Home // BIOTECHNO 2019, The Eleventh International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies // View article
Authors:
Apostolos C. Tsolakis
Olga Kapetanou
George Petsos
Ioannis Nikolaidis
Elias C. Aifantis
Keywords: EEG, Tsallis Entropy, Higuchi Fractal Dimension, Bioinformatics
Abstract:
Alzheimer’s Disease (AD) is one of the challenges of modern medicine since no cure has been found yet, the scientific community still doesn’t fully understand the pathogenesis behind it, and any interventions found can delay the progress for only a limited amount of time. Over the years, research has shifted from curing the disease to understanding the mechanisms behind it as well as finding tools that will speed up diagnosis many years before its clinical manifestation, when the decline begins. One of the many promising tools that have been explored towards that direction is the electroencephalogram (EEG), which holds many different measures that can be used as biomarkers for early diagnosis and differentiation from other neurodegenerative disorders by exploiting various bio-informatics techniques. Literature has presented a high correlation between EEG signals and structural abnormalities in AD. However, there hasn’t been an analysis that can provide a clear result that binds the two and leads to early diagnosis, and very few studies have explored early stages of AD, such as Mild Cognitive Impairment. Moreover, most of the approaches applied do not adopt a multimodal methodology that combines different analysis methods. To that end, the present work proposes the combination of Tsallis Entropy and Higuchi Fractal Dimension, in a common framework for either the entire EEG or on each frequency separately, to examine the performance in Mild Cognitive Impairment (MCI) and AD subjects.
Pages: 3 to 7
Copyright: Copyright (c) IARIA, 2019
Publication date: June 2, 2019
Published in: conference
ISSN: 2308-4383
ISBN: 978-1-61208-717-7
Location: Athens, Greece
Dates: from June 2, 2019 to June 6, 2019