K971803 · Neurotronics, Inc. · MNR · Nov 12, 1997 · Anesthesiology
Device Facts
Record ID
K971803
Device Name
NEUROTRONICS POLYSOMNOGRAPHY SYSTEM 101
Applicant
Neurotronics, Inc.
Product Code
MNR · Anesthesiology
Decision Date
Nov 12, 1997
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 868.2375
Device Class
Class 2
Indications for Use
The device is intended for use in a sleep laboratory for the acquisition, display, storage, and analysis of polysomnography data from a polygraph with IRIG compatible outputs. The analysis features of the system are designed for subjects 13 years of age and older.
Device Story
POLYSMITH is a polysomnography data acquisition, analysis, display, and storage system. It accepts inputs from a polygraph with IRIG-compatible outputs via a connector block and PC-based analog-to-digital converter. The system automatically analyzes data to determine sleep stages (per 30-second epoch) and detect apneas and hypopneas. Used in sleep laboratories by physicians or sleep technicians. The software displays acquired data on a monitor for review and operator editing; generates sleep stage summary reports. Healthcare providers verify automated summary data against raw data displayed on the screen. The system assists in clinical diagnosis of sleep disorders; benefits include automated processing of complex polysomnography signals.
Clinical Evidence
Performance evaluated by comparing POLYSMITH against the Oxford SAC predicate using six all-night sleep records. Additionally, performance was compared to human scoring using two all-night sleep recordings from patients with severe sleep apnea. Data included EEG, EOG, EMG, airflow, and respiratory effort channels.
Technological Characteristics
PC-based system with enclosed analog-to-digital converter and connector block. Inputs: IRIG-compatible polygraph signals. Software runs on NT operating system. Connectivity: Standalone workstation. Analysis: Automated sleep staging and apnea/hypopnea detection.
Indications for Use
Indicated for use in sleep laboratories to assist qualified practitioners in diagnosing sleep disorders in patients 13 years of age and older. Requires physician or technician oversight. Requires specific input channels: 2 EEG, 2 EOG, chin EMG, leg EMG, airflow, 2 respiratory effort, and oxygen saturation.
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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# Nov 1 2 1997
#### 2. 510 (K) Summary
Applicant: Neurotronics Incorporated 20825 NE 132nd Ave. Route 1 Box 543 Waldo, FL 32694
Contact person: Jack R. Smith, Ph.D. 352-468-1006 Fax: 352-468-1006 e-mail: smith@neurotronics.com
### Device Name: POLYSMITH
## SUBSTANTIAL EQUIVALENCE
This new system, the POLYSMITH, is essentially equivalent, with the same intended use, to the Microtronics SAC system. same individual (Dr. Jack R. Smith) designed both The On October 6, 1986, the FDA notified Microtronics systems. K862527A) that their sleep-analyzing computer was (Re: determined to be substantially equivalent to devices in interstate commerce prior to May 28, 1976. Software for the processing of heart rate and respiration signals was subsequently added (FDA Ref. K863124). Microtronics was subsequently sold to Oxford Medical Instruments, and the Microtronics system is now known as the Oxford SAC system.
#### Device Description
Staturarian the land
POLYSMITH is a polysomnography data acquisition, analysis, display, and storage system, which accepts polysomnography data and allows the operator to view the data on the computer monitor. The device also automatically analyzes the data to determine the sleep stage for each thirty-second epoch and to detect apneas and hypopneas. The hardware consists of a personal computer with an enclosed analog-todigital converter and a connector block for conveniently connecting the input data leads. The device is designed to input data from a polygraph that has IRIG-compatible outputs. To use all analysis capabilities, there should be at least two EEG channels, two rapid eye movement channels (electro-occulograms), a chin EMG (electromyogram), a leg EMG, an ECG, airflow, two respiratory effort channels and an oxygen saturation channel. The software, which is running under the NT operating system, will display all of the acquired data on the computer screen for reviewing and operator editing. The automated analysis feature, designed tor subjects 13 years of age and older, generates multiple reports, including a sleep stage summary, describing the sleep data.
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#### Intended Use
The device is intended for use in a sleep laboratory for the acquisition, display, storage, and analysis of polysomnography data from a polygraph with IRIG compatible outputs. The analysis features of the system are designed for subjects 13 years of age and older.
#### Warning:
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The POLYSMITH software derives a description of a night's sleep from raw polysomnography data presented to the system. It is possible for the summary data to be incorrect for reasons including bad or missing polysomnography data, power failure, inaccurate calibration, and clinical data, to which the system has not been exposed. The POLYSMITH maintains all of the raw data. All summary data should be verified by examining the raw data on the computer monitor. The data can be viewed with the same resolution as a 10mm/sec. polygraph recording by viewing the data in the 10-second screen display mode. Since some of the sleep-staging criteria are based on specified amplitude levels, the EEG and EOG signals must be calibrated for accurate sleep It is recommended that a signal with known staging. waveform characteristics, such as a calibration signal, be included at the beginning or end of the recording as verification that the calibration was done.
#### Assessment of Performance Data
The device performance was compared with that of a predicate device, the Oxford SAC system. The system performance was evaluated by analyzing six all-night sleep records recorded to optical disk at the Henry Ford Sleep Diagnostic Center (HFSDC) in Detroit, Michigan and comparing the results obtained with the predicate device. In addition, the device performance was compared to human scoring, using two allnight sleep recordings, from the HFSDC, of patients with severe sleep apnea. Each recording contains two EEG channels (central and occipital), two eye channels, a chin EMG channel, a leg EMG channel, an airflow channel, and one respiratory effort channel.
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Food and Drug Administration 9200 Corporate Boulevard Rockville MD 20850
NOV 1 2 1997
Jack R. Smith, Ph.D. Neurotronics Incorporated 4609 NW 6th Street, B-5 Gainesville, Florida 32609
Re : K971803 Polysmith Regulatory Class: II (two) Product Code: 73 MNR Dated: August 18, 1997 Received: August 20, 1997
Dear Dr. Smith:
We have reviewed your Section 510(k) notification of intent to market the device referenced above and we have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to 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, Druq, and Cosmetic Act (Act). 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 (Premarket Approval), 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 895. A substantially equivalent determination assumes compliance with the current Good Manufacturing Practice requirements, as set forth in the Quality System Regulation (QS) for Medical Devices: General requlation (21 CFR Part 820) and that, through periodic (QS) inspections, the Food and Drug Administration (FDA) will verify such assumptions. Failure to comply with the GMP regulation may result in requlatory action. In addition, FDA may publish further announcements concerning your device in the Federal Register. Please note: this response to your premarket notification submission does not affect any obligation you might have under sections 531 through 542 of the Act for devices under the Electronic Product Radiation Control provisions, or other Federal laws or regulations.
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Page 2 - Jack R. Smith, Ph.D.
This letter will allow you to begin marketing your device as described in your 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 you desire specific advice for your device on our labeling regulation (21 CFR Part 801 and additionally 809.10 for in vitro diagnostic devices), please contact the Office of Compliance at (301) 594-4648. Additionally, for questions on the promotion and advertising of your device, please contact the Office of Compliance at (301) 594-4639. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). Other general information on your responsibilities under the Act may be obtained from the Division of Small Manufacturers Assistance at its toll-free number (800) 638-2041 or (301) 443-6597 or at its internet address "http://www.fda.gov/cdrh/dsmamain.html".
Sincerely yours,
Thomas J. Callahan
Thomas J. Callahan, Ph.D. Director Division of Cardiovascular, Respiratory, and Neurological Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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Page 1_of_ 1
510(k) Number (if known): K971803
Device Name: Polysmith
#### Indications For Use:
This device is intended for use in a sleep laboratory for the acqusition, display, storage, and analysis of polysomnography data obtained from a polygraph with IRIG compatible outputs. It's purpose is to assist a qualified sleep practitioner in the diagnosis of sleep disorders in patients 1.3 years of age and older. To use the analysis capabilities, there must be at least two EEG channels, two rapid eye movement channels (electroocculograms), a chin EMG (electromyogram) channel, a leg EMG channel, an airflow channel, two respiratory effort channels, and an oxygen desaturation channel. This device is to be used only under the direction of a physician or qualified sleep technician.
# (PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)
Concurrence of CDRH, Office of Device Evaluation (ODE)
Adol A. Ciark.
(Division Sign-Off) (Division Sign-Olt)
Division of Cardiovascular, Respiratory, Division ological Devices
510(k) Number _
Prescription Use_V (Par 21 CFR 801.109)
OR
Over-The-Counter Use__________________________________________________________________________________________________________________________________________________________
(Optional Format 1-2-96)
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.
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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.
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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.
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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.
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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.
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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.