K962811 · Spacelabs Medical, Inc. · DXJ · Jun 24, 1997 · Cardiovascular
Device Facts
Record ID
K962811
Device Name
SPACELABS MEDICAL MULTI-DISCLOSURE WORKSTATION
Applicant
Spacelabs Medical, Inc.
Product Code
DXJ · Cardiovascular
Decision Date
Jun 24, 1997
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 870.2450
Device Class
Class 2
Indications for Use
The SpaceLabs Multi-Disclosure Workstation is intended for use with the SpaceLabs PCMS monitoring network to provide for the collection, review, editing, printing and archiving of waveform data records (full disclosure and strips), 12-lead ECG diagnostic reports, and alarm recordings collected by monitors on the network.
Device Story
Workstation functions as a PC-based accessory to SpaceLabs PCMS network; connects via Ethernet. Inputs include patient waveform data, 12-lead ECG reports, and alarm recordings from network-connected monitors. Software processes data for on-screen review, editing, and printing. Used by clinicians in clinical settings to manage patient records; provides full-disclosure waveform review and side-by-side comparisons of stored data. Does not perform automated physiological analysis; serves as a data management and archival tool to support clinical decision-making through historical data review.
Clinical Evidence
Bench testing only. System underwent safety and performance testing to ensure functional requirements and specifications were met. Hardware components comply with applicable industry and safety standards.
Technological Characteristics
Pentium-based PC running Windows NT; SVGA monitor, laser printer, keyboard, optional mouse and CD-ROM drive. Ethernet connectivity to PCMS network. Software-based data management system. No physiological analysis algorithms. Sterilization not applicable.
Indications for Use
Indicated for clinical use in a network environment to collect, store, display, edit, and print patient waveform data, 12-lead ECG reports, and alarm recordings from a Patient Care Management System (PCMS).
Regulatory Classification
Identification
A medical cathode-ray tube display is a device designed primarily to display selected biological signals. This device often incorporates special display features unique to a specific biological signal.
Predicate Devices
Hewlett-Packard M1251A Full Disclosure Review System (K905788)
Marquette Muse Cardiology Management System (K840932)
Submission Summary (Full Text)
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K962811

15220 N.E. 40th Street
P.O. Box 97013
Redmond, Washington 98073-9713
206-882-3700
JUN 24 1997
510(k) SUMMARY
SpaceLabs Medical Multi-Disclosure Workstation
1. Submitter's Name
SpaceLabs Medical Inc.
15220 N.E. 40th Street
Redmond, WA 98073
Telephone: (206) 882-3913
Facsimile: (206) 867-3550
2. Name of Device
SpaceLabs Medical Multi-Disclosure Workstation
Classification: Display, Cathode-Ray Tube; 74DXJ; 21 CFR 870.2450
3. Predicate Device(s)
The SpaceLabs Medical Multi-Disclosure Workstation is an accessory to the SpaceLabs Medical PCMS network to offer support for the collection, review, editing, archiving and printing of patient waveform data available from the network. This device is substantially equivalent to workstations currently marketed by Hewlett-Packard Company and Marquette Electronics, Inc. Hewlett-Packard markets the M1251A Full Disclosure Review System (K905788) which collects waveform data and provides support for the review, editing, archival and printing of this data. The Marquette Muse Cardiology Management System (K840932) includes these features for the on-line review of 12-lead ECG reports and their subsequent archival for later retrieval.
4. Device Description
The SpaceLabs Medical Multi-Disclosure Workstation is a personal computer accessory with an Ethernet link to the SpaceLabs Medical PCMS network.
The Workstation is a software application for a generally-available Pentium® based computer system with an SVGA monitor, laser printer and keyboard, with optional mouse and CD-ROM drive, running Windows NT.
The SpaceLabs Medical proprietary software consists of modules for monitoring census information on the PCMS network, collecting waveform, 12-lead and alarm data from the network, processing waveform data for display, printing reports, and managing patient information.
The system provides full-disclosure waveform data, which provides a means to review continuous waveform data from a patient for one or more channels of data. Strips or disclosure print-outs of the data may be reviewed on-screen, printed, or saved for archival purposes and later side-by-side comparisons
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of previously stored data. The user may select from a variety of viewing and printing formats.
5. Intended Use
The SpaceLabs Multi-Disclosure Workstation is intended for use with the SpaceLabs PCMS monitoring network to provide for the collection, review, editing, printing and archiving of waveform data records (full disclosure and strips), 12-lead ECG diagnostic reports, and alarm recordings collected by monitors on the network.
6. Comparison of Technological Characteristics
We consider the device to be substantially equivalent to workstations currently marketed by Hewlett-Packard Company and Marquette Electronics, Inc. The design, components used in the workstation system, and energy source are similar to its predicate devices.
All systems provide an interface to a network system in order to provide basic collection, display, review, editing, printing, and archival capabilities for the management of patient data. The only significant difference between the Multi-Disclosure Workstation and these comparable systems is in the number of additional features provided by the Hewlett-Packard and the Marquette workstations when compared to the SpaceLabs Medical Workstation. Specifically, the SpaceLabs Medical Workstation does not support non-network applications and provides no analysis of physiological data.
7. Testing
The SpaceLabs Medical Multi-Disclosure Workstation has been subject to extensive safety and performance testing prior to release. Final testing for the system includes various performance tests designed to ensure that the device meets all of its functional requirements and performance specifications. Safety tests have further been performed by the various manufacturers of the required hardware components to ensure the system complies to applicable industry and safety standards.
In conclusion, the SpaceLabs Medical Multi-Disclosure Workstation is as safe and effective as the predicate devices and raises no new issues.
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DEPARTMENT OF HEALTH & HUMAN SERVICES
Public Health Service
Food and Drug Administration
9200 Corporate Boulevard
Rockville MD 20850
JUN 24 1997
Mr. Russ Garrison
SpaceLabs Medical, Inc.
15220 N.E. 40th Street
P.O. Box 97013
Redmond, Washington 98073-9713
Re: K962811
SpaceLabs Medical Multi-Disclosure Workstation
Regulatory Class: II (two)
Product Code: 74 DXJ
Dated: March 24, 1997
Received: March 26, 1997
Dear Mr. Garrison:
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, Drug, 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 regulation (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 regulatory 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 - Mr. Russ Garrison
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, 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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PREMARKET NOTIFICATION
SpaceLabs Medical Multi-Disclosure Workstation
INDICATIONS FOR USE
510(k) Number: Pending
Device Name: SpaceLabs Medical Multi-Disclosure Workstation
Indications for Use:
1. Data Access - Provides the user with the means to collect multiple patient data directly from a hardwired or telemetry Patient Care Management System (PCMS) monitoring network.
2. Data Storage - Allows the user to retain up to 48 patient waveforms for up to 48 hours.
3. Data Display - Allows the user to pull data from storage or during continuous monitoring by patient and parameter.
4. Data Editing - Provides the user with the means to edit 12-lead ECG waveform data and interpretation text from SpaceLabs Medical 12-lead modules connected to the Patient Care Management System (PCMS) monitoring network.
5. Data Printing - Allows the user to print time annotated waveforms and patient data on paper for review or archive history.
M. Pugl
(Division Sign-Off)
Division of Cardiovascular, Respiratory, and Neurological Devices
510(k) Number: Y462811
Prescription Use
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.