K212684 · Medeia, Inc. · OLU · Jan 28, 2023 · Neurology
Device Facts
Record ID
K212684
Device Name
BrainView QEEG Software
Applicant
Medeia, Inc.
Product Code
OLU · Neurology
Decision Date
Jan 28, 2023
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 882.1400
Device Class
Class 2
Attributes
Software as a Medical Device, Pediatric
Indications for Use
The BrainView QEEG Software Package is to be used by qualified medical or clinical professionals for the statistical evaluation of the human electroencephalogram (EEG).
Device Story
BrainView QEEG Software Package performs post-hoc statistical analysis of resting digital EEG data. Input consists of artifact-free, eyes-closed or eyes-open EEG recordings transferred from a host system. The software applies Fast-Fourier Transformation (FFT) to extract spectral power for delta, theta, alpha, and beta frequency bands. It derives over 4,000 measures, including absolute/relative power, asymmetry, and coherence for 19 monopolar and 171 bipolar derivations. These are compared against an age-regressed, Gaussian-validated normative database to generate Z-scores. Results are presented as statistical tables and topographical brain maps. Used in clinical settings by qualified medical personnel, the output serves as a supplementary tool for patient evaluation. It is contraindicated for use as a standalone diagnostic system; clinicians must review traditional EEG and selected epochs to avoid diagnostic errors. The device benefits patients by providing quantitative, age-matched normative comparisons to assist clinical decision-making.
Clinical Evidence
Bench-only validation using clinically acquired EEG waveforms from a small sample of subjects across the 4-85 age range. The study compared Z-scores for absolute power generated by the subject device against the predicate (K041263). Acceptance criteria required an R-squared factor of 0.8 or better. Results confirmed that the subject device produces results in agreement with the predicate across 23 age-grouped sets of Z-scores.
Technological Characteristics
Software-based QEEG analysis tool. Implements Fast-Fourier Transformation (FFT) for spectral analysis (1-40 Hz). Features include Z-score calculation and topographical mapping for 19 monopolar and 171 bipolar derivations. Normative database includes 2303 subjects (eyes-closed) and 1965 subjects (eyes-open) aged 4-85. Developed per IEC 62304:2015. Software level of concern: Moderate.
Indications for Use
Indicated for qualified medical or clinical professionals to perform post-hoc statistical evaluation of human EEG in patients aged 4-85 years.
Regulatory Classification
Identification
An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.
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January 28, 2023
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Medeia, Inc. % Daniel Lehtonen Regulatory Consultant Compliance and Regulatory Services, LLC 3771 Southbrook Dr. Dayton, Ohio 45430
Re: K212684
Trade/Device Name: BrainView QEEG Software Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OLU Dated: February 4, 2022 Received: February 8, 2022
Dear Daniel Lehtonen:
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
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requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 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 (OS) 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 R. Gupta -S
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) K212684
Device Name BrainView OEEG Software Package
Indications for Use (Describe)
The BrainView QEEG Software Package is to be used by qualified medical or clinical professionals for the statistical evaluation of the human electroencephalogram (EEG).
Type of Use (Select one or both, as applicable)
| <div> <span></span>Prescription Use (Part 21 CFR 801 Subpart D) </div> |
|---------------------------------------------------------------------------|
| <div> <span></span>Over-The-Counter Use (21 CFR 801 Subpart C) </div> |
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Image /page/3/Picture/0 description: The image shows the logo for Medeia. The logo has the word "Medeia" in bold, black letters. The first letter, "M", is colored with a gradient from green to blue. Below the word "Medeia" is the phrase "Designed for Clinicians" in blue letters.
# 510(k) SUMMARY
This summary of 510(k) safety and effectiveness information is submitted in accordance with the Requirements of Safe Medical Device Systems Act 1990 and 21 CFR Sec. 807.92
510(k) Number:
K212684
#### a1 APPLICANT INFORMATION:
| Date Prepared: | 10 Dec 2021 |
|----------------|---------------------------------------------------------------|
| Name: | Medeia, Inc. |
| Address: | 7 W. Figueroa Street<br>Suite 300<br>Santa Barbara, CA, 93101 |
| Contact Person: | Slav Danev |
|-----------------|------------------|
| Phone Number: | +1 800 433 4609 |
| Fax Number: | +1 800 433 4609 |
| Email: | danev@medeia.com |
#### a2 NAME OF DEVICE:
| Trade Name: | BrainView QEEG Software Package |
|-----------------------|---------------------------------------------------------|
| Common Name: | Normalizing Quantitative Electroencephalograph Software |
| Classification Name: | Electroencephalograph; 21 CFR 882.1400 (OLU) |
| Classification Panel: | Neurology |
#### a3 PREDICATE DEVICES:
| Predicate Device: | K041263; NeuroGuide Analysis System (NAS) |
|-------------------|-------------------------------------------|
| Reference Device: | K171414; qEEG-Pro |
The FDA database for recalls was searched on 03 March 2021 during the preparation of the 510(k) submission and no recalls for the devices noted above were found.
#### STATEMENT OF INTENDED USE: a4
The BrainView QEEG Software Package is to be used by qualified medical or clinical professionals for the statistical evaluation of the human electroencephalogram (EEG).
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Image /page/4/Picture/1 description: The image shows the logo for Medeia. The word "Medeia" is written in a combination of colors, with the "M" transitioning from green to blue, and the rest of the letters in black. Below the word "Medeia" is the phrase "Designed for Clinicians" in a smaller, light blue font.
#### a5 DESCRIPTION OF THE DEVICE:
BrainView QEEG Software Package is a software program for the post-hoc statistical analysis of the human electroencephalogram (EEG). EEG recorded on a separate device (i.e., the host system) is transferred to the BrainView QEEG software package for display and user-review.
The device herein described consists of a set of tables that represent the reference means and standard deviations for representative samples. These tables are implemented as computer files that provide access to the exact tabular data resource for use by software that uses the tables as an information resource. The system requires that the user select reliable samples of artifact-free, eyes-closed or eyes open, resting digital EEG for purposes of analysis.
Analysis consists of the Fast-Fourier Transformation (FFT) of the data to extract the spectral power for each of the designated frequency bands (e.g. delta, theta, alpha, and beta), and frequency information from the EEG. The results of this analysis are then displayed in statistical tables and topographical brain maps of absolute and relative power asymmetry, and coherence for 19 monopolar and 171 selected bipolar derivations of the EEG.
In all over 4,000 measures are derived for comparison against carefully constructed and statistically controlled age-regressed, normative database in which the variables have been transformed and validated for their Gaussian distribution.
Each variable extracted by the analysis is compared to the database using parametric statistical procedures that express the differences between the patient and an appropriate age-matched reference group in the form of z-scores.
The BrainView QEEG Software Package is intended for prescription use by qualified medical personnel.
The device is intended for use by qualified medical personnel only and qualifies for exemption per 21 CFR 801 Subpart D Prescription devices.
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#### TECHNOLOGICAL CHARACTERISTIC COMPARISON: a6
| ltem | BrainView QEEG | NeuroGuide Analysis<br>System (NAS)<br>K041263 | qEEG-Pro<br>K171414 |
|---------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Device | Subject Device | Predicate Device | Reference Device |
| Indications for<br>Use | The BrainView QEEG<br>system is to be used by<br>qualified medical and<br>qualified clinical<br>professionals for the<br>post-hoc statistical<br>evaluation of the human<br>electroencephalogram<br>(EEG).<br>Rx-only | The NAS system is to be<br>used by qualified medical<br>and qualified clinical<br>professionals for the<br>post-hoc statistical<br>evaluation of the human<br>electroencephalogram<br>(EEG).<br>OTC | The qEEGpro system is to<br>be used by qualified<br>medical and qualified<br>clinical professionals for<br>the post-hoc statistical<br>evaluation of the human<br>electroencephalogram<br>(EEG).<br>Rx-only |
| EEG data<br>comparison<br>against normative<br>database | Yes; 2303 subjects<br>(eyes closed);<br>1965 subjects<br>(eyes open) | Yes; 625 samples | Yes; 1482 samples<br>(eyes closed);<br>1231 subjects<br>(eyes open) |
| EEG Spectral<br>Analysis | Yes; 4 frequency bands<br>(delta, theta, alpha, and<br>beta) | Yes; 4 frequency bands<br>(delta, theta, alpha, and<br>beta) | Yes; 4 frequency bands<br>(delta, theta, alpha, and<br>beta) |
| Age Range<br>Included in the<br>Normative<br>Database | 4-85 years | 2 months-82 years | 4-82 years |
| Product code | OLU | OLU | OLU |
| Classification | 882.1400 | 882.1400 | 882.1400 |
| Visual Display of<br>EEG | Yes | Yes | Yes |
| Software | Proprietary via DLL | Proprietary via DLL | Proprietary via DLL |
| Software<br>Features | Onscreen QEEG Z-Scores<br>and maps | Onscreen QEEG Z-Scores<br>and maps | Onscreen QEEG Z-Scores<br>and maps |
| Frequency Range | 1 - 40 Hz | 0.5 to 40 Hz | 1 - 40 Hz |
| Ratio of power | Yes | Yes | Yes |
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#### b1 NON-CLINICAL TESTING:
Non-clinical performance testing included delta, theta, alpha, and beta comparison of the subject and predicate device using a variety of simulated signals which were analyzed for frequency and power. These performance data demonstrated confirmation of pre-specified, objective evidence to specify that output requirements for the software have been fulfilled and met through static and dynamic analyses and code and document inspections. The software testing performance data further established that the software device's specifications consistently conform to the pre-specified user needs and the intended use. The algorithms and statistical methods used for data analysis were also evaluated through these tests. Therefore, the testing demonstrated the that the system accurately translates and presents EEGs from patients.
Potential adverse effects of the device are known if the BrainView QEEG software package is used as a standalone diagnostic system in the absence of other clinical data from more traditional means of patient evaluation. Relying only upon the use of a single index (such as relative power or the topological maps alone) without reviewing the traditional EEG, the epochs selected for analysis, or the complete set of statistical summary tables is also contraindicated and a source of potential error. Additional sources of error could arise from the inappropriate selection of EEG (selecting EEG epochs with artifacts, or by purposely selecting conditions for testing other than those specified). Additionally, it is possible that errors will occur through the purposeful falsification of symptoms in the patient history and patient age.
### Referenced Standards and Performance Testing:
The BrainView QEEG Software Package was developed using:
- IEC 62304:2015 [Edition 1.1] Medical device software — Software life cycle processes
## Software Verification and Validation Testing
Software verification and validation testing were conducted following the FDA guidance document for software contained in medical devices. The software was considered to be a "moderate" level of concern since a failure or latent flaw could indirectly result in a minor injury to the patient through incorrect or delayed information or through action of the operator.
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Image /page/7/Picture/1 description: The image shows the logo for Medeia. The word "Medeia" is written in a combination of colors, with the "M" in green and blue, and the rest of the letters in black. Below the word "Medeia" is the phrase "Designed for Clinicians" in a smaller font size.
#### b2 CLINICAL TESTING:
Clinical testing of the subject device included the use clinically acquired EEG waveforms from selected subjects who were used to validate performance of subject device database to that of the predicate K041263. These subjects were adequate to provide a range of values of the databases to verify performance since they are part of the adult and pediatric range of ages as well as the frequencies within the databases.
Acceptance criteria were defined as the BrainView QEEG software produces results sufficiently in agreement with the predicate device and that the R-squared factor shall be 0.8 or better. Additionally, the observed range of results obtained from the predicate device shall be used to verify that the BrainView QEEG produces results in agreement with the results obtained from the predicate device. The pre-defined acceptance criteria were met as 10-minute EEG recordings for eyes closed and eyes open of the subjects were de-artifacted and used to calculate z-scores for absolute power for the subject and predicate databases. Although the sample size was small, it was possible to validate results by computing values for all discrete ages ranging between 4 and 85, resulting in 23 age grouped sets of Z-scores for each subject's EEG sample which were compared with the predicate device's output and found to be similar.
#### b3 CONCLUSIONS:
The BrainView QEEG software has the same intended use as the predicate device, and it has the same manner of use and function, being a software-based database. Furthermore, it has similar requirements for training and expectations of intended users. The systems have equivalent performance in terms of data sampling and accuracy in the reference norms across age. Based on the device description, IFU, and performance testing, the BrainView QEEG software package is substantially equivalent to the predicate.
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.