EyeBOX

The EyeBOX device aims to provide an objective assessment for concussions by utilizing electroencephalography (EEG) and eye-tracking technology to analyze responses to visual stimuli in patients shortly after a head injury. It employs trained classifiers to derive a quantitative score from oculomotor and EEG metrics, demonstrating notable sensitivity and specificity in identifying injuries corroborated by CT scans, thus serving as a supplementary diagnostic tool.

The EyeBOX device is designed for the objective evaluation of concussions in individuals aged 5 to 67, specifically within one week following a head injury. The methodology involves patients wearing an electroencephalography (EEG) headset while observing moving visual stimuli. During this process, the EyeBOX system concurrently records the patient's eye movements and EEG data, which is then processed to extract critical oculomotor and quantitative EEG (qEEG) metrics, forming the basis for a scientifically derived score. The system further utilizes trained classifiers, which compare the patient's acquired data against established data from trauma cohorts to calculate a concussion likelihood score ranging from 0 to 20. Clinical studies have demonstrated the EyeBOX's efficacy, showing approximately 90% sensitivity and 80% specificity in detecting injuries that were also positive on CT scans, positioning it as an objective, supplementary diagnostic tool to augment traditional neurological examinations in the assessment of mild head trauma.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. How does the EyeBOX score correlate with the severity of concussion symptoms or long-term outcomes in patients who are CT-negative but clinically symptomatic?; What specific oculomotor and quantitative EEG metrics contribute most significantly to the EyeBOX score, and how are these metrics weighted by the trained classifiers?; How does the performance of EyeBOX (sensitivity/specificity) vary across different age groups within the 5-67 range, and are there adjustments in the algorithm for pediatric versus adult populations?; What is the test-retest reliability of the EyeBOX score in stable individuals, and how susceptible is the device to factors like fatigue, medication, or pre-existing neurological conditions unrelated to the acute head injury?; Beyond identifying CT-positive injuries, how effective is EyeBOX in differentiating between concussions and other non-structural head injuries or in tracking recovery trajectories over time?