SOC prediction." PloS one 20, no. 3 (2025): e0314255.
[41] Esfandiari, Nura, Kourosh Kiani, and Razieh Rastgoo. "A conditional generative chatbot using transformer model." Neural Computing and Applications (2025): 1–32.
[42] Sun, Dan, Jacky He, Hanlu Zhang, Zhen Qi, Hongye Zheng, and Xiaokai Wang. "A LongFormer-Based Framework for Accurate and Efficient Medical Text Summarization." In 2025 8th International Conference on Advanced Algorithms and Control Engineering (ICAACE), pp. 1527-1531. IEEE, 2025.
)