NOGA AUTOMATED SLEEP STUDY SCORING AND DATA MANAGEMENT SYSTEM
Applicant
Widemed, Ltd.
Product Code
MNR · Anesthesiology
Decision Date
May 5, 2007
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 868.2375
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
The Noga Automated Sleep Study Scoring and Data Management System is a computer program (software) intended for use as an aid for the diagnosis of respiratory related sleep disorders. The Noga System is intended to be used for analysis, display, redisplay (retrieve), summarize, reports generation and networking of physiological data received from a physiological activity monitoring device. Physiological data includes: ECG, SpO2, EtCO2 and Impedance respiration. This system is to be used under the supervision of a physician.
Device Story
Noga System is a web-based software application for analyzing physiological data from third-party monitoring devices. Inputs include ECG, SpO2, EtCO2, and impedance respiration signals. Software converts raw data into a standard format, performs automated scoring of sleep stages (wake/sleep), detects respiratory events (apnea/hypopnea), and calculates Apnea/Hypopnea Index (AHI). System generates summary reports and displays data via standard web browser. Used in clinical settings under physician supervision to assist in diagnosing respiratory-related sleep disorders. Benefits include automated analysis and efficient data management, aiding clinical decision-making by providing objective sleep metrics.
Clinical Evidence
Clinical study validated Noga System accuracy against gold-standard PSG and Morpheus predicate. Primary endpoints included AHI calculation and respiratory event detection. Results showed high AHI correlation across devices. For AHI ≥15 cutoff, Noga demonstrated 100% sensitivity and 92.7% specificity vs. gold-standard, and 92.8% sensitivity and 94.8% specificity vs. Morpheus predicate.
Technological Characteristics
Web-based software program. Processes third-party physiological signals (ECG, SpO2, EtCO2, Impedance). Architecture based on Morpheus software with modular layering for maintenance. Operates on standard personal computers via Internet Explorer. Complies with IEC 60601-1-4 (programmable medical systems) and ISO 14971 (risk management).
Indications for Use
Indicated for use as an aid in the diagnosis of respiratory-related sleep disorders in patients undergoing physiological monitoring. To be used under physician supervision.
Regulatory Classification
Identification
A breathing (ventilatory) frequency monitor is a device intended to measure or monitor a patient's respiratory rate. The device may provide an audible or visible alarm when the respiratory rate, averaged over time, is outside operator settable alarm limits. This device does not include the apnea monitor classified in § 868.2377.
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# 510(K) SUMMARY
# 510(K) Number K_K070326
MAY 2 5 2007
# 5.1 Applicant's Name: WideMed LTD 10, ha'sadnaot st. Herzliya 46733, Israel Tel: +972 9 951 4159 Fax: +972 9 951 4158
5.2 Contact Person:
Dorit Winitz, Ph.D. Biomedical Strategy (2004) Ltd. 7 Jabotinsky Street. Ramat Gan 52520, Israel Tel: +972-3- 6123281 Fax: +972-3-6123282 Mail: dorit@ebms.co.il
5.3 Date Prepared: January 2007
5.4 Trade Name:
Noga Automated Sleep Study Scoring and Data Management System
5.5 Classification Name: Ventilatory Effort Recorder / Breathing Frequency Monitor
5.6 Medical Specialty: Anesthesiology
5.7 Product Code: Ventilatory Effort Recorder, MNR.
5.8 Device Class: Class II
5.9 Regulation Number: 868.2375
5.10 Panel: Anesthesiology
#### 5.11 Predicate Device:
- 1. The Morpheus M 1 (WideMed, Ltd.), cleared under K022506.
- 2. The Silent Night V (Sleep Solutions, Inc.), cleared under K000253.
- 3. Gold standard PSG manual scoring (e.g., manual scoring of ALICE-5 PSG, cleared under K040595)
5-3
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# 5.15 Substantial Equivalence:
# Intended Use
With regard to its intended use, the Noga System is substantially equivalent to the combination of its predicate devices, all enable an automatic analysis of physiological acquired signals and are intended for providing information on sleep disordered breathing (SDB) for use as an aid for the diagnosis of respiratory related sleep disorders.
# Technological Characteristics and Mode of Operation
Similarly to Morpheus, the Noga System is a computer program analyzing third party's physiological input signals. Both devices convert these raw data signals from their respective recorder device [PSG (Morpheus) or physiological activity monitoring device (Noga)} into WideMed standard format prior to analysis.
The Noga software program is based on the Morpheus software program with the changes required to support the analysis of limited set of signals. The core software components and architecture are substantially equivalent, while minor differences include changes in modularity and layering that do not have a functional consequence, but were implemented to enhance software maintenance and reliability.
# Performance Testing
Software verification and validation testing was conducted to evaluate the performance of the Noga System and to verify that it performs according to its specifications described in the Software Requirements Specifications (SRS).
A clinical study was conducted to validate the accuracy of the Noga System to detect respiratory related sleep disorders against both a gold-standard PSG and the Morpheus predicate device. The number of respiratory events and the total sleep time as measured by the Noga System with regard to the gold-standard result in an accurate representation of AHI. Statistical analysis of the test results indicated high correlation of AHI across devices. Further analysis indicated that the sensitivity of Noga for a cutoff of AHI ≥15 is 100% and specificity is 92.7% when compared to gold-standard, and 92.8% sensitivity and 94.8% specificity when compared to the Morpheus predicate.
#### Summary
Based on the performance testing results, including software verification and validation process and the analysis of the similarities and differences, WideMed Ltd believes that the Noga System is substantially equivalent to its predicates without raising new issues of safety or effectiveness.
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# 5.12 Performance Standards:
- 1. IEC 60601-1-4 + A1, Medical electrical equipment Part 1: General requirements for safety 4. Collateral Standard: Programmable electrical medical systems, Edition 1.1, 2000-4
- 2, ISO 14971-1, Application of risk management to medical devices, 2000.
# 5.13 Intended Use / Indication for Use:
The Noga Automated Sleep Study Scoring and Data Management System is a computer program (software) intended for use as an aid for the diagnosis of respiratory related sleep disorders.
The Noga System is intended to be used for analysis, display, redisplay (retrieve), summarize, reports generation and networking of physiological data received from a physiological activity monitoring device.
Physiological data includes: ECG, SpO2, EtCO2 and Impedance respiration
This system is to be used under the supervision of a physician.
## 5.14 Device Description:
The Noga Automated Study Scoring and Data Management System (Noga System) is a Web-based computer program (software), intended for use as an aid to the diagnosis of respiratory-related sleep disorders.
The Noga System is designed to process the raw signal data acquired by a third party physiological activity monitoring device in standard medical download format, analyze them, obtain the study's analysis results, generate summary reports, and display the signals' data and reports on a personal computer, using a standard Internet Explorer Browser.
Signals from the physiological activity monitoring device include the following:
- 에 ECG
- Impedance respiration 하
- EtCO2 트
- I SpO2
Scoring Analysis includes:
- 트 Apnea/Hypopnea Index (AHI)
- 에 Sleep Staging (Sleep - Wake stages, and Total Sleep Time)
- Respiratory Events Detection (Apnea and Hypopnea)
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# DEPARTMENT OF HEALTH & HUMAN SERVICES
Image /page/3/Picture/1 description: The image shows the logo for the U.S. Department of Health & Human Services. The logo is a circular seal with the words "DEPARTMENT OF HEALTH & HUMAN SERVICES - USA" around the perimeter. Inside the circle is an abstract image of an eagle.
ood and Drug Administration 9200 Corporate Boulevard Rockville MD 20850
WideMed Limited C/O Dorit Winitz, Ph. D. Regulatory Affairs Consultant BioMedical Strategy (2004) Limited 7 Jabotinsky Street Ramat-Gan 52520 ISRAEL
MAY 25 2007
Re: K070326
Trade/Device Name: Noga Automated Sleep Study Scoring and Data Management System Regulation Number: 21 CFR 868.2375 Regulation Name: Breathing Frequency Monitor Regulatory Class: II Product Code: MNR Dated: April 30, 2007 Received: May 3, 2007
Dear Dr. Winitz:
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.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to such 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.
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#### Page 2 - Dr. Winitz
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); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
This letter will allow you to begin marketing your device as described in your Section 510(k) premarket notification. The FDA finding of substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to proceed to the market.
If vou desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Office of Compliance at (240) 276-0120. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21CFR Part 807.97). You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (240) 276-3150 or at its Internet address http://www.fda.gov/cdrh/industry/support/index.html.
Sincerely yours,
Suite Y. Michaud MD
Chiu Lin, Ph.D. Director Division of Anesthesiology, General Hospital, Infection Control and Dental Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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# INDICATIONS FOR USE
510(k) Number (if known):
K070326
Device Name: Noga Automated Sleep Study Scoring and Data Management System
Indications for Use:
The Noga Automated Sleep Study Scoring and Data Management System is a computer program (software) intended for use as an aid for the diagnosis of respiratory related sleep disorders.
The Noga System is intended to be used for analysis, display, redisplay (retrieve), summarize, reports generation and networking of physiological data received from a physiological activity monitoring device.
Physiological data includes: ECG, SpO2, EtCO2 and Impedance respiration.
Prescription Use V (Part 21 CFR 801 Subpart D)
AND/OR
Over-The-Counter Use (21 CFR 801 Subpart C)
KO-703-26
(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE OF NEEDED)
Concurrence of CDRH, Office of Device Evaluation (ODE)
Page 1 of 1
ign-Off) Acting Chist
sion of Anesthesiology, General Hospital,
icon Control, Dental Devices
C(k) Number:
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.