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An effective method to remove noise in EEG signal using wavelet packet transform
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| Author:
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P. THAMARAI, K. ADALARASU
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| Abstract:
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Electroencephalogram (EEG) sign is the recording of impulsive electrical interest of the mind over a small period of time. Signals are made through attack of neurons in the brains that are measured and calculated through EEG. EEG indicators are low voltage indicators that are contaminated with the aid of various types of noises that are additionally known as artifacts. As these alerts are used to diagnose diverse varieties of mind related diseases like narcolepsy, Sleep apneasyndrome, Insomnia and parasomnia it will become necessary to make those indicators free from noise for correct evaluation and detection of the sicknesses. Various noise elimination strategies together with ICA -Independent Component Analysis, PCA -Principle Component Analysis, Wavelet packet transform and Wavelet Packet Transform are to be had and can be carried out in mat lab. All these strategies may be used for EEG signal de-noising through noise to the original sign and then put in force the noise reduction method and their overall performance can be evaluated based on the elements which includes SNR and MSE. In this article, an arithmetical method for putting off artifacts from EEG demos via wavelet packet transform without thinking about SNR calculation is proposed
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| Keyword:
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SNR calculation
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| EOI:
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| DOI:
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| Download:
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