PERANCANGAN SISTEM INSTRUMENTASI BERBASIS INTERNET OF THINGS PADA ALAT PENDETEKSI BANGKITAN KEJANG PENGIDAP EPILEPSI

Abstract

Epilepsy is a disease caused by chronic neurological disorders which is characterized by recurrent seizures. Many studies have been conducted to try to cure the disease. In fact, medically, epilepsy cannot be cured, but the frequency of seizures can be reduced by taking medicines regularly. Medicines certainly contain chemicals that have negative side effects on the human body. A solution is needed to reduce the long-term effects caused by medicines that reduce the frequency of epileptic seizures. The research entitled "Designing Internet Of Things-Based Instrumentation System On Seizure Detection Equipment For People With Epilepsy" has the goal of developing a tool for detecting seizures in people with epilepsy that can be monitored remotely by the family. The tool is built using several main components, namely the EEG sensor system, Light Dependent Resistor (LDR) sensor, SW-520D sensor or tilt detector, and GPS Ublox Neo-6M. Experiments have been carried out for each component and the result is that the EEG sensor system after being amplified by 4213 times is 230 mV in relaxed conditions, 121 mV in listening to music, 83 mV in thinking conditions, and 72 mV in sports conditions. The LDR sensor as a light intensity detector has an accuracy rate of 71.12%, the SW-520D sensor or tilt detector as a patient fall detector has an accuracy of 96.7%, and the Ublox Neo-6M GPS as a location detector has an average difference in distance from Smartphone GPS of 2.90 meters.