Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
The brain is the main control of the body and any disorder that occurs in the brain affects the body’s vital activity. There are many diseases that infect the brain and effect on brain functions and which affects many people around the world. Brain signals extracted by EEG system are used to diagnose brain signals and classify them as normal or abnormal. The process of detecting and classifying EEG signals are difficult and exhausting process and require effort by the specialist doctor to diagnose them. Brain injury treatment is complicated and require surgical intervention when the injury is severe but when early detection of injury may be treated without surgical intervention. This study will use the EEG signals that have been collected as images. Then these signals will be extracted from these images. At the beginning the background will be removed by thresholding and then extracting the signals by tracking each signal. These signals are then analyzed using DWT for features extraction and using ANN for classification.
How to cite this article:
Muzhir Shaban Al-Ani and Ahmed Mohammed Abed. Design and Implementation of Brain Signal Detection and Analysis Approach.
DOI: https://doi.org/10.36478/jeasci.2018.1262.1270
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.1262.1270