Utilization of automated eye tracking as an ancillary diagnostic test in neurological disorders.

Abstract

Modern eye-tracking technology, a non-invasive modality that records eye movements in response to visual stimuli, has shown significant promise as a diagnostic tool for neurological disorders. Its capacity to detect subtle abnormalities in ocular motor function, often linked to underlying neural circuitry dysfunction, provides a distinct advantage over traditional bedside examinations, which may overlook these nuances and typically require more advanced or invasive diagnostic modalities. Moreover, these advanced methods are not always readily available in routine clinical practice and may not capture the valuable insights that eye-tracking can provide. Despite its potential, the application of eye-tracking has largely remained confined to research settings, often restricted by a narrow focus on specific neurological conditions and a reliance on individualized data analysis. This has impeded its broader adoption in clinical neurology, where standardized, scalable, and automated diagnostic tools are essential. In this project, we aimed to bridge this gap by developing a comprehensive and automated Diagnostic Eye-Tracking Study (DETS) tailored for routine clinical practice. We established standardized protocols incorporating relevant visual stimuli and tasks, and defined biometrics that are both informative and practical for clinical neurology. Additionally, we developed an advanced analytical software platform capable of generating both quantitative and qualitative results, ensuring robust and clinically relevant interpretations. To validate our approach, we conducted a pilot study that demonstrated the efficacy and feasibility of the protocols, as well as the validity and reliability of our automated analytical software. The study confirmed that our approach offers a valuable ancillary tool to enhance diagnostic accuracy across a range of neurological disorders. By integrating this tool into standard neurological assessments, we anticipate a significant improvement in patient outcomes.