IoT-Based Monitoring System for Detection of Epileptic Seizure by Heart Rate Variation

Abstract

Heart rate variability (HRV) is highly identified in seizures, it reflects autonomous nervous system disturbance and it can provide useful clinical information that can be used for seizure detection. For decades, Electroencephalography (EEG) was the first device used to monitor brain signals and seizures. However, using EEG is not practical cause it requires to attach electrodes to the head scalp and it takes time to get results and it usually used during or after seizures occurred. To avoid EEG problems we need a detection system that can provide understandable data, easy to be used and capable of early intervention so the patient have the chance to prevent seizures and its related side effects. In this study, we plan to design epileptic seizure detection system by the heart rate monitoring with the internet of things (IoT) based. The sensor used is a pulse sensor, it is used as a heart rate detector processed by NodeMCU, the test results and measurements will be real-Time displayed on LCD and transmitted to ThingSpeak platform which it will be accessible to doctors, family members to follow the patient status.