scholarly journals FPGA Based Architecture Implementation for Epileptic Seizure Detection Using One Way ANOVA and Genetic Algorithm.

2019 ◽  
Vol 12 (3) ◽  
pp. 1543-1553 ◽  
Author(s):  
Varsha Harpale ◽  
Vinayak Bairagi

Epilepsy is a brain disorder which produces recurrent seizures as a storm of the electrical activity of the brain. 70 millions of people living with epilepsy in the world and most of them are from developing countries and near about 12 millions of people are residing from India. In rural areas, seizure disorder is not treated seriously so there is a need for awareness and availability of proper medication. Recurring seizures are the major source of diagnosis of epilepsy so real-time prediction using analytical methods is a need of the research in this area. Electroencephalographic (EEG) signals are the rich source of the early diagnosis of epilepsy. The basic objective of the work is to proposed real time architecture which could be included in existing EEG monitoring and measuring instruments to mark the seizure occurrence. This will facilitate medical practitioners monitoring primary status of patients and understanding frequency of seizure occurrence. Thus the proposed work provide real-time architecture or improved performance reconfigurable solution to contribute in designing real-time seizure detection system. The EEG processing architecture is designed and implemented in this work, which will add values to the existing EEG monitoring and recording system.

2010 ◽  
Vol 46 (6) ◽  
pp. 922-935 ◽  
Author(s):  
Deng-Shan Shiau ◽  
J. J. Halford ◽  
K. M. Kelly ◽  
R. T. Kern ◽  
M. Inman ◽  
...  

Author(s):  
N. Shawki ◽  
T. Elseify ◽  
T. Cap ◽  
V. Shah ◽  
I. Obeid ◽  
...  

2020 ◽  
Vol 32 ◽  
pp. 02008
Author(s):  
Meenal Vijay Kakade ◽  
Chandrakant J. Gaikwad ◽  
Vijay R. Dahake

The use of computer aided diagnosis systems for disease identifiscation, based on signal processing, image processing and video processing terminologies is common due to emerging technologies in medical field. The detection of epilepsy seizures using EEG recordings is done by different signal processing techniques. To reduce the disability caused by the uncertainty of the occurrence of seizures, a recording system which shall result accurate and early detection of seizure with quick warning is greatly desired. To optimize the performance of EEG based epilepsy seizures detection, in this work we are presenting a method based on two key algorithms. Here, we propose unique algorithm based on SWT (Stationary Wavelet Transform), for easier seizure analysis process, along with improved performance of the application of seizure detection algorithms. Then, we propose the algorithm for feature extraction that makes use of Higher Order Statistics of the coefficients that are calculated using Wavelet Packet Decomposition (WPD).This helps in improving the epilepsy seizures detection performance. The proposed methods helps to improve the overall efficiency and robustness of EEG based epilepsy seizures detection system.


Sign in / Sign up

Export Citation Format

Share Document