To investigate the feasibility of detecting and quantifying simulated skew deviations using the EyePhone smartphone eye-tracking application.
Approach:
Study Design: Healthy volunteers were enrolled, and their eye movements were recorded using EyePhone while simulating skew deviation through a cross-cover test.
Measurement Technique: Eye movements were analyzed using in-house code that extracted features from videos recorded by EyePhone.
Key Findings:
EyePhone demonstrated a Spearman correlation of 0.93 (CI: 0.90–0.95) with designed skew deviations.
The area under the receiver operator curve for discriminating skews ≥5 diopters was 0.90.
Interpretation:
EyePhone may serve as a practical tool for detecting clinically significant skew deviation, pending further validation.
Limitations:
The study was conducted in a controlled experimental setting with healthy volunteers.
Further validation in clinical groups is necessary.
Conclusion:
EyePhone shows potential for detecting skew deviations, which could aid in the diagnosis of vestibular strokes.
