Abstract
Different studies have stated that electroencephalogram signals in Alzheimer’s disease patients usually have less synchronization as compare to healthy subjects. Changes in electroencephalogram signals start at early stage but clinically, these changes are not easily detected. To detect this perturbation, three neural synchrony measurement techniques have been examined with three different sets of data. This research work have successfully reported the experiment of comparing right and left temporal of brain with the rest of the brain area (frontal, central and occipital), as temporal regions are relatively the first ones to be affected by Alzheimer’s disease. A new approach using principal component analysis before applying neural synchrony measurement techniques has been presented and compared with to other existing techniques. The simulation results indicated that applying principal component analysis before synchrony measurement techniques show significantly improvement over the lateral one. The results of the experiments were analyzed using Mann-Whitney U test.
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Al-Jumeily, D., Iram, S., Hussain, A.J., Francois-Benois, V., Fergus, P. (2014). Early Detection Method of Alzheimer’s Disease Using EEG Signals. In: Huang, DS., Han, K., Gromiha, M. (eds) Intelligent Computing in Bioinformatics. ICIC 2014. Lecture Notes in Computer Science(), vol 8590. Springer, Cham. https://doi.org/10.1007/978-3-319-09330-7_4
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DOI: https://doi.org/10.1007/978-3-319-09330-7_4
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