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Power-Saving Approach to Seizure Prediction Using Trigger Algorithms

This study explores innovative trigger algorithms aimed at enhancing the prediction of seizures while minimizing power consumption. Led by mentor Keun Soo Yim and mentees Le Xu and Le Wang, the research focuses on developing effective computational strategies that can be integrated into wearable devices for real-time monitoring and prediction. The proposed methods prioritize efficiency without compromising the accuracy of seizure detection, ultimately contributing to better management of seizure disorders and improving the quality of life for those affected.

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Power-Saving Approach to Seizure Prediction Using Trigger Algorithms

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  1. Trigger Algorithm 1 Trigger Algorithm 2 A Power-Saving Approach of Seizure PredictionMentor: KeunSooYim Mentee: Le Xu, Le Wang

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