Epileptic Seizure Feature Extraction using Variational Mode Decomposition
E. Swetha1, Shaik. Jakeer Hussain2

1E. Swetha, Vignan’s Foundation for Science, Technology & Research, Vadlamudi, Guntur (A.P), India.
2Dr. Shaik. Jakeer Hussain, Vignan’s Foundation for Science, Technology & Research, Vadlamudi, Guntur (A.P), India.
Manuscript received on 13 February 2019 | Revised Manuscript received on 04 March 2019 | Manuscript Published on 08 June 2019 | PP: 280-283 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E10570275S419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Signal processing for extracting the features of biosignals needs an adaptive processing techniques. Most of the biosignals such as EEG are non stationary signals. Therefore extracting the features of these non stationary signals are the challenges faced by the researchers. Many frequency domain techniques are proposed such as Hilbert transform, DWT, EMD. The most popular recent EMD technique is to achieve the accurate denoising & interpretation, but it fails to decompose the signal effectively and also due to lack of mathematical model or proof’s, choice of interpolation, and sensitivity to both sampling and noise. Hence the new emerging technique Variational mode decomposition (VMD) is used in this paper to extract the features of EEG signal. The advantage of using VMD, is lusty to sampling and noise.
Keywords: Epileptic Seizure, Electro Encephalogram(EEG), Variational Mode Decomposition(VMD).
Scope of the Article: Nano electronics and Quantum Computing