The qEEG-Pro System is to be used by qualified clinical professionals for the statistical evaluation of the human electroencephalogram (EEG).
Device Story
qEEG-Pro is a software-based tool for post-hoc statistical analysis of human EEG; inputs are artifact-free, resting digital EEG recordings (eyes-open or eyes-closed) transferred from a host system. The device performs Fast-Fourier Transformation (FFT) to extract spectral power (delta, theta, alpha, beta) and frequency information. It compares these variables against an age-regressed normative database using parametric statistics to generate z-scores. Outputs include statistical tables and topographical brain maps of absolute/relative power, power asymmetry, and coherence. Used by qualified clinical professionals in a clinical setting to assist in patient evaluation; output is intended to supplement, not replace, traditional EEG review and clinical assessment. Benefits include objective statistical comparison of patient EEG against normative reference groups to aid clinical decision-making.
Clinical Evidence
Validation study of 3 subjects (1 pediatric, 2 adult) comparing qEEG-Pro to the predicate (K041263). 9-minute EEG recordings (eyes-open/closed) were de-artifacted to calculate absolute power z-scores. Results validated across ages 6-60 (55 sets of z-scores per subject). Acceptance criteria (R-squared ≥ 0.8) met. Non-clinical testing included static/dynamic software analysis using simulated signals to verify frequency and power output accuracy.
Technological Characteristics
Software-based analysis tool; proprietary DLL implementation. Performs FFT-based spectral analysis (delta, theta, alpha, beta bands). Generates >5,000 measures including absolute/relative power, asymmetry, and coherence. Compares data against an age-regressed normative database (1,482 eyes-closed samples; 1,231 eyes-open samples). Operates on 19 monopolar and 171 bipolar derivations. Software level of concern: moderate.
Indications for Use
Indicated for qualified medical or clinical professionals to perform post-hoc statistical evaluation of human EEG data. No specific patient population age or disease state contraindications provided, though use requires professional clinical judgment.
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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July 1, 2018
BrainMaster Technologies, Inc. % Maria F. Griffin Senior Consultant mdi Consultants, Inc. 55 Northern Blvd. Suite 200 Great Neck, New York 11021
Re: K171414
Trade/Device Name: qEEG-Pro Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OLU Dated: April 11, 2017 Received: May 15, 2017
Dear Maria F. Griffin:
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. 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 801); medical device reporting of medical device-related adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
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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 http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/) and CDRH Learn (http://www.fda.gov/Training/CDRHLearn). 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 (http://www.fda.gov/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
For Carlos L. Peña, PhD, MS Director Division of Neurological and Physical Medicine Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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## Indications for Use
510(k) Number (if known) K171414
Device Name qEEG-Pro
Indications for Use (Describe)
The qEEG-Pro System is to be used by qualified clinical professionals for the statistical evaluation of the human electroencephalogram (EEG).
| Type of Use (Select one or both, as applicable) | |
|-------------------------------------------------|--|
|-------------------------------------------------|--|
X Prescription Use (Part 21 CFR 801 Subpart D)
| Over-The-Counter Use (21 CFR 801 Subpart C)
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# K171414 510(k) SUMMARY
I. SUBMITTER BrainMaster Technologies, Inc. 195 Willis Street, Suite 3 Bedford, OH 44146
| Contact Person: | Tom Collura, President |
|-----------------|------------------------|
| Tel: | 440-232-6000 ext. 205 |
Date Prepared: June 29, 2018
#### II. DEVICE
| Name of Device: | qEEG-Pro |
|----------------------|---------------------------------------------------------|
| Common Name: | Normalizing Quantitative Electroencephalograph Software |
| Classification Name: | Electroencephalograph |
| Regulatory Class: | II |
| Product Code: | OLU |
#### III. PREDICATE DEVICE
NeuroGuide Analysis System (NAS), K041263
#### IV. DEVICE DESCRIPTION
qEEG Pro Database (QPD) 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 QPD 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, power asymmetry, and coherence for 19 monopolar and 171 selected bipolar derivations of the EEG. In all over 5,000 measures are derived for comparison against
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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.
#### INDICATIONS FOR USE V.
The qEEG-Pro System is to be used by qualified medical or qualified clinical professionals for the statistical evaluation of the human electroencephalogram (EEG).
### COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH PREDICATE VI. DEVICE
| Item | qEEG-Pro | NeuroGuide Analysis System<br>(NAS) K041263 |
|---------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Indications for<br>Use | The qEEGpro system is to be<br>used by qualified medical and<br>qualified clinical professionals<br>for the post-hoc statistical<br>evaluation of the human<br>electroencephalogram (EEG).<br>Rx-only | The NAS system is to be used by<br>qualified medical and qualified<br>clinical professionals for the<br>post-hoc statistical evaluation of<br>the human electroencephalogram<br>(EEG).<br>OTC |
| EEG data<br>comparison<br>against normative<br>database | Yes; 1482 samples (eyes-<br>closed);1231 subjects (eyes-<br>open) | Yes; 625 samples |
| EEG Spectral<br>Analysis | Yes; 4 frequency bands (delta,<br>theta, alpha, and beta) | Yes; 4 frequency bands (delta,<br>theta, alpha, and beta) |
| Age Range<br>Included in the<br>Normative<br>Database | 4-82 years | 2 months-82 years |
| Product code | OLU | OLU |
| Classification | 882.1400 | 882.1400 |
| Visual Display of<br>EEG | Yes | Yes |
| Software | Proprietary via DLL | Proprietary via DLL |
#### PERFORMANCE DATA VII.
The following performance data were provided in support of the substantial equivalence determination.
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## Non-Clinical Testing
Software documentation up to a moderate level of concern was submitted which included validation performance 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 by examination 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 use of the device are known if the qEEG-Pro 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 artifacted EEG epochs, or selecting EEG representative of other states, such as drowsiness or eyes-open EEG when comparing to an eyes-closed database, 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.
## Clinical Testing
Clinical testing of the subject device included a study of 3 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 qEEG-Pro produces results sufficiently in agreement with the predicate devices and that the R-squared factor shall be 0.8 or better. Additionally, the observed range of results obtained from the predicate devices shall be used to verify that the qEEG-Pro produces results in agreement with the results obtained from the predicate device. The pre-defined acceptance criteria were met as 9-minute EEG recordings for eyes closed and open of the subjects (1 pediatric 9 years, 2 adult 48 and 46 both male and female) 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 6 and 60, resulting in 55 sets of zscores for each subject's EEG sample which were compared with the predicate device's output and found to also be similar.
#### VIII. CONCLUSIONS
The qEEG-Pro 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
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description, IFU, and performance testing, the qEEG-Pro 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.