EyeBOX

DEN170091

Oculogica, Inc. · granted 2018-12-28 · product code QEA · Neurology

Premarket evidence — what FDA accepted

Device typehardware with ml
source quote (p.2)
“The Oculogica EyeBOX system consists of an integrated stand, eye-tracking camera, video stimulus display screen, and computer programmed for analysis of eye movements.”
AlgorithmThe device collects 220 seconds of binocular gaze data at 500Hz, processes it for blinks and normalization, and calculates a score between 0 and 20 based on an underlying model. Scores of 10 or more indicate possible concussion.
source quote (p.3)
“During eye tracking, EyeBOX collects 220 seconds of binocular gaze data at 500Hz as the patient watches the video stimulus go around the screen five times. The first and last ten seconds of data are discarded. The data are processed for blinks and normalized. A score between 0 and 20 is the calculated from the normalized data. Scores of 10 or more are presented as consistent with the possible presence of concussion.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedNo

Validation studies (2)

Bench

sample size not stated

standards: ANSI/AAMI ES60601-1: 2005 and A1:2012, Medical electrical equipment Part 1: General requirements for basic safety and essential performance, IEC 60601-1-2:2014 (4th edition), Medical electrical equipment – Part 1-2: General requirements for basic safety and essential performance – Collateral Standard: Electromagnetic Compatibility – Requirements and Tests, EN 61000-4-2:2008, Electrostatic Discharge Immunity, IEC 62471:2006 Photobiological Safety of Lamps and Lamp Systems, ISO 15004-2:2007 Ophthalmic Instruments - Fundamental Requirements and Test Methods Part 2: Light Hazard Protection

Retrospective clinical

n=282 patients

endpoints: sensitivity; specificity; positive predictive value; negative predictive value; test-retest reliability

Reported performance (4 observations)

sensitivity80.4CI 66.1%, 91.9%
source quote (p.7)
“The EyeBOX identified 37 of these as positive for concussion (score 10 or higher), resulting in a measured sensitivity of 80.4% (66.1%, 91.9%).”
specificity66.1CI 59.7%, 72.1%
source quote (p.7)
“Of the 236 subjects who did not meet the clinical reference standard definition of concussion, EyeBOX identified 156 as negative for concussion (score less than 10) resulting in a measured specificity of 66.1% (59.7%, 72.1%).”
npvas written: “Negative Predictive Value (NPV)”94.5CI 89.9%, 97.5%
source quote (p.8)
“The negative predictive value (NPV) of the device was 94.5% (89.9%, 97.5%).”
ppvas written: “Positive Predictive Value (PPV)”31.6CI 23.3%, 40.9%
source quote (p.8)
“The positive predictive value (PPV) was 31.6% (23.3%, 40.9%).”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: De Novo decision summary PDF.

Predicate network

Postmarket — what happened after clearance

Not yet tracked — the weekly postmarket refresh hasn't snapshotted this device.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to De Novo AI/ML devices in the Neurology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/DEN170091