Artifacts Removal of EEG Signals By the Application of ICA and Double Density DWT Algorithm

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Author(s)

Vandana Roy 1,* Shailja Shukla 2

1. Department of Electronics & Communication, Jabalpur Engineering College, Jabalpur, Madhya Pradesh, India

2. Department of Computer Science Engineering, Jabalpur Engineering College, Jabalpur, Madhya Pradesh, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijem.2014.02.04

Received: 15 May 2014 / Revised: 18 Jun. 2014 / Accepted: 24 Jul. 2014 / Published: 26 Aug. 2014

Index Terms

Artifacts, EEG Signals, Double Density, Wavelet Denoising

Abstract

Independent Component Analysis is used for the automation and detection of brain artifacts. The Independent Component Analysis (ICA) here is used for the segmentation of artifact peaks in the signal. Then the Discrete Wavelet Transform is applied for multi-level transfer of signal data until the reception of significant result. We have extended our search and applied the Double Density Algorithm for the multi-level transfer. The results obtained were analyzed from the data set of EEG signals taken with a outsource reference. Since the method is parameter free implementations in clinical settings are imaginable.

Cite This Paper

Vandana Roy, Shailja Shukla,"Artifacts Removal of EEG Signals By the Application of ICA and Double Density DWT Algorithm", IJEM, vol.4, no.2, pp.42-55, 2014. DOI: 10.5815/ijem.2014.02.04

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