Affiliations: [a] Department of Computer Science and IT, The University of Azad Jammu and Kashmir, City Campus, Muzaffarabad 13100, Pakistan | [b] College of Computer Sciences and Engineering, University of Jeddah, Jeddah 23890, Saudi Arabia
Correspondence:
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Corresponding author: Lal Hussain, Department of Computer Science and IT, University of Azad Jammu and Kashmir, City Campus, Muzaffarabad 13100, Pakistan. E-mails: lall_hussain2008@live.com, lal.hussain@ajku.edu.pk.
Abstract: BACKGROUND: Brain neural activity is measured using electroencephalography (EEG) recording from the scalp. The EEG motor/imagery tasks help disabled people to communicate with the external environment. OBJECTIVE: In this paper, robust multiscale sample entropy (MSE) and wavelet entropy measures are employed using topographic maps’ analysis and tabulated form to quantify the dynamics of EEG motor movements tasks with actual and imagery opening and closing of fist or feet movements. METHODS: To distinguish these conditions, we used the topographic maps which visually show the significance level of the brain regions and probes for dominant activities. The paired t-test and Posthoc Tukey test are used to find the significance levels. RESULTS: The topographic maps results obtained using MSE reveal that maximum electrodes show the significance in frontpolar, frontal, and few frontal and parietal brain regions at temporal scales 3, 4, 6 and 7. Moreover, it was also observed that the distribution of significance is from frontoparietal brain regions. Using wavelet entropy, the significant results are obtained at frontpolar, frontal, and few electrodes in right hemisphere. The highest significance is obtained at frontpolar electrodes followed by frontal and few central and parietal electrodes.
