How video games can monitor eye conditions using the Vision Performance Index : A pilot study

Authors: Yusuf Ahmed, Josh Herman, Mohan Reddy, Jacob Mederos, Kyle C. McDermott, Devesh K. Varma, Cassie A. Ludwig, Iqbal (Ike) K. Ahmed, Khizer R. Khaderi

Authors Disclosures: Yusuf Ahmed: Not Current  Josh Herman: Not Current  Mohan Reddy: Not Current  Jacob Mederos: Not Current  Kyle McDermott: Not Current  Devesh Varma: Not Current  Cassie Ludwig: Not Current  Iqbal (Ike) Ahmed: Not Current  Khizer Khaderi: Not Current 

Abstract Body:

Purpose: In a world where digital media is deeply engrained into our everyday lives, there lies an opportunity to leverage our interactions with technology for health and wellness purposes. The Vision Performance Index (VPI) leverages natural human-technology interaction to evaluate visual function using visual, cognitive and motor psychometric data over five domains: field of view, accuracy, multi-tracking, endurance, and detection. The purpose of this study was to evaluate trends in VPI scores and psychophysical measures in patients with specific ocular pathology using data obtained from patient-interactions with video games.  

Study Design:  Prospective comparative analysis  

Methods:  The Vizzario Inc software development kit was integrated into two video-game applications, Balloon Pop and Picture Perfect, which allowed for generation of VPI scores. Patients with dry eye disease, glaucoma, cataract, diabetic retinopathy (DR), and age-related macular degeneration (AMD) as well as healthy individuals were instructed to play video games which were specifically engineered to allow for VPI generation. The primary outcome was VPI overall score in each comparison group. VPI component and subcomponent scores, and VPI psychophysical inputs, were also compared.      

Results:  VPI overall score was not significantly different across comparison groups. VPI subcomponent ‘reaction accuracy’ score was significantly greater in DR patients (106 ± 13.2) versus controls (96.9 ± 11.5), p=0.0220. VPI subcomponent 
‘colour detection’ score was significantly lower in patients with DR (96.8 ± 2.5; p=0.0217) and glaucoma (98.5 ± 6.3; p=0.0093) compared to controls (101 ± 11; p=0.0198). Psychophysical measures were statistically significantly different from controls: proportion correct (lower in DR, AMD), contrast errors (higher in cataract, DR), and saturation errors (higher in dry eye).  

Conclusions:  The VPI may offer utility in monitoring select ocular diseases through evaluation of subcomponent and psychophysical input scores. The VPI offers an opportunity to shift the paradigm of visual health, wellness, and performance assessments.