Early Detection of Alzheimer's Disease Through Eye Movement Analysis: A Digital Diagnostic Approach

Yu Chun Lin, Li Kai Huang, Jeng Chian Wu, Tai Ying Chang, Hsiang Wei Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Given the increasing worldwide incidence of dementia, primarily Alzheimer's disease dementia, there is an urgent requirement for non-invasive, early diagnostic techniques. This study introduces a novel approach utilizing eye movement analysis to detect early signs of cognitive decline indicative of dementia disorders. By analyzing the eye movement patternsof 95 participants, including 31 individuals with dementia and 64 cognitively normal controlsubjects, during tasks involving picture description and reading activities, distinct eye movement characteristics were identified. Using the Tobii Eye Tracker 5 for precise tracking and ASUS tablets for display, the study leveraged advanced machine learning algorithms such as XGBoost, logistic regression, and deep neural networks (DNNs) to analyze data. Significanteye movement features differentiated people with dementia from controls, indicating potential as early biomarkers. This approach demonstrated that digital eye tracking technologies combined with machine learning could offer a rapid, cost-effective solution for early all causedementia diagnosis, promising substantial improvements in patient care and management strategies. The outcomes suggest the feasibility of this method in clinical settings, highlightingthe importance of further research with larger sample sizes to refine the diagnostic models.

Original languageEnglish
Title of host publicationIEEE International Workshop on Electromagnetics
Subtitle of host publicationApplications and Student Innovation Competition, iWEM 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350366976
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2024 - Taoyuan, Taiwan
Duration: Jul 10 2024Jul 12 2024

Publication series

NameIEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2024

Conference

Conference2024 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2024
Country/TerritoryTaiwan
CityTaoyuan
Period7/10/247/12/24

Keywords

  • All cause dementia
  • Alzheimer's Disease
  • Deep Neural Network
  • Digital Diagnostics
  • Early Diagnosis
  • Eye Movement Analysis
  • Machine Learning Models

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Instrumentation

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