EyeBOX

The EyeBOX device aids in diagnosing concussion by utilizing high-speed, near-infrared eye-tracking technology to record gaze positions, which are then analyzed by a proprietary algorithm to detect subtle oculomotor changes indicative of mild traumatic brain injury. It is intended for patients aged 5 to 67 within one week of head injury, serving as an objective adjunctive tool to standard neurological assessments.

The EyeBOX, Model OCL 02.5, is a medical device designed to assist in the diagnosis of concussion, also known as mild traumatic brain injury (mTBI). It is intended for use with patients aged 5 through 67 years within one week of a head injury, functioning as an adjunct to a standard neurological assessment. The device's primary purpose is to measure and analyze eye movements to detect subtle abnormalities that may indicate a concussion, providing clinicians with objective data to support their diagnostic conclusions. The methodology involves the patient watching a video stimulus on an LCD monitor for approximately four minutes while a high-speed near-infrared (IR) camera records their gaze positions 500 times per second. These recorded data are then processed by a proprietary algorithm that identifies subtle changes in eye movements characteristic of concussion, culminating in a 'BOX score.' The device output includes a classification: a negative EyeBOX classification suggests eye movements consistent with the absence of concussion, whereas a positive classification indicates eye movements that could be present in individuals both with and without concussion. The Model OCL 02.5 incorporates an updated eye-tracking camera system and other component modifications, with bench and human participant testing performed to validate aspects such as spatial precision, step response, and reliable blink and gaze detection.

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. What specific eye movement parameters does the EyeBOX algorithm analyze to generate the BOX score, and how are these parameters quantitatively differentiated in concussed versus non-concussed individuals?; Given that a 'positive EyeBOX classification corresponds to eye movement that may be present in both patients with or without concussion,' what is the device's specificity and positive predictive value in diverse clinical populations, and how should clinicians interpret such a positive finding?; How does the algorithm account for potential variability in eye movement characteristics across the wide indicated age range (5 to 67 years), and are there different normative thresholds or adjustments applied for pediatric, adolescent, adult, and older adult populations?; The N=84 human participant testing demonstrated reliable blink and gaze position detection with the new camera; what were the quantitative results for spatial precision and step response from the artificial eye testing, and how do these translate to diagnostic accuracy?; Beyond the listed changes (camera, components, UI, report), were there any modifications to the core data processing algorithm or the BOX score calculation between Model OCL 02 and Model OCL 02.5?