EPILEPSY SEIZURE DETECTION USING WEARABLE MEMS DEVICES

Abstract

Epilepsy is one of the most common neurological disorders, and it affects almost 1% of the population worldwide. It is a brain disorder affecting people of all ages mainly seen in many developing countries. Till date many sufferers do not get proper diagnosis and treatment for the same because of its unpredictability. People with epilepsy and their families suffers from stigma Seizure disorder would not be nearly so distressful if the time of seizure occurrence were predictable. Unpredicted and unattended seizures can have life threatening complications. In this paper, we present a preclinical demonstrator for real-time detection of seizures based wearable MEMS devices. Here we used accelerometer in this project which is attached on the hand of the patient. The accelerometers are Micro-Electro-Mechanical Sensors (MEMS). If the person suddenly suffered by epilepsy seizure, the movement of the hand reaction will accelerate the accelerometer which generates signal to the microcontroller. The microcontroller triggers the buzzer through driver to alert the neighbours. Moreover, that the microcontroller generate signal to the GSM Modem. The GSM modem will send SMS notification to the relative’s mobile of the patient. So the doctor has to give additional treatment to the patient. Suppose the patient used their hand for general purpose the alarm will be ON and send SMS to their relatives by using this system. To avoid this problem, the performance of wearable MEMS devices, based on the patient’s motion will be calculated in normal and abnormal condition. However, the programmable language will be used to compare the values from normal and abnormal range while receiving signal from accelerometer. Experimental results show the real impact of our proposed system to address the seizure detection.

Existing System

Proposed System

Architecture

BLOCK DIAGRAM