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A novel approach for the elimination of artefacts from EEG signals employing an improved Artificial Immune System algorithm

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Electroencephalogram (EEG) is the recording of electrical activities of the brain. It is contaminated by other biological signals, such as cardiac signal (electrocardiogram), signals generated by eye movement/eye blinks (electrooculogram) and muscular artefact signal (electromyogram), called artefacts. Optimisation is an important tool for solving many real-world problems. In the proposed work, artefact removal, based on the adaptive neuro-fuzzy inference system (ANFIS) is employed, by optimising the parameters of ANFIS. Artificial Immune System (AIS) algorithm is used to optimise the parameters of ANFIS (ANFIS-AIS). Implementation results depict that ANFIS-AIS is effective in removing artefacts from EEG signal than ANFIS. Furthermore, in the proposed work, improved AIS (IAIS) is developed by including suitable selection processes in the AIS algorithm. The performance of the proposed method IAIS is compared with AIS and with genetic algorithm (GA). Measures such as signal-to-noise ratio, mean square error (MSE) value, correlation coefficient, power spectrum density plot and convergence time are used for analysing the performance of the proposed method. From the results, it is found that the IAIS algorithm converges faster than the AIS and performs better than the AIS and GA. Hence, IAIS tuned ANFIS (ANFIS-IAIS) is effective in removing artefacts from EEG signals.
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Keywords: Artificial Immune System; adaptive neuro-fuzzy inference system; electrocardiogram; electroencephalogram; electroocculogram; improved Artificial Immune System

Document Type: Research Article

Affiliations: 1: Department of Electronics and Communication Engineering, Regional Centre, Anna University, Tirunelveli Region, Tirunelveli, Tamil Nadu, India 2: Department of Electrical and Electronics Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India 3: Department of Electronics and Communication Engineering, Vins Christian College of Engineering, Nagercoil, Tamil Nadu, India

Publication date: March 3, 2016

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