Brain-computer interface (BCI) character input system combining eye-tracking and motor imagery. Addressing the problems of low speed, high false triggering, significant fatigue, and large individual variability inherent in traditional single-paradigm BCIs for character input tasks, a three-level collaborative architecture of "eye-tracking coarse screening—motor imagery active confirmation—language model error correction enhancement" is proposed. The paper systematically reviews the development of non-invasive BCI spelling systems, the research progress of eye-tracking and hybrid interaction, and the latest trends in combining eye-tracking with character input tasks. Based on this, the key bottlenecks faced by the hybrid system are analyzed, including unstable eye-tracking localization, fluctuating motor imagery signals, multimodal temporal asynchrony, and insufficient efficiency of the complete input link. A unified modeling and fusion strategy is presented. Research shows that eye-tracking is suitable for rapid spatial localization, motor imagery is suitable for active confirmation, and language models can effectively improve error correction and associative input capabilities. Combined with publicly available research data, this type of system demonstrates high application value in terms of accuracy, throughput, and communication assistance potential. This article argues that future efforts should focus on improving synchronization accuracy, adaptive decoding, and closed-loop interaction design to advance hybrid brain-computer interface character input systems from experimental prototypes to practical applications.

Jun Ye, A Hybrid Brain Computer Interface Character Input System Combining Eye Tracking and Motor Imagery. International Journal of Neural Network (2026), Vol. 5, Issue 1: 71-78. https://doi.org/10.38007/NN.2026.050108.

[1] Liu, X., & Yang, D. (2025, March). LLM Data Strategy: Improving Data Availability and Efficiency. In Doctoral Symposium on Computational Intelligence (pp. 425-437). Singapore: Springer Nature Singapore.

[2] Yin, J. (2026, March). An Efficient Iterative Algorithm for Calibrating Agency MBS Estimation Parameters Based on Bayesian Optimization, Implemented in Python. In 2026 IEEE Madhya Pradesh Section Conference (MPCON) (pp. 1462-1467). IEEE.

[3] Zheng, H. (2026, April). Research on Cloud-Edge Collaborative Elastic Computing and Cost Optimization for High-Concurrency Scenarios. In 2026 IEEE 15th International Conference on Communication Systems and Network Technologies (CSNT) (pp. 1489-1496). IEEE.

[4] Liu, H. (2025, December). Mlops Model Deployment System for Multi-Cloud Environments and Improvement of Commercial AI Service Availability. In 2025 IEEE International Conference on Communication Networks and Computing (CNC) (pp. 1047-1052). IEEE.

[5] Hong, Y. (2025, December). Chain Demand Mutation Identification and Emergency Response Decision-Making Integrated With Social Media Sentiment Analysis. In 2025 IEEE International Conference on Communication Networks and Computing (CNC) (pp. 425-432). IEEE.

[6] Chen, M. (2026, March). Design of a Privacy-Oriented AI Compliance Hook System Based on Static Code Analysis. In 2026 IEEE Madhya Pradesh Section Conference (MPCON) (pp. 648-654). IEEE.

[7] Lyu, N. (2026, April). Toward Robust AI Agents: A Closed-Loop Task Planning–Execution–Feedback Framework for Open Scenarios. In 2026 IEEE 15th International Conference on Communication Systems and Network Technologies (CSNT) (pp. 1182-1188). IEEE.

[8] Zhang, K. (2025, December). Research on Cross-Selling Precision Marketing Strategy Based On Xgboost Model and SHAP Explanatory Framework. In 2025 IEEE 1st International Conference on Recent Trends in Computing and Smart Mobility (RCSM) (pp. 1-7). IEEE.

[9] Zhu, P. (2025, December). Construction of Multi-Scale Biostatistical Analysis Framework and its Application in Biomedical Signal Feature Recognition and Classification. In 2025 5th International Conference on Mobile Networks and Wireless Communications (ICMNWC) (pp. 1-7). IEEE.

[10] Zhang, C., Han, J., Zou, Y., Dong, K., Li, Y., Ding, J., & Han, X. (2024, April). Detecting the anomalies in LiDAR pointcloud. In WCX SAE World Congress Experience. SAE Technical Paper.

[11] Wu, W. (2025, June). Construction and optimization of intelligent gateway software management platform based on jenkins cluster management under cloud edge integration architecture in industrial internet of things. In International Conference on 6G Communications Networking and Signal Processing (pp. 633-645). Singapore: Springer Nature Singapore.

[12] Pan, H. (2025, March). Research on Efficient Computing Model of Hartree Fock and Density Functional Theory Based on GPU Acceleration. In Doctoral Symposium on Computational Intelligence (pp. 485-496). Singapore: Springer Nature Singapore.

[13] Yiting Hong. Differentially Private High-Dimensional Business Data Publishing and Analysis Algorithm. International Journal of Business Management and Economics and Trade (2026), Vol. 7, Issue 1: 28-35.

[14] Wu, Y. (2025, October). Multi-Level Belief Rule Base Modeling Architecture and Intelligent Optimization Technology for Decision Support Systems. In 2025 2nd International Conference on Software, Systems and Information Technology (SSITCON) (pp. 1-8). IEEE.

[15] Zhang, Q. (2025, October). Application of Reinforcement Learning in Dynamic Advertising Content Generation. In 2025 2nd International Conference on Software, Systems and Information Technology (SSITCON) (pp. 1-5). IEEE.

[16] Zhang, Q. (2025, July). Research on Improving the Effectiveness of Programmatic Advertising Using Multi-armed Bandit Algorithms. In International Conference on Frontier Computing (pp. 543-552). Singapore: Springer Nature Singapore.

[17] Wang, Z. (2026). Exploration of the Application of Resource Circular Economy in the Agricultural Industry Chain.

[18] Wang, Y. (2025, December). Construction of an Intelligent Recommendation System for Personalized Training Plans for Sports Rehabilitation Patients Based on Graph Neural Networks. In 2025 IEEE 1st International Conference on Recent Trends in Computing and Smart Mobility (RCSM) (pp. 1-6). IEEE.