The Development of an Alzheimer's Diagnostic Sensor and Algorithm using Microsaccades Biomarkers

Area of Science:

• Neuroscience
• Ophthalmology
• Gerontology

Background:

• Alzheimer's disease is a progressive neurodegenerative disorder impacting daily life.
• Current diagnostic methods like MMSE and MoCA are time-consuming and lack objective accuracy.
• Objective biomarkers for cognitive decline are needed.

Purpose of the Study:

• To introduce eye-tracking technology as a novel method for assessing cognitive state.
• To investigate the correlation between aging, cognitive function, and microsaccade behavior.
• To validate eye-tracking as a potential objective diagnostic tool for cognitive impairment.

Main Methods:

• Utilized eye-tracking technology to monitor participants' eye movements.
• Analyzed the frequency of microsaccades along the x and y axes.
• Correlated microsaccade data with cognitive function scores and age groups.

Main Results:

• Microsaccade occurrences increased with advancing age.
• A higher number of microsaccades was observed with declining cognitive function scores.
• These changes were evident even within the same age demographics.

Conclusions:

• Demonstrated a significant correlation between aging and cognitive function decline.
• Verified that reduced cognitive function impacts microsaccade patterns.
• Eye-tracking offers a promising, objective approach for monitoring cognitive health and aging effects.