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Artifacts Removal Schemes Using Wavelet Transforms in Brain Computer Interface

G. Saravana Kumar, S. Ravi

Abstract


In this work, a method to reduce electroencephalogram (EEG) artifacts from Visual-Evoked Potentials (VEP) in brain-computer interface (BCIs) design is presented. For the test composite signal the frequency ranges corresponding to stimulus-related VEP components were located using cyclo stationary (CS) analysis based algorithm.  The resulting cyclic frequency spectrum provides VEP frequency band detection.  Using this identified frequency ranges, low pass or band pass filtering is employed for EEG artifacts reduction.  The proposed Statistical Coefficient Selection (SCS) and wavelet-based method called Wavelet Denoising Algorithm (WDA) are used to distinguish VEP components and EEG artifacts. The proposed scheme exhibits satisfactory results with various datasets

Keywords


Brain Computer Interface (BCI), Statistical Coefficient Selection (SCS), Wavelet Denoising Algorithm, Visual Evoked Potential (VEP).

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References


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