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Brain-computer interfaces (BCIs) have emerged as a transformative technology that enables direct communication between the brain and external devices. Despite significant progress, challenges persist in improving the quality and reliability of brain signal acquisition. This research paper proposes a comprehensive framework for enhancing brain signal acquisition in BCIs, combining advancements in signal processing techniques, electrode design, and neurofeedback mechanisms. The proposed approach aims to optimize signal-to-noise ratio, reduce artifacts, and enhance information transfer rates. Experimental results demonstrate promising improvements in BCI performance, providing a foundation for future advancements in neurotechnology.