This project focuses on using wearable biosignals (ACC, BVP, EDA, TEMP) for seizure detection in epilepsy patients. It applies MiniROCKET for feature extraction and XGBoost for classification, addressing imbalanced data and real-time monitoring challenges, aiming to enhance seizure detection accuracy and patient care.
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This project focuses on using wearable biosignals (ACC, BVP, EDA, TEMP) for seizure detection in epilepsy patients. It applies MiniROCKET for feature extraction and XGBoost for classification, addressing imbalanced data and real-time monitoring challenges, aiming to enhance seizure detection accuracy and patient care.
az899/seizure_detection-
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This project focuses on using wearable biosignals (ACC, BVP, EDA, TEMP) for seizure detection in epilepsy patients. It applies MiniROCKET for feature extraction and XGBoost for classification, addressing imbalanced data and real-time monitoring challenges, aiming to enhance seizure detection accuracy and patient care.
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