EEG-Based Control System for Maze Object Navigation
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In this project, we developed a main program that enables control of object movement within a maze through electroencephalogram (EEG) signal analysis. The maze design was implemented using MATLAB to ensure geometric complexity and structural integrity. Our approach incorporates advanced signal processing algorithms to identify specific EEG patterns, which are then translated into movement commands through a classification system. The implementation involves key MATLAB functions for real-time signal filtering, feature extraction using Fast Fourier Transform (FFT), and pattern recognition through machine learning classifiers. This integration allows for precise directional control of objects within the maze environment. The project aims to explore brain-computer interface applications in gaming design and establishes a foundation for future research in neural-controlled interactive systems.
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