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TEAM

CogniSafe: Empowering Athlete Well-being with EEG and Voice Data

B Mede, Fabian Lehmann, Nadun Kulasekera Mudiyanselage, Dylan Fillmore

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Diagnosing concussions continues to pose a significant challenge, resulting in delayed treatment and heightened long-term health risks. Conventional methods are often subjective, lacking real-time insights and exposing athletes to increased vulnerability. Leveraging EEG and voice data offers a non-invasive and efficient alternative, facilitating early identification, swift intervention, decreased risk of prolonged recovery, and potential mitigation of long-term consequences. Consequently, my objective is to develop a machine learning model for concussion detection, utilizing EEG or voice data.

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