The EyeBOX is intended to measure and analyze eye movements as an aid in the diagnosis of concussion, also known as mild traumatic brain injury (mTBI), within one week of head injury in patients 5 through 67 years of age in conjunction with a standard neurological assessment of concussion. A negative EyeBOX classification may correspond to eye movement that is consistent with a lack of concussion. A positive EyeBOX classification corresponds to eye movement that may be present in both patients with or without concussion.
Device Story
EyeBOX is an eye-tracking device used in clinical settings to aid concussion diagnosis. Patient sits at device, resting chin and forehead on supports; watches video moving around perimeter of LCD monitor. High-speed near-infrared (IR) camera records gaze positions at 500 Hz. Data processing algorithm analyzes eye movements to detect subtle changes associated with concussion; produces 'BOX score' output. Healthcare provider uses output in conjunction with standard neurological assessment to assist clinical decision-making. Device benefits patient by providing objective data to support concussion diagnosis.
Clinical Evidence
Bench testing performed on artificial eye to verify spatial precision and step response. Human participant testing (N=84) conducted to demonstrate reliability of new camera and analysis in detecting blinks and gaze positions across the measured range. Software verification and user testing also performed.
Technological Characteristics
Table-top eye-tracking system; includes host PC, touchscreen, LCD stimulus screen, head/chin rest, and high-speed near-infrared (IR) camera. Connectivity includes WiFi. Standards: IEC 60601-1-2:2014 (EMC), Z80.36-2016 (Light Hazard Protection). Proprietary algorithm processes gaze data to output BOX score.
Indications for Use
Indicated for patients 5-67 years of age with suspected concussion (mTBI) within one week of head injury, used as an aid to standard neurological assessment.
Regulatory Classification
Identification
A traumatic brain injury eye movement assessment aid is a prescription device that uses a patient's tracked eye movements to provide an interpretation of the functional condition of the patient's brain. This device is an assessment aid that is not intended for standalone detection or diagnostic purposes.
Special Controls
In combination with the general controls of the FD&C Act, the traumatic brain injury eye movement assessment aid is subject to the following special controls:
*Classification.* Class II (special controls). The special controls for this device are:(1) Clinical performance data under anticipated conditions of use must evaluate tracked eye movement in supporting the indications for use and include the following:
(i) Evaluation of sensitivity, specificity, positive predictive value, and negative predictive value using a reference method of diagnosis;
(ii) Evaluation of device test-retest reliability; and
(iii) A description of the development of the reference method of diagnosis, which may include a normative database, to include the following:
(A) A discussion of how the clinical work-up was completed to establish the reference method of diagnosis, including the establishment of inclusion and exclusion criteria; and
(B) If using a normative database, a description of how the “normal” population was established, and the statistical methods and model assumptions used.
(2) Software verification, validation, and hazard analysis must be performed. Software documentation must include a description of the algorithms used to generate device output.
(3) Performance testing must demonstrate the electrical safety and electromagnetic compatibility (EMC) of the device.
(4) The patient-contacting components of the device must be demonstrated to be biocompatible.
(5) A light hazard assessment must be performed for all eye-tracking and visual display light sources.
(6) Labeling must include:
(i) A summary of clinical performance testing conducted with the device, including sensitivity, specificity, positive predictive value, negative predictive value, and test-retest reliability;
(ii) A description of any normative database that includes the following:
(A) The clinical definition used to establish a “normal” population and the specific selection criteria;
(B) The format for reporting normal values;
(C) Examples of screen displays and reports generated to provide the user results and normative data;
(D) Statistical methods and model assumptions; and
(E) Any adjustments for age and gender.
(iii) A warning that the device should only be used by trained healthcare professionals;
(iv) A warning that the device does not identify the presence or absence of traumatic brain injury or other clinical diagnoses;
(v) A warning that the device is not a standalone diagnostic; and
(vi) Any instructions to convey to patients regarding the administration of the test and collection of test data.
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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which consists of the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG ADMINISTRATION" in blue text.
Oculogica, Inc. % Janice Hogan Partner Hogan Lovells US LLP 1735 Market Street Suite 2300 Philadelphia, Pennsylvania 19103
Re: K201841
Trade/Device Name: EyeBOX Regulation Number: 21 CFR 882.1455 Regulation Name: Traumatic brain injury eye movement assessment aid Regulatory Class: Class II Product Code: QEA Dated: July 2, 2020 Received: July 2, 2020
Dear Janice Hogan:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part
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801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4. Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Jay Gupta Assistant Director DHT5A: Division of Neurosurgical, Neurointerventional and Neurodiagnostic Devices OHT5: Office of Neurological and Physical Medicine Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known)
Device Name
EyeBOX
Indications for Use (Describe)
The EyeBOX is intended to measure and analyze eye movements as an aid in the diagnosis of concussion, also known as mild traumatic brain injury (mTBI), within one week of head injury in patients 5 through 67 years of age in conjunction with a standard neurological assessment of concussion.
A negative EyeBOX classification may correspond to eye movement that is consistent with a lack of concussion. A positive EyeBOX classification corresponds to eye movement that may be present in both patients with or without concussion.
| Type of Use (Select one or both, as applicable) | |
|----------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------|
| <div> <span> × Prescription Use (Part 21 CFR 801 Subpart D) </span> </div> | <div> <span> Over-The-Counter Use (21 CFR 801 Subpart C) </span> </div> |
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## 510(k) Summary [21 CFR 807.92]
9/4/2020 Date Prepared: Submission Number: K201841 Submitted by: Oculogica Inc. 33 IRVING PLACE NEW YORK, NY 10003 ROSINA SAMADANI, PH.D. 484-393-2694 Subject Device Name: EyeBOX, Model OCL 02.5 EyeBOX, Model OCL 02, K191183 Predicate Device Name: Regulation Number: 21 CFR 882.1455 Traumatic brain injury eye movement assessment aid Regulation Name: Regulatory Class: Class II Product Code: QEA Review Panel: Neurology Oculogica Inc. Manufacturer: 33 IRVING PLACE NEW YORK, NY 10003 301453677 Registration Number: Manufacturer Contact: ROSINA SAMADANI, PH.D. 484-393-2694 ROSINA@OCULOGICA.COM
The company's EyeBOX Model OCL 02.5 device is a modification to the EyeBOX Model OCL 02 device, which was cleared under premarket notification K191183. The EyeBOX Model OCL 02.5 device has the same intended use, the same principles of operation, and similar technological characteristics as the previously cleared EyeBOX Model OCL 02 device. None of the changes in technology raise new questions of safety or effectiveness, and comprehensive testing demonstrates that these changes do not adversely impact performance.
The following table presents a comparison of the device of this submission to the predicate device.
| | Predicate Device | Subject Device |
|---------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------|
| 510(k) Number | K191183 | K201841 |
| Trade Name | EyeBOX | Same |
| Model Number | OCL 02 | OCL 02.5 |
| Manufacturer | Oculogica, Inc. | Same |
| Product Code | QEA | Same |
| Regulation | 21 CFR 882.1455 Traumatic brain injury<br>eye movement assessment aid | Same |
| | | |
| Indications<br>for Use | The EyeBOX is intended to measure and<br>analyze eye movements as an aid in the<br>diagnosis of concussion, also known as<br>mild traumatic brain injury (mTBI), within<br>one week of head injury in patients 5<br>through 67 years of age in conjunction with<br>a standard neurological assessment of<br>concussion.<br>A negative EyeBOX classification may<br>correspond to eye movement that is<br>consistent with a lack of concussion.<br>EyeBOX classification<br>positive -<br>A<br>corresponds to eye movement that may be<br>present in both patients with or without<br>concussion. | Same |
| Device<br>Description | Oculogica's EyeBOX is an eye-tracking<br>device with custom software. The device is<br>comprised of a host PC with integrated<br>touchscreen interface for the operator, eye<br>tracking camera, LCD stimulus screen and<br>head-stabilizing rest (chin rest and<br>forehead rest) for the patient, and data<br>processing algorithm. The data processing<br>algorithm detects subtle changes in eye<br>movements resulting from concussion.<br>The eye tracking task takes about 4<br>minutes to complete and involves watching<br>a video move around the perimeter of an<br>LCD monitor positioned in front of the<br>patient while a high speed near-infrared<br>(IR) camera records gaze positions 500<br>times per second. The post-processed<br>data<br>are analyzed automatically to<br>produce one or more outcome measures. | Same |
| Principle of<br>operation | The data processing algorithm detects<br>subtle changes in eye movements<br>resulting from concussion. The eye<br>tracking task takes about 4 minutes to<br>complete and involves watching a video<br>move around the perimeter of an LCD<br>monitor positioned in front of the patient<br>while a high speed near-infrared (IR)<br>camera records gaze positions 500 times<br>per second. The post-processed data are<br>analyzed automatically to produce a BOX<br>score. | Same |
| WiFi Functionality | Provided | Same |
| Enclosure | Table-top | Same |
| Patient position | Seated only | Same |
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#### 1. Intended Use and Indications for Use Statement
No change is made to the intended use of the device, the patient population or intended user.
The EyeBOX is intended to measure and analyze eye movements as an aid in the diagnosis of concussion, also known as mild traumatic brain injury (mTBI), within one week of head injury in patients 5 through 67 years of age in conjunction with a standard neurological assessment of concussion.
A negative EyeBOX classification may correspond to eye movement that is consistent with a lack of concussion.
A positive EyeBOX classification corresponds to eye movement that may be present in both patients with or without concussion.
#### 2. Technological Characteristics
Oculogica's EyeBOX uses eye-tracking technology and a data processing algorithm to detect subtle changes in eye movements resulting from concussion. The EyeBOX principles of operation have not changed. The principles of operation are identical to its predicate device. The technological characteristics important to device function as an aid in diagnosis of concussion are not changed; the eye tracking performance and proprietary EyeBOX algorithm, which processes the eye tracking data and outputs the BOX score, are not changed.
The following changes have been implemented.
- The eye tracking camera is replaced with a camera system having equivalent function. ●
- Certain components are replaced with components having equivalent function.
- . Minor changes to the user interface to simplify user interaction.
- Minor changes to the EyeBOX report to assist interpretation of results.
None of the changes in technology raise new questions of safety or effectiveness.
#### 3. Performance Testing
The following verification / validation activities were performed by the risk assessment of the changes according to the Oculogica Quality Management System. Results of this comprehensive testing demonstrate that these changes also do not adversely impact performance.
- Electromagnetic emissions and immunity testing according to IEC 60601-1-2:2014 (4TH EDITION) Medical electrical equipment - Part 1-2: General requirements for basic safety and essential performance - Collateral Standard: Electromagnetic disturbances - Requirements and tests
- Z80.36-2016 Light Hazard Protection For Ophthalmic Instruments ●
- Bench testing was performed on an artificial eye (designed with similar geometry to a ● human eye) to demonstrate that the spatial precision and step response of the new camera met performance requirements.
- Testing was performed in N=84 human participants to demonstrate that the new camera and analysis could reliably detect blinks and gaze position across the range of gaze positions measured by the device.
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- Software verification and user testing ●
#### Conclusion 4.
The EyeBOX Model OCL 02.5 device has the same intended use and principle of operation as the previously cleared EyeBOX Model OCL 02 device. In addition, the EyeBOX Model OCL 02.5 device has comparable technological characteristics as its predicate. None of the changes in technology raise new questions of safety or effectiveness, and comprehensive testing demonstrates that these changes do not adversely impact performance. Thus, the EyeBOX Model OCL 02 device is substantially equivalent to its predicate device.
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.
