K142693 · Zywie, Inc. · DPS · Feb 20, 2015 · Cardiovascular
Device Facts
Record ID
K142693
Device Name
ZywieAI Software Library
Applicant
Zywie, Inc.
Product Code
DPS · Cardiovascular
Decision Date
Feb 20, 2015
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 870.2340
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
The ZywieAI Software Library is intended for use by qualified medical professionals for the assessment of arrhythmias using historic ambulatory ECG data. The product supports downloading and analyzing data recorded in compatible formats from any device used for the arrhythmia diagnostics such as Holter, Event Monitor, MCT (Mobile Cardio Telemetry), or other similar devices when assessment of the rhythm is necessary. The ZywieAI Software Library can also be electronically interfaced, and perform analysis with data transferred from other computer based ECG systems, such as ECG management system. The software library provides ECG signal processing and analysis on a beat by beat basis, QRS Detection, Non-paced Arrhythmia Interpretation, PAC (Premature Atrial Contraction), Non-paced Heart Rate determination, Pause, Tachycardia, Bradycardia, Atrial Flutter/Fibrillation, Ventricular Flutter/Fibrillation, Ventricular Ectopic Beat detection, Ventricular Tachycardia, AV (Atrioventricular) Conduction Block, ST Change Episode detection, and Non-paced Ventricular Arrhythmia calls. The product can be integrated into computerized ECG monitoring devices. In this case the medical device manufacturer will identify the indication for use depending on the application of their device. The product cannot be used with potentially life-threatening arrhythmias which require inpatient monitoring. Verification of the output from ZywieAI Software is the responsibility of a trained healthcare professional or physician. The ZywieAI Software Library is used for analyzing ECG data for adult patient population.
Device Story
ZywieAI Software Library is an object library (callable functions) for automated ECG analysis. It ingests historic ambulatory ECG data from Holter, Event, or MCT monitors; processes signals via API or web service; and performs beat-by-beat analysis. Outputs include QRS detection, heart rate, and various arrhythmia interpretations (e.g., PAC, tachycardia, bradycardia, flutter/fibrillation, ST changes). Used by qualified medical professionals in clinical settings to support diagnostic decision-making. Healthcare providers review software-generated annotations to confirm rhythm assessments. Benefits include efficient analysis of large ECG datasets for outpatient cardiac monitoring.
Clinical Evidence
Bench testing only. Software verification and validation performed per FDA guidance for moderate level of concern. Performance validated against standardized databases: MIT-BIH Arrhythmia Database (MITDB), MIT-BIH Noise Stress Test Database (NSTDB), QT Database (QTDB), and European ST-T Database (ESCDB).
Technological Characteristics
Object library (compiled machine code/IDL) for integration into ECG monitoring systems. Operates via API or web service. Complies with ANSI/AAMI EC57:2012 (rhythm/ST segment algorithm testing) and IEC 62304:2006 (software lifecycle).
Indications for Use
Indicated for adult patients requiring assessment of arrhythmias using historic ambulatory ECG data, including those with symptoms like dizziness, syncope, dyspnea, palpitations, or those requiring drug monitoring, post-cardiac surgery monitoring, sleep-disordered breathing evaluation, or stroke/ischemia etiology investigation. Contraindicated for potentially life-threatening arrhythmias requiring inpatient monitoring.
Regulatory Classification
Identification
An electrocardiograph is a device used to process the electrical signal transmitted through two or more electrocardiograph electrodes and to produce a visual display of the electrical signal produced by the heart.
Predicate Devices
Monebo Automatic ECG Analysis and Interpretation Software Library (K062282)
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Public Health Service
Food and Drug Administration 10903 New Hampshire Avenue Document Control Center - WO66-G609 Silver Spring, MD 20993-0002
February 20, 2015
Zywie, Inc. % Jon Ward President and CEO AJW Technology Consultants, Inc. 445 Apollo Beach Blvd. Apollo Beach, Florida 33572
Re: K142693
> Trade/Device Name: ZywieAI Software Library Regulation Number: 21 CFR 870.2340 Regulation Name: Electrocardiograph Regulatory Class: Class II Product Code: DPS Dated: January 12, 2015 Received: January 13, 2015
Dear Jon Ward,
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. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to 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.
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
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with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical devicerelated adverse events) (21 CFR 803); 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.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Division of Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address
http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to
http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
You may obtain other general information on your responsibilities under the Act from the Division of Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address
http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.
Sincerely yours,
# Melissa A. Torres -S
For Bram D. Zuckerman, M.D. Director Division of Cardiovascular Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known): K142693
Device Name: ZywieAI Software Library
The ZywieAI Software Library is intended for use by qualified medical professionals for the assessment of arrhythmias using historic ambulatory ECG data. The product supports downloading and analyzing data recorded in compatible formats from any device used for the arrhythmia diagnostics such as Holter, Event Monitor, MCT (Mobile Cardio Telemetry), or other similar devices when assessment of the rhythm is necessary. The ZywieAI Software Library can also be electronically interfaced, and perform analysis with data transferred from other computer based ECG systems, such as ECG management system. The software library provides ECG signal processing and analysis on a beat by beat basis, QRS Detection, Non-paced Arrhythmia Interpretation, PAC (Premature Atrial Contraction), Non-paced Heart Rate determination, Pause, Tachycardia, Bradycardia, Atrial Flutter/Fibrillation, Ventricular Flutter/Fibrillation, Ventricular Ectopic Beat detection, Ventricular Tachycardia, AV (Atrioventricular) Conduction Block, ST Change Episode detection, and Non-paced Ventricular Arrhythmia calls.
The product can be integrated into computerized ECG monitoring devices. In this case the medical device manufacturer will identify the indication for use depending on the application of their device.
The product cannot be used with potentially life-threatening arrhythmias which require inpatient monitoring.
Verification of the output from ZywieAI Software is the responsibility of a trained healthcare professional or physician.
The ZywieAI Software Library is used for analyzing ECG data for adult patient population.
Prescription Use X Prescription Use X
AND/OR
Over-The-Counter Use (21 CFR 807 Subpart C)
# (PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE OF NEEDED)
Concurrence of CDRH. Office of Device Evaluation (ODE)
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# 510(k) SUMMARY (as required by 807.92)
#### I. SUBMITTER
Zywie, Inc. 12000 Findley Road, Suite 360 Johns Creek, GA 30097
Phone: 678-992-1941 Fax: 678-230-9196
Contact Person: Latha Ganeshan Date Prepared: September 19, 2014
# REGULATORY CORRESPONDENT
AJW Technology Consultants, Inc 445 Apollo Beach, Blvd Apollo Beach, FL 33572
Phone: 813-645-2855 Fax: 813-645-2856
Contact Person: Jon Ward, President Email: wardjp@ajwtech.com
#### II. DEVICE
Name of Device: ZywieAI Software Library Common or Usual Name: Automated ECG Analysis and Interpretation Software Classification Name: Electrocardiograph Device Panel: Cardiovascular Regulatory Class: II Product Code: DPS
#### III. PREDICATE DEVICE
The ZywieAI Software Library is substantially equivalent in intended use and similar technological characteristics of Monebo Automatic ECG Analysis and Interpretation Software Library cleared as part of K062282 and the IQmark Digital Holter which was cleared under K031466.
These predicates have not been subject to a design-related recall. No reference devices were used in this submission
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#### IV. DEVICE DESCRIPTION
The ZywieAI Software Library is an "object library". An object library is a collection of callable functions that have been compiled (or assembled) into machine code or Interactive Data Language (IDL) code for the computer on which they execute.
The basic software application reads the input ECG signals from a file into computer memory and passes that data to ZywieAI Software Library for analyzing, annotating, and creating output. This output is sent back to the basic software application where the output is written to a file. The read input signal may invoke some or all of the functions in the object library. An application program could be written to write input data to a file using web services. The same or a different application program could be written to consume the output file using web services.
The ZywieAI Software Library provides ECG signal processing, ORS Detection, Nonpaced Arrhythmia Interpretation, PAC, Non-paced Heart Rate determination, Pause, Tachycardia, Bradycardia, Atrial Flutter/Fibrillation, Ventricular Flutter/Fibrillation, Ventricular Ectopic Beat detection, Ventricular Tachycardia, AV Conduction Block, ST Change Episodes detection, Non-paced Ventricular Arrhythmia calls and rhythm interpretation.
The library can be accessed through an Application Program Interface (API) as a callable function or using a web service call. This allows the library to be used as an accessory to an ECG management application or as a stand-alone product.
Zywie will compile the ZywieAI Software Library as specified by an ECG device manufacturer. An object library will be created and delivered to the device manufacturer. who can then integrate it into application software for their ECG analysis. Typically the software library is used along with ECG monitoring devices and ECG management software for patients:
- > With symptoms that may be due to cardiac arrhythmias. These may include but are not limited to symptoms such as: a) dizziness or lightheadedness; b) syncope of unknown etiology in which arrhythmias are suspected or need to be excluded: and c) dyspnea (shortness of breath).
- A With palpitations with or without know arrhythmias to obtain correlation of rhythm with symptoms.
- > Who require monitoring effect of drugs to control ventricular rate in various atrial arrhythmias (e.g. atrial fibrillation)
- A Recovering from cardiac surgery who are indicated for outpatient arrhythmia monitoring
- A With diagnosed sleep disordered breathing including sleep apnea (obstructive, central) to evaluate possible nocturnal arrhythmias
- A Requiring arrhythmia evaluation of etiology of stroke or transient cerebral ischemia, possibly secondary to atrial fibrillation or atrial flutter
- A With co-morbid conditions such as hyperthyroidism or chronic lung disease
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#### V. INDICATIONS FOR USE
The ZywieAI Software Library is intended for use by qualified medical professionals for the assessment of arrhythmias using historic ambulatory ECG data. The product supports downloading and analyzing data recorded in compatible formats from any device used for the arrhythmia diagnostics such as Holter, Event Monitor, MCT (Mobile Cardio Telemetry), or other similar devices when assessment of the rhythm is necessary. The ZywieAI Software Library can also be electronically interfaced, and perform analysis with data transferred from other computer based ECG systems, such as ECG management system. The software library provides ECG signal processing and analysis on a beat by beat basis, QRS Detection, Non-paced Arrhythmia Interpretation, PAC (Premature Atrial Contraction), Non-paced Heart Rate determination, Pause, Tachycardia, Bradycardia, Atrial Flutter/Fibrillation, Ventricular Flutter/Fibrillation, Ventricular Ectopic Beat detection, Ventricular Tachycardia, AV (Atrioventricular) Conduction Block, ST Change Episode detection, and Non-paced Ventricular Arrhythmia calls.
The product can be integrated into computerized ECG monitoring devices. In this case the medical device manufacturer will identify the indication for use depending on the application of their device.
The product cannot be used with potentially life-threatening arrhythmias which require inpatient monitoring.
Verification of the output from ZywieAI Software is the responsibility of a trained healthcare professional or physician.
The ZywieAI Software Library is used for analyzing ECG data for adult patient population.
#### VI. COMPARISON OF TECHNOLIGICAL CHARACTERISTICS WITH THE PREDICATE DEVICES
The monitoring of basic physiological parameters is the technological principle for both the subject and predicate devices. At a high level, the subject and predicate devices are based on the following same technological characteristics:
# K062282 - Monebo Automated ECG Analysis and Interpretation Software
- Read raw ECG signal data and analyze
- device algorithms are proprietary software library and are server based 0
# K031466 - IQmark Digital Holter
- device algorithms are proprietary software library and are server/pc based .
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The following technological differences exist between the subject and predicate devices:
# K062282 - Monebo Automated ECG Analysis and Interpretation Software
- o Predicate device doesn't have the ST segment change detection capabilities
- . The predicate device reports "Insufficient data" for Pause, Tachycardia, and Bradycardia, whereas subject device testing was done using sufficient data from the MITDB (The MIT-BIH Arrhythmia Database), NSTDB (The MIT-BIH Noise Stress Test Database), QTDB (The QT Database -PhysioNet) & ESCDB (The European ST-T Database -PhysioNet)databases. Positive and Negative Predicative Accuracy cannot be calculated for Ventricular Flutter/Fibrillation because all records contain VF
# K031466 - IQmark Digital Holter
- . Predicate device doesn't have the ORS Detection. PAC, Tachycardia, Bradycardia Atrial and Ventricular Flutter/Fibrillation, Ventricular Tachycardia, AV Conduction Block, Non-paced Ventricular Arrhythmia calls capabilities
#### VII. PERFORMANCE DATA
The following performance date were provided in support of the substantial equivalence determination
# Software Verification and Validation Testing
Software verification and validation testing were conducted and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." The software for this device was considered as a "Moderate" level of concern, since a failure or latent flaw could directly result in minor injury to the patient or operator.
# Reference Standards
The ZywieAI Software Library meets the requirements of following performance standards in accordance with FDA Guidance for the content of Premarket Submission for Software Contained in Medical Devices Document for Class II Moderate Level of Concern:
- ANSI/AAMI EC57:20012 Testing and reporting performance results of ● cardiac rhythm and ST segment measurement algorithms
- IEC 62304:2006 Medical device software Software lifecvcle processes .
# VIII. CONCLUSIONS
The testing completed demonstrates that the ZywieAI Software Library exhibits comparable technical and functional characteristics to the predicate devices.
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Based on those characteristics, the ZywieAI Software Library is substantially equivalent to the predicate device in safety and effectiveness in addition to being intended for the same uses.
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.