K964750 · Marquette Electronics, Inc. · LOS · Feb 21, 1997 · CV
Device Facts
Record ID
K964750
Device Name
EAGLE 4000 PATIENT MONITOR
Applicant
Marquette Electronics, Inc.
Product Code
LOS · CV
Decision Date
Feb 21, 1997
Decision
SESE
Submission Type
Traditional
Attributes
Pediatric
Indications for Use
The Marquette Eagle 4000 Patient Monitor is designed to monitor and display patient data. Its design allows the operator to adjust parameter alarm settings that would audibly and visually notify the operator when a violation occurs. The option is provided for printing of information by a paper recorder. Use of the Marquette Eagle 4000 Patient Monitor is intended for patient populations including: adult, pediatric, and/or neonatal. Use of the Marquette Eagle 4000 Patient Monitor is not recommended for use in patient's home or residence, during patient transport, or when it has not been ordered by a physician or other qualified medical personnel. Use of the Marquette Eagle 4000 Patient Monitor is intended for operating room (OR), post anesthesia recovery, critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care. These departments are typically located in hospitals or may be located in outpatient clinics or free standing surgical centers. It is intended for use by physicians, physician assistants, registered nurses, certified registered nurse anesthetists, or other hospital personnel trained in the use of the equipment.
Device Story
Patient monitoring system; inputs include ECG, invasive/non-invasive blood pressure, SpO2, temperature, respiration, and cardiac output signals. Device processes physiological data to display real-time values and waveforms; includes 12-lead ECG analysis (12 SL program) for arrhythmia detection. Outputs include visual/audible alarms for parameter violations and printed reports via paper recorder. Used in hospital departments (OR, ICU, recovery) and outpatient clinics; operated by physicians, nurses, and trained medical personnel. Assists clinicians in patient status assessment and clinical decision-making; provides continuous monitoring to improve patient safety in critical care environments.
Clinical Evidence
Bench testing only. Verification and validation testing performed comparing the Eagle 4000 to predicate devices. Results demonstrate equivalent or superior performance in accuracy for all monitored physiological parameters.
Technological Characteristics
Multi-parameter patient monitor; includes 12-lead ECG analysis (12 SL program). Parameters: ECG, invasive/non-invasive BP, SpO2, temperature, respiration, apnea, pulse, cardiac output. Connectivity: paper recorder output. Form factor: bedside monitor unit. Software: 12 SL ECG analysis algorithm.
Indications for Use
Indicated for monitoring physiological parameters (ECG, invasive/non-invasive BP, SpO2, temperature, respiration, apnea, pulse, cardiac output, arrhythmia) in adult, pediatric, and neonatal patients in clinical settings (hospitals, clinics, surgical centers). Not for home use or patient transport.
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K964750
# 510(k) Summary of Safety and Effectiveness
FEB 21 1997
## 1. Manufacturer/ Submitter
Marquette Medical Systems
8200 West Tower Avenue
Milwaukee, WI 53223 U.S.A.
Establishment Registration Number: 2124823
Contact Name/ Telephone Number:
Dianne Schmitz
Corporate Regulatory Affairs
Marquette Medical Systems
Phone: (414) 362-3230
Date: November 15, 1996
## 2. General Information
Common Usual Name
This device is commonly known as a patient monitoring system.
Trade Proprietary Name
Marquette's trade/ proprietary name for this device is the Eagle 4000 Patient Monitor.
Classification Name(s)
The Marquette Eagle 4000 Patient Monitor's classification names, classification panels, and regulation citations include:
* 21 CFR 870.1025 Detector and Alarm, Arrhythmia 74DSI
* 21 CFR 868.2375 Monitor, Breathing Frequency 73BZQ
* 21 CFR 868.2375 Monitor, (Apnea Detector) Ventilatory Effort 73FLS
* 21 CFR 870.1110 Monitor, Blood Pressure, Indwelling 74CAA
* 21 CFR 870.1130 Monitor, Blood Pressure, Non-Indwelling 74BXD
* 21 CFR 880.2910 Monitor, Temperature (with probe) 80BWX
* 21 CFR 870.1435 Monitor, Cardiac Output, Thermal (Balloon Type Catheter) 74KFN
* 21 CFR 870.2300 Monitor, Cardiac (Incl.) 74DRT
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cardiotachometer & rate alarm)
* 21 CFR 870.2700 Oximeter, Pulse 74DQA
## Device Classification
Both of the main predicate devices included parameters which are Class III parameters, and both devices were cleared to market via the 510(k) notification route. The modified device that is the subject of this 510(k) submission remains in Class III.
## Performance Standards
Performance standards (Section 514 of the Act) have not yet been established for the device that is the subject of this premarket notification submission.
## 3. Legally Marketed Predicate Device(s)
The Marquette Eagle 4000 Patient Monitor is substantially equivalent, with similar indications for use to the following devices which are currently legally marketed and in commercial distribution:
Marquette Eagle Monitor K920790
Marquette SL Series Tram Module K921669
## 4. Device Description
The Marquette Eagle 4000 Patient Monitor is a patient monitoring system that is designed to be used to monitor a patient's basic physiological parameters including: electrocardiography (ECG), invasive blood pressure, non-invasive blood pressure, oxygen saturation, temperature, respiration, apnea detection, pulse rate, cardiac output, and full arrhythmia analysis. The device now includes Marquette's 12 lead ECG Analysis program (commonly referred to as 12 SL).
## 5. Intended Use
The Marquette Eagle 4000 Patient Monitor is designed to monitor and display patient data. Its design allows the operator to adjust parameter alarm settings that would audibly and visually notify the operator when a violation occurs.
The option is provided for printing of information by a paper recorder.
Use of the Marquette Eagle 4000 Patient Monitor is intended for patient populations including: adult, pediatric, and/or neonatal.
Use of the Marquette Eagle 4000 Patient Monitor is not recommended for use in patient's home or residence, during patient transport, or when it has not been ordered by a physician or other qualified medical personnel.
Use of the Marquette Eagle 4000 Patient Monitor is intended for operating room (OR), post anesthesia recovery, critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or
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neonatal intensive care. These departments are typically located in hospitals or may be located in outpatient clinics or free standing surgical centers. It is intended for use by physicians, physician assistants, registered nurses, certified registered nurse anesthetists, or other hospital personnel trained in the use of the equipment.
## 6. Conclusion
Verification and validation testing was done on the Eagle 4000 Patient Monitor and its predicate devices. Test results indicate that the Eagle 4000 Patient Monitor provides an equivalent level or better in performance, when compared to the legally marketed predicate devices when tested to the accuracy requirements as specified in the contents of the premarket notification submission.
Marquette Medical Systems has demonstrated that the Eagle 4000 Patient Monitor is as safe and effective, and performs substantially equivalent to the predicate devices.
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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.
