BIOSENSOR HOLTER MONITOR SYSTEM SOFTWARE, MODEL 1005
Applicant
Biosensor Corp.
Product Code
DQK · Cardiovascular
Decision Date
Jun 14, 1999
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 870.1425
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
The Biosensor CMS Holter Analysis system is intended for patients requiring ambulatory monitoring is most frequently used for the indications below. 1. Evaluation of symptoms suggesting arrhythmia or myocardial ischemia. 2. Evaluation of symptoms suggesting arrhythmia in various types or groups of patients. 3. Evaluation of patients for ST segment changes. 4. Evaluation of a patient's response after resuming occupational or recreational activities (e.g., after M.I. or cardiac surgery.) 5. Clinical and epidemiological research studies. 6. Evaluation of patients with pacemakers 7. Reporting of time and frequency domain heart rate variability 8. Reporting of QT Interval.
Device Story
Biosensor CMS Holter Analysis System processes ambulatory ECG data; inputs include continuous ECG signals from patient recorders. System utilizes signal processing algorithms to perform QRS detection, VE detection, and ST segment measurement. To mitigate noise from myopotentials, baseline wander, and line interference, system employs beat averaging and optional high/low pass filters; users receive on-screen notifications when filters are active. Output consists of heart rate trends, arrhythmia reports, ST values, and other ECG parameters for physician review. Used in clinical settings by healthcare professionals to aid in diagnosis and management of cardiac conditions. System provides diagnostic information to support clinical decision-making regarding patient cardiac health.
Clinical Evidence
No clinical data provided. Evidence relies on adherence to established standards for Holter systems (ANSI/AAMI EC11-1982) and the requirement for diagnostic accuracy testing of QRS/VE detectors and ST measurement algorithms.
Technological Characteristics
Holter analysis system software; utilizes 05-40 Hz bandpass filters for line interference reduction; optional high-pass filters for baseline wander and low-pass filters for EMG interference; employs beat averaging for noise reduction; provides on-screen status notifications for active filters.
Indications for Use
Indicated for patients requiring ambulatory ECG monitoring for evaluation of symptoms suggesting arrhythmia or myocardial ischemia, ST segment changes, post-activity response (e.g., post-MI or cardiac surgery), pacemaker evaluation, heart rate variability, and QT interval assessment.
Regulatory Classification
Identification
A programmable diagnostic computer is a device that can be programmed to compute various physiologic or blood flow parameters based on the output from one or more electrodes, transducers, or measuring devices; this device includes any associated commercially supplied programs.
Submission Summary (Full Text)
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JUN 1 4 1999
## Section 2 - Safety and Effectiveness Summary and Certifications
## Safety
For safe use of Holter systems, labeling and documentation must be complete. Standards for these are also covered in ANSI/AAMI EC11-1982.
## Effectiveness
Holter analysis systems contain software, which must perform effectively, accurately, and reliably. Recommended standards and test methods for the performance of these systems are also compiled in detail in the Association for the Advancement of Medical Instrumentation draft standard for Holter systems.
In addition to these, because of lack of proper user training, problems may arise regarding the following:
(a) Lead placement (Correct positions for electrodes are explained in ECG textbooks such as "Harrison's Principles of Internal Medicine", Eds. R.G. Petersdorf, R.D. Adams, E. Braunwald, K.J. Isselbacher, J.B. Martin and J.D. Wilson, 10th edition, pp: 1320-21. McGraw Hill, 1983).
(b) Line Interference (A comprehensive reference list for causes and reduction methods for line interference is given in "A new technique for line interference monitoring and reduction in biopotential amplifiers", Y.Z. Ider and H. Koymen, IEEE Trans. Biomedical Engineering, Vol. 37, pp. 624-31, 1990.) Patient recorder hardware with 05-40 Hz bandpass filters can reduce partially or substantially an problems with line interference.
(c) EMG (myopotential) interference (A low pass filter may be provided as an option as too much muscle interference may be encountered during an Holter recording. Users should be notified continuously when this filter is in use, since low pass filters may affect the diagnostic value of the ECG recording information. The CMS Holter Analysis System provides such notification on screen.)
(d) Baseline wander (High pass correction filters may be provided as an option as baseline wander may occur during Holter recording. Users should be notified continuously when this filter is used, since baseline wander filters may affect the diagnostic value of the recording. The CMS Holter Analysis System provides such notification on screen.)
(e) Averaging (In Holter systems, ST level changes must be accurately measured for each lead). Due to myopotential, baseline wander and other noise interference, such measurements cannot be reliably made using a single beat. Therefore, beats are averaged and measurements are made from average beats to minimize errors.
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(f) Diagnostic Accuracy (In Holter systems that measure heart rate, arrhythmia content, ST values and other ECG parameters, the algorithms used to make such measurements and report trends to the physician influence the quality of information provided to the physician. Testing of the diagnostic accuracy of the ST measurements, QRS detector and VE detector are necessary to evaluate the value of the measurements and trends supplied to the physician for review.
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Image /page/2/Picture/1 description: The image shows the seal of the U.S. Department of Health & Human Services. The seal is circular and contains the words "DEPARTMENT OF HEALTH & HUMAN SERVICES • USA" around the perimeter. In the center of the seal is a stylized image of a caduceus, a symbol of medicine and health, with a staff entwined by two snakes.
Public Health Service
Food and Drug Administration 9200 Corporate Boulevard Rockville MD 20850
JUN 1 4 1999
Mr. Steve Springrose Vice President Biosensor Corporation 11481 Rupp Drive Burnsville, MN 55337
Re: K990956 Biosensor Holter Monitor System Software, Model 1005 Requlatory Class: II (two) Product Code: DQK Dated: March 17, 1999 Received: March 22, 1999
Dear Mr. Springrose:
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 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). 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 Requlation (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 regulatory action. In addition, FDA may publish further announcements
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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.
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, ² Misbranding by reference to premarket notification? (21CFR 807.97). Other qeneral 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/dsma/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): | K990956 |
|---------------------------|-------------------------|
| Device Name: | Ambulatory (Holter) ECG |
・・
Indications For Use:
Ambulatory (Holter) ECG intended use:
The Biosensor CMS Holter Analysis system is intended for patients requiring anbulatory The Biosensor Citis Hotel Analysis 35 oven 10 monitoring is most frequently used for the indications below.
1. Evaluation of symptoms suggesting arrhythmia or myocardial ischemia.
1. Evaluation of Symptoms suggesting army announce of the works or groups of patients.
3. Evaluation of patients for ST segment changes.
4. Evaluation of a patient's response after resuming occupational or recreational activities (e.g., after M.I. or cardiac surgery.)
5. Clinical and epidemiological research studies.
6. Evaluation of patients with pacemakers
7. Reporting of time and frequency domain heart rate variability
8. Reporting of QT Interval.
(PLEASE DO NOT WRITE BELOW THIS LINE - CONTINUE ON ANOTHER PAGE IF NEBDED)
Concurrence of CDRH Office of Device Evaluation (ODE)
(Division Sign-Off) Division of Cardiovascular, Respiratory, and Neurological Devic 510(k) Number
Prescription Use
(Per 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.
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.
