EZcap: A Novel Wearable for Real-Time Automated Seizure Detection From EEG Signals

Epileptic seizures present a serious danger to the lives of their victims, rendering them unconscious, lacking control, and may even result in death only few seconds after onset. This gives rise crucial need for an effective seizure detection method that is fast, accurate, has potential mass market adoption. Kriging methods have good reputation high accuracy spatial prediction, hence, extensive use geostatistics. paper demonstrates successful application device edge computing environment by modeling brain as panorama. We hereby propose novel wearable real-time automated from EEG signals using three different types Kriging, namely, Simple Ordinary Universal Kriging. After multiple experiments with electroencephalogram (EEG) obtained patients well those healthy counterparts, results reveal performed very accuracy, sensitivity latency detection. It was found however, outperforms other mean 0.81 sec, perfect specificity, 97.50% 94.74%. The this compare models literature but excellent surpasses performance most existing works