Kinetic Software Library

{1} **FDA** U.S. FOOD & DRUG ADMINISTRATION October 23, 2026 Monebo Technologies, Inc. % George Hattub Senior Regulatory Affairs Project Manager Innolitics, LLC 1101 West 34th St. #550 Austin, Texas 78705 Re: K260640 Trade/Device Name: Kinetic Software Library Regulation Number: 21 CFR 870.2340 Regulation Name: Electrocardiograph Regulatory Class: Class II Product Code: DPS Dated: September 24, 2026 Received: September 24, 2026 Dear George Hattub: 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 (the 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. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. 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. U.S. Food & Drug Administration 10903 New Hampshire Avenue Silver Spring, MD 20993 www.fda.gov {2} K260640 - George Hattub Page 2 Before making any change significantly affecting the safety or effectiveness of the device, you must submit a new premarket notification in accordance with 21 CFR 807.81. Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download). Your device is also subject to, among other requirements, the Quality Management System Regulation (QMSR) (21 CFR Part 820), which includes, but is not limited to, ISO 13485 clause 7.3 (Design controls), ISO 13485 clause 8.3 (Nonconforming product), ISO 13485 clause 8.5.2 (Corrective action), and ISO 13485 clause 8.5.3 (Preventative action). Please note that regardless of whether a change requires premarket review, the QMSR requires device manufacturers to review and approve changes to device design and production (ISO 13485 clause 7.3 and ISO 13485 clause 7.5) and document changes and approvals in the Medical Device File (ISO 13485 clause 4.2.3). 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 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 (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the Quality Management System Regulation (QMSR) (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050. All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems. For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the {3} K260640 - George Hattub Page 3 Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100). Sincerely, KIMBERLY N. CROWLEY -S For: Jennifer Kozen Assistant Director DHT2A: Division of Cardiac Electrophysiology, Diagnostics, and Monitoring Devices OHT2: Office of Cardiovascular Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health Enclosure {4} DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration # Indications for Use Form Approved: OMB No. 0910-0120 Expiration Date: 06/30/2023 See PRA Statement below. 510(k) Number (if known) K260640 Device Name Kinetic Software Library Indications for Use (Describe) The Kinetic Software Library consists of a basic application for analyzing ECG data. It is intended for use by qualified medical professionals for assessing ECG data. The device supports analyzing data recorded from “wet/hydrogel electrodes” and a “modified lead II patch” device. The Kinetic Software Library provides ECG signal processing and analysis based on a time window, QRS detection, Ectopic Beat detection, QRS feature extraction, heart rate measurement, and rhythm analysis. The Kinetic Software Library is not intended for life supporting or sustaining systems or ECG monitoring and alarm devices. The Kinetic Software Library is intended for integration and use with other medical devices through an API. It is the responsibility of the device manufacturer to integrate the Kinetic library correctly and to ensure their ECG device has the correct regulatory approvals and is validated for their intended use. Type of Use (Select one or both, as applicable) ☑ Prescription Use (Part 21 CFR 801 Subpart D) ☐ Over-The-Counter Use (21 CFR 801 Subpart C) # CONTINUE ON A SEPARATE PAGE IF NEEDED. This section applies only to requirements of the Paperwork Reduction Act of 1995. # *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.* The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." FORM FDA 3881 (6/20) Page 1 of 1 PSC Publishing Services (301) 443-6740 EF {5} monebo 510(k) Summary Page 1 of 16 # 1. CONTACT INFORMATION | Company Name | Monebo Technologies, Inc. | | --- | --- | | Address | 1800 Barton Creek Blvd. Austin, TX 78735, USA | | Phone Number | +1.512.732.0235 ext. 123 | | Company Representative | Dale Misczynski, CEO | | Email | dale.misczynski@monebo.com | | Primary Contact | George Hattub Senior Regulatory Consultant at Innolitics | | Additional Contributor | J. David Giese, Partner at Innolitics | | Primary Contact Phone Number | +1.508-479-6116 | | Primary Contact Email | fda@innolitics.com | | Date Summary Prepared | October 22, 2026 | # 2. DEVICE INFORMATION Trade Name: Kinetic Software Library Common Name: ECG Software Library Classification Name: Electrocardiograph Regulation Number: 21 CFR §870.2340 Product Code(s): DPS # 3. PREDICATE DEVICE | Predicate Device Name | Monebo Automated ECG Analysis and Interpretation Software Library | | --- | --- | | Manufacturer | Monebo Technologies, Inc. | | 510(k) Number | K062282 | K260640 {6} | monebo | 510(k) Summary | Page 2 of 16 | | --- | --- | --- | | Product Code | DPS | | --- | --- | | Regulation Number | 21 CFR §870.2340 | | Regulation Name | Electrocardiograph | | Regulatory Class | Class 2 | | Review Panel | Cardiac Electrophysiology, Diagnostics, and Monitoring Devices (DHT2A) | ## 4. DEVICE DESCRIPTION ### 4.1 Description Like the predicate device which is the Monebo Automated ECG Analysis and Interpretation Software Library (K062282), the subject device, which is the Kinetic Software Library, is a SaMD (Software as a Medical Device). More specifically, it is designed to be integrated into another client's ECG medical device. The Kinetic Software Library does not have a user interface or produce a physical report. It is integrated into a client's ECG type of medical device via an API (Application Programming Interface). ### 4.2 Indications for Use The Kinetic Software Library consists of a basic application for analyzing ECG data. It is intended for use by qualified medical professionals for assessing ECG data. The device supports analyzing data recorded from “wet/hydrogel electrodes” and a “modified lead II patch” device. The Kinetic Software Library provides ECG signal processing and analysis based on a time window, QRS detection, Ectopic Beat detection, QRS feature extraction, heart rate measurement, and rhythm analysis. The Kinetic Software Library is not intended for life supporting or sustaining systems or ECG monitoring and alarm devices. The Kinetic Software Library is intended for integration and use with other medical devices through an API. K260640 {7} | monebo | 510(k) Summary | Page 3 of 16 | | --- | --- | --- | It is the responsibility of the device manufacturer to integrate the Kinetic library correctly and to ensure their ECG device has the correct regulatory approvals and is validated for their intended use. ### 4.3 Predicate Device vs. Subject Device Indications for Use The table below compares the indications for use of the Predicate Device versus the Subject Device: | Use | KINETIC Software Library Subject Device | Monebo Automated ECG Analysis and Interpretation Software Library (K062282) Predicate Device | | --- | --- | --- | | **Indications For Use** | The Kinetic Software Library consists of a basic application for analyzing ECG data. It is intended for use by qualified medical professionals for assessing ECG data. The device supports analyzing data recorded from “wet/hydrogel electrodes” and a “modified lead II patch” device. The Kinetic Software Library provides ECG signal processing and analysis based on a time window, QRS detection, Ectopic Beat detection, QRS feature extraction, heart rate measurement, and rhythm analysis. | The Automatic Arrhythmia Detection Software Library is intended for use by qualified medical professionals for assessing historic ambulatory ECG data. The product allows downloading and analyzing data recorded in compatible format by Holter or Event monitoring devices. The Automatic Arrhythmia Detection Software Library provides ECG signal processing and analysis on a beat-by-beat basis, QRS and Ventricular Ectopic Beat detection, and QRS feature extraction. | K260640 {8} | monebo | **510(k) Summary** | Page 4 of 16 | | --- | --- | --- | | | The Kinetic Software Library is not intended for life supporting or sustaining systems or ECG monitoring and alarm devices. The Kinetic Software Library is intended for integration and use with other medical devices through an API. It is the responsibility of the device manufacturer to integrate the Kinetic library correctly and to ensure their ECG device has the correct regulatory approvals and is validated for their intended use. | 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. | | --- | --- | --- | | **Intended User** | Software Engineer for integration | Software Engineer for integration | | **ECG Signal Processing** | The new product (library) will provide ECG signal processing and analysis based on a time window. | The Automatic Arrhythmia Detection Software Library provides ECG signal processing and analysis based on on a beat-by-beat basis, | | **Method of Calibration** | Both used a genetic algorithm to refine the parameters | Both used a genetic algorithm to refine the parameters | | **Principle of Operation** | Both use rule-based algorithms where the parameters have concrete, physical meaning and have values that are bound to physiologically meaningful ranges. | Both use rule-based algorithms where the parameters have concrete, physical meaning and have values that are bound to physiologically meaningful ranges. | K260640 {9} | monebo | 510(k) Summary | Page 5 of 16 | | --- | --- | --- | | Number of Parameters | ~1000 | ~100 | | --- | --- | --- | | Algorithm Adjustable by User | No | No | | Final Validation and Verification by User | Yes | Yes | | Programing Language | C/C++ | Delphi | | Deployment Mechanism | Complied as a shared object library | Complied as a shared object library | | Target Population | Adult patients and adolescents 18 years and above | Adult patients aged 21 | | Supported Lead Configuration | 1 Lead | 12 Leads | | Signal Acquisition | ECG Wet Electrode | ECG Wet Electrodes | | ECG Data Input | Receives ECG waveform data together with acquisition parameters such as sample rate, ADC gain, and ADC zero values. | Receives ECG waveform data together with acquisition parameters such as sample rate, ADC gain, and ADC zero values. | | Noise Handling and | Performs noise analysis and signal quality evaluation for the | Performs noise analysis and signal quality evaluation for the | K260640 {10} | monebo | 510(k) Summary | Page 6 of 16 | | --- | --- | --- | | Signal Quality Assessment | assessment of the integrity of the ECG signal and generates signal-quality metrics used to support reliable interpretation of subsequent processing results. | assessment of the integrity of the ECG signal and generates signal-quality metrics used to support reliable interpretation of subsequent processing results. | | --- | --- | --- | | Object Initialization | Initializes the processing components required for ECG analysis, including the ECG processor, beat classifier, P-wave finder, T-wave finder, QRS onset/offset detector, and output annotation modules. The subject algorithm additionally illustrates creation of the annotator object and associated software resources within the application framework. | Initializes the processing components required for ECG analysis, including the ECG processor, beat classifier, P-wave finder, T-wave finder, QRS onset/offset detector, and output annotation modules. The subject algorithm additionally illustrates creation of the annotator object and associated software resources within the application framework. | | Signal Processing by Sample | ECG library performs ECG processing on a time window basis of incoming waveform data and preparation of the signal for feature detection and classification. | The original algorithms processes ECG data on a sample-by-sample basis, allowing continuous analysis of incoming waveform data and preparation of the signal for feature detection and classification. | | Filtering | The subject algorithm similarly includes normalization and filtering functions before execution of the core annotation process | Applies signal filtering to reduce baseline wander, noise, and other artifacts. The predicate algorithm specifically identifies a 16th-order online FIR filter | K260640 {11} | monebo | **510(k) Summary** | Page 7 of 16 | | --- | --- | --- | | | | | | --- | --- | --- | | **Peak Detection** | Algorithm identifies significant ECG waveform peaks, particularly QRS complexes, which serve as the primary reference points for subsequent beat and rhythm analysis. | Algorithm identifies significant ECG waveform peaks, particularly QRS complexes, which serve as the primary reference points for subsequent beat and rhythm analysis. | | **Beat Classification** | Algorithm classifies detected beats according to ECG morphology and timing characteristics. This classification forms the basis for distinguishing normal beats from ectopic beats. | Algorithm classifies detected beats according to ECG morphology and timing characteristics. This classification forms the basis for distinguishing normal beats from ectopic beats. | | **Heart Rate Value and Change Calculation** | Algorithms calculate heart rate and evaluate changes in heart rate over time. These calculations contribute to rhythm analysis and support detection of clinically significant rhythm abnormalities. | Algorithms calculate heart rate and evaluate changes in heart rate over time. These calculations contribute to rhythm analysis and support detection of clinically significant rhythm abnormalities. | | **QRS Onset and Offset Determination** | Algorithms identify the onset and offset boundaries of the QRS complex. Accurate delineation of these intervals supports waveform characterization and rhythm interpretation. | Algorithms identify the onset and offset boundaries of the QRS complex. Accurate delineation of these intervals supports waveform characterization and rhythm interpretation. | K260640 {12} | monebo | 510(k) Summary | Page 8 of 16 | | --- | --- | --- | | Previous Beat Classification | Algorithm evaluates the relationship between the current beat and preceding beats. This temporal analysis improves rhythm classification and assists in identifying abnormal conduction patterns. | Algorithm evaluates the relationship between the current beat and preceding beats. This temporal analysis improves rhythm classification and assists in identifying abnormal conduction patterns. | | --- | --- | --- | | Atrial Fibrillation Testing | The algorithm performs atrial fibrillation detection by analyzing rhythm irregularity and ECG waveform characteristics associated with AF episodes. | The algorithm performs atrial fibrillation detection by analyzing rhythm irregularity and ECG waveform characteristics associated with AF episodes. | | P-Wave Searching | The algorithm searches for and characterizes P-wave activity. Detection of atrial activity assists in rhythm classification and differentiation of supraventricular and ventricular events. | The algorithm searches for and characterizes P-wave activity. Detection of atrial activity assists in rhythm classification and differentiation of supraventricular and ventricular events. | | PVC, Ventricular, and Other Arrhythmia Classification | The algorithm identifies premature ventricular contractions (PVCs), ventricular beats, and other abnormal beat morphologies. This classification contributes to arrhythmia detection and reporting. | The algorithm identifies premature ventricular contractions (PVCs), ventricular beats, and other abnormal beat morphologies. This classification contributes to arrhythmia detection and reporting. | K260640 {13} | monebo | 510(k) Summary | Page 9 of 16 | | --- | --- | --- | | Report File Generation | The library provides the following output: - Beats report - Rhythms report - Global beat report | The library provides the following output: - Beats report - Rhythms report - Global beat report | | --- | --- | --- | ### 4.4 Device Comparison Table The table below compares the features & characteristics of the Predicate Device versus the Subject Device: | | Internal Features & Characteristics | Kinetics Software Library (Subject Device) | Monebo AAISL K062282 (Predicate Device) | Conclusion | | --- | --- | --- | --- | --- | | Beats Detected | | | | | | 1 | P wave onset | yes | yes | same | | 2 | P wave peak | yes | yes | same | | 3 | P wave offset | yes | yes | same | | 4 | QSR onset | yes | yes | same | | 5 | R peak | yes | yes | same | | 6 | QSR offset | yes | yes | same | | 7 | T wave onset | yes | yes | same | | 8 | T peak | yes | yes | same | K260640 {14} monebo 510(k) Summary Page 10 of 16 | 9 | T offset | yes | yes | same | | --- | --- | --- | --- | --- | | Beat Type Classification | | | | | | 10 | V type | yes | yes | same | | 11 | S type | yes | no | Validated per EC57 & Intended Use unchanged | | 12 | Q type | yes | no | Intended Use unchanged | | 13 | N type | yes | yes | same | | Parameters Computed | | | | | | 14 | HR | yes | yes | same | | Interpretive Arrhythmias | | | | | | 15 | Normal Sinus Rhythm | yes | yes | same | | 16 | Bradycardia | yes | yes | same | | 17 | Tachycardia | yes | yes | same | | 18 | Premature Ventricular Complexes | yes | yes | same | | 19 | Atrial Premature Contraction | yes | yes | same | | 20 | Atrial Fibrillation or Flutter | yes | yes | same | | 21 | Ventricular Tachycardia | yes | yes | same | | 22 | Ventricular Trigeminy | yes | yes | same | | 23 | Ventricular Bigeminy | yes | yes | same | | 24 | Accelerated Idioventricular rhythm | yes | yes | same | K260640 {15} monebo 510(k) Summary Page 11 of 16 | 25 | Supraventricular Tachycardia | yes | yes | same | | --- | --- | --- | --- | --- | | Reports Provided | | | | | | 26 | Beats | Internal Report | Physical Report | Validated per EC57 & Intended Use unchanged | | 27 | Rhythms | Internal Report | Physical Report | Validated per EC57 & Intended Use unchanged | | 28 | Global Beat | Internal Report | Physical Report | Intended Use unchanged | The table below compares the overall attributes of the Predicate Device versus the Subject Device: | Overall Device Attributes | KINETIC Software Library Subject Device | Monebo Automated ECG Analysis and Interpretation Software Library (K062282) Predicate Device | Conclusion | | --- | --- | --- | --- | | Manufacturer | Monebo | Monebo | Same as Predicate | | Environment for use | Hospitals, Clinics, Medical Offices | Hospital, Clinics, Medical Offices | Same as Predicate | | Intended Patient Population | Adult patients and adolescents 18 years and above | Adult patients aged 21 | Similar | | Contraindications | Pediatrics for infants and children below 18 years | Pediatric use | Similar | K260640 {16} | monebo | **510(k) Summary** | Page 12 of 16 | | --- | --- | --- | | **Intended User** | Software Engineer for integration & Healthcare profession for ECG Results | Software Engineer for integration & Healthcare profession for ECG Results | Same as Predicate | | --- | --- | --- | --- | | **Physical Characteristics** | Software package-Operates on Windows, Linux & Android | Software package-Operates on Windows | Same as Predicate | | **Input** | ECG Signal | ECG Signal | Same as Predicate | | **Design and Incorporated Technology** | ECG Library with Analysis | ECG Library with Analysis | Same as Predicate | | **Output** | ECG Interpretation | ECG Interpretation | Same as Predicate | | **Reporting** | Results provided in digital format | Results displayed physical report | Similar in that the physical report was derived from digital information. | | **Safety** | Performance validated per EC57 | Performance validated per EC57 | Same as Predicate | #### 4.5 Summary of Technological Characteristics Comparison The Subject and Predicate device have very similar technological characteristics. Both devices are software only medical devices. The next intended user is a software engineer for integration into an ECG type medical device. The ultimate intended use is a healthcare profession who will be provided with information based upon analysis and interpretation from the internal reference library which resides within the Subject Device. These are same for the Predicate Device. The inputs for both devices are ECG signals, the internal technology is based upon a reference library and analysis of the ECG signal, and the output is an interpretation of the ECG based whose performance is based upon EC 57 The outputs from both devices are digital. ## 5 PERFORMANCE TESTING K260640 {17} | monebo | 510(k) Summary | Page 13 of 16 | | --- | --- | --- | Performance testing was conducted on a custom dataset using methods similar to EC57. They are provided below. ### 5.1 Rhythm Statistics Gross performance statistics at the rhythm level are provided in table below: | Rhythm type | Episode Sensitivity | Episode Specificity | Episode Positive Predictive Value | Episode Accuracy | | --- | --- | --- | --- | --- | | Dataset 1.2 | | | | | | Normal Sinus Rhythm (N) | 0.929 | 0.950 | 0.963 | 0.938 | | Sinus Bradycardia (SBR) | 0.955 | 0.980 | 0.933 | 0.975 | | Sinus Tachycardia (ST) | 0.921 | 0.993 | 0.951 | 0.985 | | Atrial Fibrillation (AF) | 0.958 | 1.000 | 1.000 | 0.994 | | Ventricular Bigeminy (B) | 1.000 | 1.000 | 1.000 | 1.000 | | Ventricular Trigeminy (T) | 0.980 | 1.000 | 1.000 | 0.998 | | Junctional Tachycardia (JT) | 1.000 | 1.000 | 1.000 | 1.000 | | Supraventricular Tachycardia (SVTA) | 1.000 | 1.000 | 1.000 | 1.000 | | Idioventricular Rhythm (IVR) | 0.974 | 1.000 | 1.000 | 0.998 | | Ventricular Tachycardia (VT) | 1.000 | 1.000 | 1.000 | 1.000 | | Noise | 0.546 | 0.904 | 0.690 | 0.803 | K260640 {18} | monebo | 510(k) Summary | Page 14 of 16 | | --- | --- | --- | ### 5.2 Beat Statistics Gross performance statistics at the beat level are provided in table below: | Dataset | QRS Sensitivity | QRS Positive Predictive Value | VEB Sensitivity | VEB Positive Predictive Value | VEB Specificity | SVEB Sensitivity | SVEB Positive Predictive Value | SVEB Specificity | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Dataset 1.2 | 0.971 | 0.985 | 0.820 | 0.913 | 0.989 | 0.926 | 0.886 | 0.992 | ### 5.3 Run Statistics Gross performance statistics at the run level are provided in table below: | Dataset | Run type | Couplet Sensitivity | Couplet Positive Predictive Value | Short run Sensitivity | Short run Positive Predictive Value | Long run Sensitivity | Long run Positive Predictive Value | | --- | --- | --- | --- | --- | --- | --- | --- | | Dataset 1.2 | V | 0.693 | 0.877 | 0.774 | 0.949 | 0.953 | 0.976 | | | S | 0.786 | 0.745 | 0.754 | 0.833 | 0.956 | 0.967 | ### 5.4 Heart Rate Statistics Performance statistics at the run level are provided in table below: | Dataset | Mean Error, bpm | Standard deviation, bpm | Standard Error of Mean, bpm | Root Mean Square Error, bpm | | --- | --- | --- | --- | --- | | Dataset 1 | 0.13 | 1.98 | 0.09 | 1.98 | 510(k) Summary {19} monebo 510(k) Summary Page 15 of 16 ### 5.5 Characteristics of the Validation Dataset and ECG Acquisition Device | Parameter | Value | | --- | --- | | Number of clinics | 80 | | Location of clinics | USA | | Number of strips | 480 | | Number of patients | 477 | | Number of females | 80 | | Number of males | 111 | | Number of n/a gender | 289 | | Age range, years | 18-96 | | Strip length, seconds | 72 | | Rhythm | Number of samples | | --- | --- | | Normal Sinus Rhythm (N) | 480 | | Sinus Bradycardia (SBR) | 133 | | Sinus Tachycardia (ST) | 63 | | Atrial Fibrillation (AF) | 72 | | Ventricular Bigeminy (B) | 47 | | Ventricular Trigeminy (T) | 49 | | Junctional Tachycardia (JT) | 38 | | Supraventricular Tachycardia (SVTA) | 44 | | Idioventricular Rhythm (IVR) | 38 | | Ventricular Tachycardia (VT) | 60 | | Noise | 196 | | Total: | 1220 | 510(k) Summary {20} | monebo | 510(k) Summary | Page 16 of 16 | | --- | --- | --- | ### The characteristics of the ECG acquisition device Model of the device: VV330 Continuous ECG Platform / Adhesive Patch (K191870) Lead configuration: II Sampling rate: 128 Hz ADC gain: 1000 units per millivolt Zero (offset): 0 The validation dataset consisted of real-world ECG data collected from 477 patients across 80 U.S. clinical centers following dataset enrichment. The centers were geographically distributed across multiple regions of the United States and included clinical practices located in areas such as Houston, Waco, Brownsville and Victoria, Texas; Phoenix, Chandler, Casa Grande, Surprise and Avondale, Arizona; Brooklyn, New York; Tampa, Florida; and Lake Charles, Louisiana. Public U.S. Census data demonstrate that these communities encompass substantially different racial and ethnic demographic profiles. ## 6 CONCLUSION Based upon this testing and validation results, in addition the information provided in this 510(k) notification's ESTAR Template, Monebo Technologies, Inc. and Innolitics LLC believes that the Kinetic Software Library does not raise addition safety or efficacy concerns. Therefore, the Monebo the Kinetic Software Library is substantially equivalent to its predicate device which is the Monebo Automated ECG Analysis and Interpretation Software Library (K062282). 510(k) Summary