Reduction of Ocular Artifacts in Single Channel EEG by EEMD-IMF Thresholding

Abstract

Abstract

Electroencephalogram (EEG) is a widely used signal for analyzing the activities of the brain and usually contaminated with artifacts due to the movements of eye, heart, muscles and power line interference. Among these ocular activities creates significant artifacts and makes the analysis difficult. In this paper, ensemble empirical mode decomposition (EEMD) inspired by wavelet thresholding is used for the correction of ocular artifacts (OA) in EEG signals. Unlike the conventional EEMD based EEG denoising techniques, which neglects the noisy intrinsic mode functions (IMFs), IMF interval thresholding is opted to correct the artifacts that yield a relatively clean EEG signal. Extensive computations are carried out using EEG motor movement/imagery (EEGMM-IDB) dataset and compared the efficacy of the proposed method with EMD-IT method of artifact correction using several standard performance metrics: change in SNR (ΔSNR), artifact rejection ratio (ARR), correlation coefficient (CC), and root mean square error (RMSE). Results of this study reveal that EEMD-IT+PT is efficient in eliminating the OAs and to maintain the neural activity in non-artifact zones.

Keywords: EEG, ocular artifacts, EMD, EEMD, thresholding

Cite this Article

Vijayasankar Anumala, Rajeshkumar Pullakura. Reduction of Ocular Artifacts in Single Channel EEG by EEMD-IMF Thresholding. Recent Trends in Electronics & Communication Systems. 2018; 5(1):
17–25p.