Low-Cost Biomarker for Eye Pattern Localization in Neurodegenerative Disorders

Overview

Neurodegenerative disorders are characterized by an extremely low quality of life and the deterioration of normal bodily and muscular functions including movement, memory, balance, breathing, and vision. Approximately 6.8 million lives are claimed by Parkinson’s, Dementia, and Multiple Sclerosis patients alone; however, a recent World Health Organization study linked the fatality rates to the late diagnosis achieved by standard diagnostic modalities. Therefore, the purpose of this research study is to develop a cost-effective, yet sensitive and specific biomarker to identify associated eye movement patterns in Parkinson’s, Dementia, and Multiple Sclerosis. The eye movement concepts of saccades and smooth pursuits are utilized in this study in order to map cognitive vision impairment in individual participants and are implemented using a combination of animation and software techniques. An advanced unsupervised machine learning localization algorithm classifies the different eye regions and plots the coordinate points to be analyzed for abnormal patterns. Additionally, the introduction of dot animation sequences for testing provides an adaptable platform that tests the endurance and flexibility of the six eye muscular regions. The biomarker itself was developed using low-cost materials that would be easily replicated and applied in rural areas and outpatient clinics. The experimental subjects consisted of three research cohorts (Parkinson’s, Dementia, and Multiple Sclerosis) and three control cohorts each spread among various ages for comparison. In 97% of the Parkinson's group, one eye tends to travel up to two times faster than the other, and eye positional data points signs to horizontal eye tremors occurrent during changes in direction. Approximately 89% of the dementia group had erratic location analyses as well, showing an overall subdued velocity and scattered gaze around the intended target. About 76% of the Multiple Sclerosis group experience multiple breaks in foveation and abnormal velocities that issues in horizontal tracking. In the future, a much wider range of diseases and eye movements could be tested to discover faster, more accurate, and more economically sensed diagnosis; additionally, this software can be adapted to be used as a monitoring and treatment tool for psychological patients. However, for now, the combination of this low-cost hardware, accurate software, and versatile animations make it a top contender for the diagnosis of neurodegenerative diseases at an early stage.

Competition history

• AJAS 2019 Category not listed

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