Towards Accurate Seizure Detection: Machine Learning Model for Wearable Technology

Wearable devices that automatically detect and predict seizures could be life-changing technology for patients suffering from epileptic seizures. These devices can help in constant monitoring and detection of seizures. This research aims to produce a Machine Learning (ML)model to detect seizures which can be used in seizure detection wearable devices. With the help of multimodal sensors like Electrodermal Activity (EDA) and Accelerometer (ACC) accurate detection of seizure can be obtained. The system can analyse skin resistance and irregular heartbeats that could indicate an impending seizure. Overall, the research paper aims to demonstrate the potential of a machine learning model which can be used in wearable technology that can enhance seizure management and improve patient outcomes.