Record Details

Robust Multichannel EEG Signals Compression Model based on Hybridization Technique

2018 International Conference on Pure and Applied Science

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Field Value
 
Title Robust Multichannel EEG Signals Compression Model based on Hybridization Technique
 
Creator Azmi Shawkat Abdulbaqi;

College of Computer and Information Technology, University of Anbar-IRAQ

ORCID : 0000-0002-9634-4160


Reyadh Hazim Mahdi; Dept. of Comp. Science, University of Mustanseryah, College of Science
Saif Al-din M. Najim;

College of Computer and Info.Tech, University of Anbar, IRAQ,


 
Subject
Artificial Neural Networks(ANN); Genetic Algorithm (GA); Multichannel Electroencephalogram (EEG); Principle Components Analysis (PCA),; Fast Fourier Transform (FFT); Telemonitoring
 
Description Abstract—Tele-monitoring of Electroencephalogram (EEG) via wireless is very critical as EEG. EEG medically is a tool test used to estimate the electrical activity of the brain. There are many channels through which EEG signals are recorded consistently and with high accuracy. So the size of these data is constantly increasing, need large storage area and a bandwidth for the transmission of the EEG signal remotely. In last decade, the EEG signal processing grew up, additionally, storing and transmitting  EEG signal data requirement is constantly increasing. This article includes the analysis method of an EEG compression and de-compression. This method is evaluated on the basis of various compression and parameters quality such as CR(compression ratio), SNR (Signal to noise ratio), PRD (percent-root-mean-square-difference), quality score (QS), etc.  The steps of EEG compression are pass through many stages: 1. Preprocessing and after that classification. 2. Linear transformation, and 3. Entropy coding. The EEG compression is specified during processing and coding algorithm for each of the steps. The decompression process is the reverse of the compression process, reconstructs the EEG original signals by using lossy algorithm but with the simple loss of significant information. The proposed compression method is a bright step in the compression field where getting a high compression ratio.
 
Publisher Pure and Applied Science
 
Contributor
 
Date 2018-03-27 21:54:15
 
Type Peer-reviewed Paper
 
Identifier http://conferences.koyauniversity.org/index.php/pas/2018/paper/view/16
 
Source Pure and Applied Science; 2018 International Conference on Pure and Applied Science
 
Language en
 
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