Noise Removal of EEG Signal Using Wavelet Transform

Noise Removal of EEG Signal Using Wavelet Transform
Author(s):
Priyanka Dhaka, Shivani Saxena
Keywords:
Electroencephalography, Wavelet Transform, Standard Deviation, Mean Square Error, Alpha-Beta-Gamma-Theta-Delta EEG waves.
Abstract
Electroencephalography (EEG) is a method to record an electrogram of the spontaneous electrical activity of the brain. As the electrical activity monitored by EEG originates in neurons (brain tissue), the recordings made by the electrodes on the surface of the scalp vary in accordance with their orientation and distance to the source of the activity. Furthermore, to remove the noises(artifacts) from the EEG signal the denoising techniques must be taken in application. In this paper, the discrete wavelet transform (DWT) noise removal technique is presented for denoising of noisy EEG signal which is further used to extract significant features from synthesized signal. Numerical Simulation of Statistical parameters have been performed to validate the accuracy of proposed method
Article Details
Unique Paper ID: 159287 Publication Volume & Issue: Volume 9, Issue 11 Page(s): 831 - 837
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