Denoising of EEG Signal Using FrFT based Barlett Window

Volume 5 Issue 1 January - March 2017

Research Paper

Denoising of EEG Signal Using FrFT based Barlett Window

Jayalaxmi Anem*, G. Sateesh Kumar**

* Senior Assistant Professor, Department of Electronics and Communication Engineering, Aditya Institute of Technology and Management, Andhra Pradesh, India.

** Professor & Head, Department of Electronics and Communication Engineering, Aditya Institute of Technology and Management, Andhra Pradesh, India.

Anem, J., Kumar, S. G. (2017). Denoising of EEG Signal Using FrFT based Barlett Window. i-manager’s Journal on Digital Signal Processing, 5(1), 18-23. https://doi.org/10.26634/jdp.5.1.13528

Abstract

Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical activity of the brain. EEG recording is highly susceptible to various forms and sources of noise, which present significant difficulties and challenges in analysis and interpretation of EEG data. Noise sources may consist of power line interference, base line noise, random body movements or respiration. A number of strategies are available to deal with noise effectively both at the time of EEG recording as well as during pre-processing of recorded data [8]. In this work, the authors have proposed FrFT based Barlett window to enhance the quality of EEG signal and the fidelity parameters like Signal to Noise Ratio (SNR), MSE, LSE, and sensitivity have to be computed and analyzed in a Matlab environment.