Comparison of Epileptic Seizure Detection using Auto-Regressive Model and Linear Prediction Model?Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 5)
Publication Date: 2014-05-30
Authors : Priyanka Jain; Pradeep Kumar Govindaiah;
Page : 263-267
Keywords : EEG; Artifacts; Electrical Activity; SWT; Adaptive Filtering; Pre-Ictal; Ictal;
Artifacts causes the incorrect reading of Electroencephalography (EEG) Signal. Specific filtering technique is to be followed to remove the artifacts. In this paper, combination of Adaptive Filtering (AF) and Stationary Wavelet Transform (SWT) is proposed to remove artifacts from the EEG signal. EEG Signals from a healthy subject and from an Epileptic subject are compared using the Autoregressive Model and Linear Prediction Model. These models does not account for the presence of noise. The dominant pole (closest to the unit circle in the z-plane) of Linear Prediction Model shows better result as compared to the dominant pole of Autoregressive Model.
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Last modified: 2014-05-16 20:42:25