VPSI 2.0: IoT-Based Hybrid Protocol With Simultaneous Equations for Real-Time Seizure Classification and False-Negative Mitigation

Nonepileptic seizures are a clinical symptom of abnormally high synchronous cortical activity known as psychogenic nonepileptic seizures (PNESs) as they exhibit no outward signs of neurological damage. The need for differentiating PNES from full-body general seizures (GTCSs) decreases therapy time and ensures proper hospice. Internet of Medical Things (IoMT) provide a closed-loop mechanism to accurately measure seizures. The erratic nature of seizures has drawn the attention where false detection could have catastrophic impact. This article discusses the vibration profile seizure identifier (VPSI) 2.0 where vibration profile analysis of an ictal patient is measured in real-time to classify seizures in an IoMT framework. The novel seizure detection model has been proposed for differentiating between multiple seizure types. The simultaneous equation (S.E) protocol is developed for noninvasive stigma-free monitoring of seizures for continual monitoring. S.E-based Internet of Things (IoT) seizure classifier is helpful to mitigate challenges present in detecting real-time occurrences of seizure by 95.683% in a controlled environment.