Classification of Alzheimer's disease patients using metrics of oculo-motors

• Autorzy: Nowak Wioletta , Nakayama Minoru , Trypka Elzbieta , Zarowska Anna

Identyfikatory

DOI

10.15439/2021F32

• Konferencja: Federated Conference on Computer Science and Information Systems (16 ; 02-05.09.2021 ; online)
• Języki publikacji: EN

Abstrakty

EN

Ocular information was observed during a set of dementia tests involving participants with two diagnostic levels of illness, such as having Alzheimer's Disease (AD), a mild level of cognitive impairment (MCI) patients, and a control group. The number of participants was 26. Features of changes in pupil size and in the central position of both eyes were compared between three levels. There are significant differences in some of the metrics between the levels in the earlier test sessions. The possibility of classification was confirmed using the extracted features, and the contributions of some features were examined.

Słowa kluczowe

EN

cognition; disease; eye; feature extraction; neurophysiology

PL

poznanie; choroba; oko; ekstrakcja cech; neurofizjologia

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2021
• Tom: Vol. 25
• Strony: 403--407
• Opis fizyczny: Bibliogr. 12 poz., wykr., tab.

Twórcy

autor

Nowak Wioletta

• Institute of Biomedical Engineering and Instrumentation, Wrocław University of Science and Technology, Wrocław, Poland 50–370

autor

Nakayama Minoru

• Department of Information and Communications Engineering, Tokyo Institute of Technology, Tokyo, Japan 152-8552

autor

Trypka Elzbieta

• Wrocław Medical University Rektorat, Wybrzeze Ludwika Pasteura 1, 50-367 Wrocław, Poland

autor

Zarowska Anna

• Wrocław University of Science and Technology, Wrocław, Poland 50–370

Bibliografia

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• 7. W. Nowak, M. Nakayama, T. Kręcicki, and A. Hachoł, “Detection procedures for patients of Alzheimer’s disease using waveform features of pupil light reflex in response to chromatic stimuli,” EAI Endorsed Transactions on Pervasive Health and Technology, vol. 6, pp. 1-11, December 2020, e6.
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Uwagi

1. Track 3: Advances in Information Systems and Technology

2. Session: 3rd Special Session on Data Science in Health, Ecology and Commerce

3. Short Papers