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Document Type |
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Thesis |
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Document Title |
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COMPUTER GENERATED ENVIRONMENT UTILIZING MACHINE LEARNING ALGORITHMS TO DETECT VISUOSPATIAL DISORDER IN DEMENTIA بيئة مولدة بالحاسب تستخدم خوارزميات تعلم الآلة للكشف عن اضطراب الفراغ البصري في الخرف |
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Subject |
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Faculty of Computing and Information Technology |
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Document Language |
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Arabic |
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Abstract |
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As age progresses, the individual is prone to more diseases, among which, one of the most important is represented by dementia. Dementia is difficult to diagnose. Most medical diagnoses are based on the pen-paper cognitive test or high-cost medical devices such as Magnetic Resonance Imaging (MRI). Therefore, there is an increasing need for applying computerized methods in the diagnosis of dementia disease to fully utilize the advantages provided by advanced technologies. When it comes to dementia’s detection, cognitive testing is one of the most accurate tests. Nevertheless, it has many disadvantages, including the measurement of the extent of the brain damage, adaptability with the Intelligence Quotient of the patient (IQ) and assessment that reflects real-world conditions and daily tasks. Hence, it is advisable to explore newer, more effective applications that adapt the cognitive methods with computerized methods. One example is the Virtual Environment (VE), which allows patients to immerse in a controlled environment. This thesis proposes a non-invasive, cognitive computerized test for diagnosis of dementia in earlier stages that uses a 3D virtual environment platform combined with Machine Learning Algorithms (MLAs). The objective is to evaluate two cognitive domains: visuospatial assessment and memory assessment, using multiple MLAs based on a voting approach. A 3D system classifies patients into three classes: patients with severe cognitive impairment (dementia), patients with Mild Cognitive Impairment (MCI), and participants with normal cognition. The experiment was applied on 115 real patients, thirty of those who had dementia, sixty-five that were cognitively healthy and twenty of those that had MCI. The performance of Virtual Reality (VR) system was compared with Mini-Cog test since the latter is used to measure cognitive impaired patients in the traditional diagnosis system at the clinic. |
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Supervisor |
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Dr. Aiiad A. Albeshri |
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Thesis Type |
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Master Thesis |
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Publishing Year |
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1441 AH
2020 AD |
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Co-Supervisor |
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Dr. Wadee S. Alhalabi |
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Added Date |
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Thursday, January 30, 2020 |
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Researchers
| أريج يحيى بايحيى | Bayahya, Areej Yahya | Researcher | Master | |
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