<b>Authors - </b>Mahi Shah, Sachin Pande, Sumitra Jakhete, Emmanuel Mark<br /> <b>Abstract - </b>Brain-Computer Interfaces (BCIs) operate as systems that translate brain signals into digital commands. They provide a non-muscular channel of communication for individuals with profound motor disabili ties. Cerebral Palsy (CP) is a neurological condition that impairs move ment and muscle tone, frequently making physical or verbal expression difficult. This paper reviews the current state of BCI technology and, building upon these insights, introduces a framework for a non-invasive, low-cost BCI communication system tailored specifically for children with CP, addressing the limited accessibility of assistive communication technologies in low-resource environments. The proposed seven-stage framework targets these ongoing challenges by incorporating OpenBCI hardware, adaptive signal processing, and gamified interfaces. This processing pipeline converts neural signals into structured communication outputs, enhancing accessibility and engagement for CP children. To assess the feasibility of the proposed framework, an offline analysis was conducted using a publicly available EEG dataset. A Linear Discriminant Analysis (LDA) classifier y a classification accu racy of 62.5% and an Information Transfer Rate (ITR) of 11.4 bits/min, demonstrating the computational viability of the approach. The modular design offers scalability, though its efficacy requires further validation in real-world pediatric settings. In summary, this work bridges theoretical insights with practical innovation, offering a promising step toward empowering CP children. While limitations in real-world testing remain, the framework lays a foundation for future refinements. Successful implementation could significantly improve independence and quality of life, marking a milestone in inclusive assistive technology.
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