AI-Driven Eeg Signal Processing for Brain-Computer Interfaces

Authors

  • M. Subrahmanyeswara Rao, M. Navya, T. Rama Krishna, Navya Padma Priya

Keywords:

Intracortical Brain-Computer Interfaces (iBCIs), Advanced AI Agents, Neural Signal Interpretation, Hierarchical Planning, Reflective AI, Adaptive Learning, Multimodal Integration, Neurorehabilitation, Assistive Technologies, Signal Acquisition Techniques, Deep Learning, Reinforcement Learning, Prosthetic Limb Control, Brain-Machine Interaction

Abstract

Intracortical brain-computer interfaces (iBCIs), shown as Neuralink, have considerable promise for facilitating direct communication between the human brain and external equipment. The intricacy and elevated dimensionality of neural data provide obstacles in deciphering and converting brain activity into significant orders. This study offers a thorough examination of the existing status of iBCIs, including sophisticated signal collecting and decoding methodologies, while also addressing the constraints of conventional methods in facilitating seamless brain-machine interface. We suggest an innovative method that utilizes sophisticated AI agents, endowed with capacities such as reflection, hierarchical planning, and decision-making, as an interface between the brain and invasive brain-computer interfaces (iBCIs). By integrating these sophisticated AI methodologies, we want to augment the analysis of brain signals, optimize task execution efficiency, and provide a more intuitive and flexible user experience to get goal-oriented results from cognitive processes. The suggested methodology is examined comprehensively, emphasizing its prospective advantages and the obstacles that must be confronted. We conclude by delineating prospective research avenues and the potential for combining sophisticated AI agents with invasive Brain-Computer Interfaces (iBCIs) for diverse applications, including neurorehabilitation, assistive technologies, and human enhancement.

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References

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Published

05.05.2025

How to Cite

M. Subrahmanyeswara Rao. (2025). AI-Driven Eeg Signal Processing for Brain-Computer Interfaces. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 1066–1072. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7493

Issue

Vol. 11 No. 4 (2023)

Section

Research Article

License

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