Denoising of EEG Gesture Using DWT
Jothimani.S1, Suganya.A2
1Jothimani. S, Assistant Professor, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur (Tamil Nadu), India.
2Suganya. A, Assistant Professor, Department of Electronicsa and Communication Engineering, M. Kumarasamy College of Engineering, Karur (Tamil Nadu), India.
Manuscript received on 27 April 2019 | Revised Manuscript received on 09 May 2019 | Manuscript Published on 17 May 2019 | PP: 522-527 | Volume-7 Issue-6S4 April 2019 | Retrieval Number: F11080476S419/2019©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: EEG signal is very complex and arbitrary in trendy environment. The Electroencephalography (EEG) signal is infected by the various noise sources, because of its lower amplitude. Similarly Electromyography (EMG), Electrocardiogram (ECG) signals have been contaminated by power line, baseline noises. The filter system recovers the infected noises. Filtering endure as of the considerable defeat the noise is not eliminated in EEG signal. So the signal has to remove these noises before treating the bloody signal. To propose an efficient demonizing algorithm DWT (Discrete Wavelet Transform) to de noising the EEG signal. In this paper introduce the dissimilar methods of discrete wavelet to analysis between the different patients. The analysis made by the well and epileptic patient that demonstrate the efficiency of sound exclusion.
Keywords: Artifacts, Power Line Noise, Baseline Noise, Discrete Wavelet Transform (DWT).
Scope of the Article: Waveform Optimization for Wireless Power Transfer