Abstract
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.
Highlights
Epilepsy characterize a disorder of brain, which can occur to people with any age
One of the main symptoms of epilepsy is the occurrence of the epileptic seizure
The main issue while detecting the epilepsy with the help of EEG is that, the artifacts mix with the seizure signals and can appear as seizure which can result in the misdiagnosis in the level of the disease
Summary
One of the main symptoms of epilepsy is the occurrence of the epileptic seizure. Epilepsy can show symptoms through any neurological part of the body, but the mostly affected organ is the brain. The main issue while detecting the epilepsy with the help of EEG is that, the artifacts mix with the seizure signals and can appear as seizure which can result in the misdiagnosis in the level of the disease. These artifacts can be system generated as well as can be generated by the human body due to various factors such as blinking of eye, body movement,etc[1]. The purpose of this work is to remove artifacts effectively so as enhance the seizure detection due to epilepsy
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