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Towards Early Diagnosis of Dementia Using a Virtual Environment

  • Conference paper
Transactions on Computational Science XVIII

Part of the book series: Lecture Notes in Computer Science ((TCOMPUTATSCIE,volume 7848))

Abstract

Dementia is one of the biggest fears in the process of ageing and the most common cause is Alzheimer’s Disease(AD). Topographic disorientation is an early manifestation of AD and threatens activities of their daily lives. Finding solutions are essential in the early diagnosis of dementia if medical treatment and healthcare services to be deployed in time. Recent studies have shown that people with mild cognitive impairment (MCI) may convert to Alzheimer’s disease (AD) over time although not all MCI cases progress to dementia. The diagnosis of MCI is important to allow prompt treatment and disease management before the neurons degenerate to a stage beyond repair. Hence, the ability to obtain a method of identifying MCI is of great importance. This work presents a virtual environment which can be utilized as a quick, easy and friendly tool for early diagnosis of dementia. This tool was developed with an aim to investigate cognitive functioning in a group of healthy elderly and those with MCI. It focuses on the task of following a route, since Topographical Disorientation (TD) is common in AD. The results shows that this novel simulation was able to predict with about 90% overall accuracy using weighting function proposed to discriminate between MCI and healthy elderly.

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Author information

Authors and Affiliations

  1. Faculty of Informatics, Universiti Sultan Zainal Abidin, Malaysia

    Syadiah Nor Wan Shamsuddin

  2. Centre for Visual Computing, University of Bradford, Bradford, BD7 1DP, UK

    Hassan Ugail

  3. Division of Psychology, University of Bradford, Bradford, BD7 1DP, UK

    Valerie Lesk & Elizabeth Walters

Authors
  1. Syadiah Nor Wan Shamsuddin
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  2. Hassan Ugail
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  3. Valerie Lesk
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  4. Elizabeth Walters
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Exascala Ltd., Unit 9, 97 Rickman Drive, B15 2AL, Birmingham, UK

    C. J. Kenneth Tan

  3. Institut für Graphische Datenverarbeitung, Fraunhofer Gesellschaft, Fraunhoferstraße 5, 64283, Darmstadt, Germany

    Arjan Kuijper

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Wan Shamsuddin, S.N., Ugail, H., Lesk, V., Walters, E. (2013). Towards Early Diagnosis of Dementia Using a Virtual Environment. In: Gavrilova, M.L., Tan, C.J.K., Kuijper, A. (eds) Transactions on Computational Science XVIII. Lecture Notes in Computer Science, vol 7848. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38803-3_13

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  • DOI: https://doi.org/10.1007/978-3-642-38803-3_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38802-6

  • Online ISBN: 978-3-642-38803-3

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