Artificial Intelligence Guided Wearable Seizure Detection Device

Abstract

Epilepsy is a neurological condition that affects millions of individuals worldwide and is characterized by recurrent seizures. Seizure detection and classification are crucial for effective treatment and management of epilepsy. In this study, we present the development and evaluation of EpiPatch, a wearable AI device for seizure detection and classification in epilepsy patients. The EpiPatch incorporates motion sensors and biosensors to measure heart rate, blood pressure, and oxygen saturation, allowing for a comprehensive understanding of the patient’s condition during a seizure. Using machine learning algorithms, the EpiPatch is able to classify different types of seizures based on their unique motions, enabling more accurate and effective treatment. The results of our evaluations indicate high levels of accuracy in seizure detection and classification, with an overall accuracy rate of 80 percent. The proposed system has the potential to significantly improve the lives of individuals affected by epilepsy, and further research and development in this area is necessary to fully realize the potential of this technology.

Keywords: Epilepsy, Seizure Classification AI, Biosensors, Vital Signs Monitoring, Wearable Device