Epilepsy is a chronic brain disorder that affects over fifty million people in the world. Severe epileptic seizures, which doctors do not notice to provide adequate emergency care, are one of the main causes of death among epilepsy patients. Seizure detection and prediction provide new and individually targeted opportunities for diagnosis and intervention in the management of epilepsy. These systems may allow for the detection of seizures prior to their clinical onset. Furthermore, these systems might be used in accidents. prevention and seizure tracking and could further be useful in closed loops to facilitate seizure abortion. Beyond their uses in immediate patient care, these systems may allow for increased granularity of neuroepidemiology data, thereby permitting improved seizure prediction and risk factor assessment. In this project, our objective is to implement IoT-based wearable device using machine learning. for epilepsy patients to predict the occurrence of an epileptic seizure long enough to help the patient and send notification through a mobile application.
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