Methods of denoising of electroencephalogram signal: a review

Sheoran, Monika and Kumar, Sanjeev and Chawla, Seema (2015) Methods of denoising of electroencephalogram signal: a review. International Journal of Biomedical Engineering and Technology, 18 (4). pp. 83-86. ISSN Online: 1752-6426, Print: 1752-6418

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Electroencephalogram (EEG) is obtained as a result of electrical activity of neurons in the brain. These signals have very small amplitudes and hence are quite prone to contamination by different artefacts. The major types of artefacts that affect the EEG are baseline wandering, power line noise, eye movements, Electromyogram (EMG) disturbance, and Electrocardiogram (ECG) disturbance. The presence of artefacts makes the analysis of EEG difficult for clinical evaluation and information. To deal with these artefacts, numerous methods and techniques have been evolved by different researchers. These methods include regression, blind source separation, wavelet and empirical mode decomposition etc. This paper provides a review of these methods for denoising of EEG signal.

Item Type: Article
Uncontrolled Keywords: signal denoising, electroencephalograms, EEG signals, blind source separation, BSS, PCA, principal component analysis, ICA, independent component analysis, regression, wavelets, empirical mode decomposition, EMD
Subjects: CSIO > Medical Instrumentation
Divisions: Medical Instrumentation
Depositing User: Ms. Jyotsana
Date Deposited: 09 Aug 2018 11:56
Last Modified: 09 Aug 2018 11:56

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