Measurement and Analysis of Eye Movements Performance to Predict Healthy Brain Aging

• Published in: IEEE access Vol. 8; pp. 87201 - 87213
• Main Authors: Garcia Cena, Cecilia E., Andres, David Gomez, Valdeolivas, Irene Pulido
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Abnormalities; Aging; biomarker; Biomarkers; Brain; Cameras; Diseases; Electrooculography; Eye movements; healthy pattern; Informed consent; measurement techniques; Motion measurement; Parkinson's disease; Statistical analysis; Visualization
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.2992254

Objective: This article presents the healthy pattern of eye movements (EM) in 145 healthy volunteers from 20 to 86 years old. Volunteers were classified into four groups according to their age. A saccadic paradigm, in horizontal and vertical axes, was performed. We described a pattern behavior in healthy volunteers to demonstrate that it can be used to measure the aging and functionality of the brain. Methods: A gaze-tracker based in video-oculography technology was used. Before EM tests, clinical data were collected, participants performed a cognitive test to discard subtle abnormalities and signed an informed consent form. To demonstrate the relationship between EM and brain aging, a linear or quadratic model was computed and statistical analysis among groups was presented. Conclusion: EM variables could be considered as biomarkers to measure the aging effect and functionality of the brain. Video-oculography is a suitable technique for measuring EM in clinical practice. Significance: The ocular healthy pattern as well as the methodology followed in this clinical study, is the base for ongoing studies aiming to incorporate EM analysis at routine practice as markers in early diagnosis for patients with neurodegenerative diseases like Alzheimer's dementia or Parkinson's disease.