K173690 · Natus Medical Incorporated Dba Excel-Tech Ltd. (Xltek) · OLV · Mar 9, 2018 · Neurology
Device Facts
Record ID
K173690
Device Name
Grass TWin
Applicant
Natus Medical Incorporated Dba Excel-Tech Ltd. (Xltek)
Product Code
OLV · Neurology
Decision Date
Mar 9, 2018
Decision
SESE
Submission Type
Special
Regulation
21 CFR 882.1400
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
This software is intended for use by qualified research and clinical professionals with specialized training in the use of EEG and PSG recording instrumentation for the digital recording, playback, and analysis of physiological signals. It is suitable for digital acquisition, display, comparison, analysis, and archiving of EEG potentials and other rapidly changing physiological parameters.
Device Story
Grass TWin is a software-only application for digital acquisition, display, analysis, and archiving of EEG and PSG physiological signals; used for Electroencephalography, Polysomnography, and Long-term Epilepsy Monitoring. Operated by qualified research and clinical professionals in clinical settings. Software interfaces with various Natus/XLTEK hardware recorders (e.g., AURA, Comet, SleepTrek3, Beehive Horizon). Input consists of physiological signals from compatible hardware; software processes these for visualization and review. Output includes digital waveforms and trends (e.g., Pulse Transit Time) displayed on a PC monitor. Clinicians use the output to interpret neurological and sleep-related data, supporting diagnostic and clinical decision-making. Benefits include efficient data management and analysis of rapidly changing physiological parameters.
Clinical Evidence
Bench testing only. No clinical data provided. Software verification and validation performed per IEC 62304, IEC 60601-1-6, and IEC 62366 standards. Results confirmed compliance with predetermined specifications and performance requirements.
Technological Characteristics
Software-only device; no hardware. Operates on Microsoft Windows 7 and Windows Server 2008. Connectivity via integration with Natus/XLTEK recording systems (AURA, Comet, SleepTrek3, Beehive Horizon). Features include PTT trend analysis and montage editor summation. Developed per IEC 62304 software life cycle processes.
Indications for Use
Indicated for qualified research and clinical professionals trained in EEG and PSG instrumentation for digital recording, playback, and analysis of physiological signals, including EEG potentials and other rapidly changing physiological parameters.
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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Natus Medical Incorporated DBA Excel-Tech Ltd. (XLTEK) Shane Sawall Manager, Regulatory Affairs 2568 Bristol Circle Oakville, Ontario L6H 5S1 CA
March 9, 2018
### Re: K173690
Trade/Device Name: Grass TWin Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OLV, GWQ Dated: February 12, 2018 Received: February 14, 2018
Dear Shane Sawall:
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 the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
For comprehensive regulatory information about medical devices and radiation-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,
# Michael J. Hoffmann -S
Carlos Peña, Ph.D. for 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) K173690
Device Name Grass® TWin®
#### Indications for Use (Describe)
This software is intended for use by qualified research and clinical professionals with specialized training in the use of EEG and PSG recording instrumentation for the digital recording, playback, and analysis of physiological signals. It is suitable for digital acquisition, display, comparison, and archiving of EEG potentials and other rapidly changing physiological parameters.
Type of Use (Select one or both, as applicable)
| <span style="font-size:10px">☒</span> Prescription Use (Part 21 CFR 801 Subpart D) | <span style="font-size:10px">☐</span> Over-The-Counter Use (21 CFR 801 Subpart C) |
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510(K) SUMMARY
Page 1 of 4
| Submission Date: | 30 November 2017 | | |
|-----------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------------------------|
| Submitter: | Natus Medical Incorporated DBA Excel-Tech Ltd. (XLTEK)<br>2568 Bristol Circle<br>Oakville, Ontario, L6H 5S1<br>Canada | | |
| Submitter and<br>Application<br>Correspondent | Mr. Shane Sawall<br>Phone: +1 (608) 829-8673<br>Fax: +1 (608) 829-8771<br>Email: shane.sawall@natus.com | | |
| Manufacturing Site: | Natus Medical Incorporated DBA Excel-Tech Ltd. (XLTEK)<br>2568 Bristol Circle<br>Oakville, Ontario, L6H 5S1<br>Canada | | |
| Trade Name: | Grass® TWin® | | |
| Common and<br>Classification<br>Name: | Standard Polysomnograph With Electroencephalograph | | |
| Classification<br>Regulation: | 21 CFR §882.1400 | | |
| Product Code: | OLV, GWQ | | |
| Substantially<br>Equivalent Devices: | New Model | Predicate 510(k)<br>Number | Predicate<br>Manufacturer / Model |
| | XLTEK / Grass TWin | K012976 | Grass-Telefactor<br>Division, Astro-Med,<br>Inc. / Grass-Telefactor<br>TWin PLUS |
| Device Description: | The Natus Medical Incorporated (Natus) DBA Excel-Tech Ltd.<br>(XLTEK) Grass® TWin ® (Grass TWin) is a comprehensive software<br>program intended for Electroencephalography (EEG), Polysomnography<br>(PSG), and Long-term Epilepsy Monitoring (LTM). TWin is incredibly<br>powerful and flexible, but also designed for easy and efficient day-to-day<br>use. Grass TWin is a software product only, and does not include any<br>hardware. | | |
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Technology
Comparison:
This software is intended for use by qualified research and clinical Intended Use: professionals with specialized training in the use of EEG and PSG recording instrumentation for the digital recording, playback, and analysis of physiological signals. It is suitable for digital acquisition, display, comparison, analysis, and archiving of EEG potentials and other rapidly changing physiological parameters.
> The Grass TWin employs the same technological characteristics as the predicate device.
| System Characteristic | Grass-Telefactor Division,<br>Astro-Med, Inc.<br>Grass-Telefactor TWin PLUS<br>(K012976) | XLTEK Grass TWin<br>(Proposed Device) |
|------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------|
| Intended Use | This software is intended for use<br>by qualified research and clinical<br>professionals with specialized<br>training in the use of EEG and<br>PSG recording instrumentation<br>for the digital recording.<br>playback, and analysis of<br>physiological signals. It is<br>suitable for digital acquisition,<br>display, comparison, analysis, and<br>archiving of EEG potentials and<br>other rapidly changing<br>physiological parameters. | Same. |
| Personal Computer<br>Operating System | Microsoft® Windows 98 or 2000 | Microsoft® Windows 7 and<br>Windows Server 2008 |
| Recording System<br>Compatibility | AURA PSG Wireless/Ambulatory<br>Recorder | AURA PSG Wireless/Ambulatory<br>Recorder |
| | AURA PSG Lite<br>Ambulatory/Wireless Sleep<br>Screener | AURA PSG Lite<br>Ambulatory/Wireless Sleep<br>Screener |
| | SleepTrek3 Portable Sleep<br>Screener | SleepTrek3 Portable Sleep<br>Screener |
| | Comet Series PSG | Comet and Comet-PLUS Series<br>PSG |
| | Comet Series EEG | Comet and Comet-PLUS Series<br>EEG |
| | AURA24 Ambulatory EEG | AURA24 Ambulatory EEG |
| | TREA Ambulatory EEG | TREA Ambulatory EEG |
| | Beehive Horizon for Long-Term<br>Monitoring | Beehive Horizon for Long-Term<br>Monitoring |
| Pulse Transit Time<br>(PTT) Trend Option | No | Yes |
| Montage Editor<br>Summation Feature | No | Yes |
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510(K) SUMMARY
Summary of Performance Testing:
Software
The Grass TWin software was designed and developed according to a robust software development process, and was rigorously verified and validated. Software information is provided in accordance with internal requirements and the following FDA guidance documents and standards:
- . The content of premarket submissions for software contained in medical devices, 11 May 05.
- Off-the-shelf software use in medical devices, 09 Sep 99. ●
- General principles of software validation; Final guidance for industry . and FDA staff, 11 Jan 02.
- Content of premarket submissions for management of cybersecurity in medical devices, 02 Oct 14.
- . Cybersecurity for networked medical devices containing off-the-shelf (OTS) software, 14 Jan 05
- . IEC 62304: 2006, Medical device software – Software life cycle processes
Results indicate that the Grass TWin software complies with its predetermined specifications, the applicable guidance documents, and the applicable standards.
Performance Testing - Bench The Grass TWin was verified for performance in accordance with internal requirements and the applicable clauses of the following standards:
- . IEC 60601-1-6: 2010, Am1: 2013, Medical electrical equipment -Part 1-6: General requirements for basic safety and essential performance – Collateral standard: Usability
- . IEC 62366: 2007, Am1: 2014, Medical devices – Application of usability engineering to medical devices.
Results indicate that the Grass TWin complies with its predetermined specifications and the applicable standards.
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510(K) SUMMARY
PAGE 4 of 4
Verification and validation activities were conducted to establish the Conclusion performance and safety characteristics of the device modifications made to the Grass TWin. The results of these activities demonstrate that the Grass TWin is as safe, as effective, and performs as well as or better than the predicate devices.
> Therefore, the Grass TWin is considered substantially equivalent to the predicate devices.
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.