Eko Analysis Software

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January 15, 2020 Eko Devices Inc % Yarmela Pavlovic Partner Manatt, Phelps & Phillips, LLP One Embarcadero Center, 30th Floor San Francisco, California 94111 Re: K192004 Trade/Device Name: Eko Analysis Software Regulation Number: 21 CFR 870.2300 Regulation Name: Cardiac Monitor (Including Cardiotachometer And Rate Alarm) Regulatory Class: Class II Product Code: MWI, DOD, DPS Dated: December 18, 2019 Received: December 18, 2019 Dear Yarmela Pavlovic: 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. 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 located 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. 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Sincerely, Stephen Browning Assistant Director Division of Cardiac Electrophysiology, Diagnostics and Monitoring Devices Office of Cardiovascular Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health Enclosure {2}------------------------------------------------ 510(k) Number (if known) K192004 Device Name Eko Analysis Software (EAS) Indications for Use (Describe) The Eko Analysis Software is intended to provide support to the evaluation of patients ' heart sounds and ECG's. The software analyzes simultaneous ECG and heart sounds. The software will detect the presence of suspected murmurs in the heart sounds. The software also detects the presence of atrial fibrillation and normal sinus rhythm from the ECG signal. In addition, it calculates certain cardiac time intervals such as heart rate, QRS duration and EMAT. The software does not distinguish between different kinds of murmurs and does not identify other arrhythmias. It is not intended as a sole means of diagnosis. The interpretations of heart sounds and ECG offered by the software are only significant when used in conjunction with physician over-read and is for use on adults (> 18 years). Type of Use (Select one or both, as applicable) 冈 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.qov "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." {3}------------------------------------------------ ### 510(k) SUMMARY ### Eko Devices, Inc.'s Eko Analysis Software ### Submitter Eko Devices Inc. 2600 10th Street, Suite #260, Berkeley, CA - 94710 Contact Person: Subramaniam Venkatraman, CTO Phone: 844-356-3384 Email: contact@ekohealth.com Date Prepared: January 8, 2020 Name of Device: Eko Analysis Software (EAS) Common or Usual Name: CardiacAl Classification Name: Cardiac monitor Regulatory Class: Class II Product Code: MWI, DQD, DPS ### Predicate Devices Dictum Health Inc., IDM100 (K170798) Diacoustic Medical Devices (Pty) Ltd, SensiCardiac Mobi (K131044) Inovise Medical. AUDICOR 200 (K073545) physIQ Inc, physIQ Heart Rhythm Module (K180234) ### Device Description The Eko Analysis Software is a cloud-based software API that allows a user to upload synchronized ECG and heart sound/phonocardiogram (PCG) data for analysis. The software uses several methods to interpret the acquired signals including signal processing and artificial neural networks. The API can be electronically interfaced, and perform analysis with data transferred from multiple mobile or computer based applications. The EAS software is only intended to be used in conjunction with data acquired using two previously-cleared physiological data acquisition devices (Eko DUO (K170874) and Eko CORE (K151319)). The software is designed to be used with companion mobile apps that are used during data acquisition. After analysis, results are returned through an interface to the mobile apps for display. The algorithm consists of the following components: - Rhythm detection algorithm: A neural network model that uses ECG to detect normal sinus rhythm and atrial fibrillation. - Murmur detection algorithm: A neural network model that uses heart sounds to detect the ● presence of murmurs. - Heart rate analysis algorithm: A signal processing algorithm that uses ECG or heart ● sounds as appropriate to calculate heart rate. It also provides an alert if the measured heart rate is indicative of Bradycardia or Tachycardia. {4}------------------------------------------------ - QRS duration algorithm: A signal processing algorithm that measures the width of the ● QRS pulse on a single-channel ECG. - EMAT Interval algorithm: A signal processing algorithm that uses Q peak detection and ● S1 envelope detection to measure the Q-S1 interval, defined as electromechanical activation time or EMAT. ### Intended Use / Indications for Use The Eko Analysis Software is intended to provide support to the physician in the evaluation of patients' heart sounds and ECG's. The software analyzes simultaneous ECG and heart sounds. The software will detect the presence of suspected murmurs in the heart sounds. The software also detects the presence of atrial fibrillation and normal sinus rhythm from the ECG signal. In addition, it calculates certain cardiac time intervals such as heart rate. QRS duration and EMAT. The software does not distinguish between different kinds of murmurs and does not identify other arrhythmias. It is not intended as a sole means of diagnosis. The interpretations of heart sounds and ECG offered by the software are only significant when used in conjunction with physician over-read and is for use on adults (> 18 years). ### Summary of Technological Characteristics EAS combines the features of multiple predicate devices into a single combined software package. The intended use of the subject product (i.e., analysis of physiological data) is the same as that of all of the predicate devices and the indications for use and technological characteristics are either identical or very similar between the subject device and each relevant predicate. Any differences in specific analyzed parameters (indications for use) do not raise different questions of safety or effectiveness in comparison to the predicates. While some of the predicate devices feature additional technological capabilities (e.g., the SensiCardiac predicate additional features differentiation between pathologic and innocent murmur, while the subject device and predicate both differentiate between the presence of murmur and no murmur), this does not raise different questions of safety or effectiveness because in all cases the subject device features are a subset of those cleared for the predicates. A table comparing the key features of the subject and predicate devices is provided below. {5}------------------------------------------------ K192004 Page 3 of 5 | | Eko Analysis<br>Software | IDM100 | Sensi Cardiac Mobi<br>Diagnostic Heart<br>Murmur<br>Application | AUDICOR 200 | physIQ Heart Rhythm<br>Module (version 1.0) | |--------------------------------|------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------|---------------------------------------------------------------|----------------------------------------------------------| | 510K<br>Number | K182119 | K170798 | K131044 | K073545 | K180234 | | Patient<br>Population | Adult patients | Neonate (up to 28<br>days); pediatric (29<br>days to 12 years,<br>excepted as<br>noted); adolescent<br>(13-17 years); adult<br>(18 years and<br>older) | Adult and pediatric<br>patients | Patients over 18 years<br>of age | Adult patients | | Intended<br>User | Physicians | Physicians and<br>patients | Physicians | Physician | Physician or other<br>qualified medical<br>professionals | | Standards<br>Met | IEC 60601-1<br>IEC 60601-1-2<br>IEC 60601-2-47<br>IED 60601-2-25<br>ANSI/AAMI EC57 | ANSI/AAMI EC53<br>EN/IEC 60601-2-25<br>EN/IEC 60601-2-51 | IEC 60601-1<br>IEC 60601-1-2 | EN 60601-1<br>EN60601-1-2<br>IEC 60601-2-25<br>IEC 60601-2-51 | ANSI/AAMI EC57 | | Device<br>Classificati<br>on | MWI, DQD, DPS | MWI | DQD, DQC | DPS, DQD, MLO | DPS | | Prescribed | Prescription Only | Prescription Only | Prescription Only | Prescription Only | Prescription Only | | Componen<br>ts | Software Only | Software +<br>Hardware | Software Only | Software + Hardware | Software Only | | Interface | Application<br>programming<br>interface (API) | | | | Callable application<br>programming interface<br>(API) | | Display | No primary display | Yes | No primary display | Yes on Audicor-<br>enabled laptop | No primary display | | Physiologi<br>cal Inputs | Heart sounds and<br>ECG data | Heart sounds, ECG<br>data, SpO2, NIBP | Heart sounds | Heart sounds and ECG<br>data | Heart sounds and ECG<br>data | | Murmur<br>Detection | Yes (classification) | No | Yes (classification) | No | No | | A-fib<br>detection | Yes (classification) | No, ECG<br>acquisition only. | No | No | Yes (classification) | | EMAT<br>Calculation | Yes | No | No | Yes | No | | Heart Rate<br>Calculation | Yes | Yes | Yes | Yes | Yes | | QRS<br>duration<br>Calculation | Yes | No | No | Yes | Yes | {6}------------------------------------------------ # Performance Data - Nonclinical Testing The Eko Analysis Software was the subject of software verification and validation testing, consistent with the principles outlined in FDA's General Principles of Software Validation; Final Guidance for Industry and FDA Staff. # Performance Data - Clinical Testing The algorithms in this submission have been validated using retrospective analysis on a combination of publicly available (MIT-BIH Arrhythmia Database, MIT-BIH Arrhythmia Noise Stress Database, AHA Database, NST Database, Physionet QT Database, and PhysioNet 2016 Database) and proprietary datasets captured with the Eko CORE and Eko DUO. In the proprietary datasets, the Eko CORE and Eko DUO were used to capture 15 second long heart sound and ECG recordings from chests of individual volunteers. A total of 732 recording were captured from 139 patients using the Eko DUO and 1445 recordings were captured from 236 patients using the Eko CORE. In the Eko DUO dataset 54.7% of patients were female and all patients were over the age of 18, with the largest percentage being 61 to 80 years of age. Additionally, 79.9% were white, while 9.4% were Asian and the remainder were Black or African American, American Indian or Alaskan Native, Native Hawaiian or Pacific Islander or Hispanic/Latino. In the Eko CORE dataset, 47.9% of patients were female. Additionally, 83.9% were white, 7.6% were black or African American and the remainder were Asian (4.2%), Hispanic or Latino (2.1%) or other/unknown. Patients were all over the age of 18 with the largest percentage being 51 to 80 years of age. A brief description of the testing provided for each individual analysis algorithm is provided below along with performance results from the most relevant datasets: # Rhythm Detection Testing was carried out on publicly available databases as well as the EKO ECG dataset. When the device was tested with the EKO ECG dataset, 74.3% (544/732) of ECG recordings were classified as either Normal or Atrial Fibrillation. Sensitivity and specificity measured in the classifiable ECGs were 100% (95% Cl: 93.8 - 100.0) and 96.2% (95% Cl: 93.8 -97.7), respectively. # Murmur Detection Testing was carried out on the Eko Heart Sound Database comprised of data collected using both the Eko CORE and Eko DUO devices. Sensitivity and specificity in the Eko Heart Sound Database were 87.6% (95% C1: 84.2 – 90.5) and 87.8% (95% C1: 85.3 – 89.9), respectively. # Heart Rate Calculation Testing was carried out on publicly available datasets as well as the EKO ECG dataset (described above). Bradycardia and Tachycardia detection accuracy was also measured in the publicly available datasets. Heart rate error measured in the MIT-BIH dataset was 1.14% (95% Cl: 0.95 - 1.34). Bradycardia detection had a sensitivity and specificity of 94.7% (95% {7}------------------------------------------------ Cl: 89.8 - 97.3) and 99.7% (95% Cl: 99.4 - 99.8) respectively. Tachycardia detection had a sensitivity and specificity of 93.6% (95% C1: 90.9 - 95.6) and 99.0% (95% C1: 98.7 - 99.3) respectively. ### QRS Duration Calculation Testing was carried out using the publicly available PhysioNet QT database. Absolute Mean Error (ms) for calculating QRS duration was 9.25 (95% Cl: 7.93 - 10.58). ### EMAT Calculation Testing was carried out on publicly available Physionet 2016 database, as well as the Eko ECG dataset. Absolute Error in the Physionet 2016 dataset was 1.68% (95% Cl: 1.06 -2.30). Given the data described above, the algorithms performed as expected. Based on the clinical performance the Eko Analysis Software has a safety and effectiveness profile that is similar to the predicate devices. ### Conclusions The Eko Analysis Software is as safe and effective as the predicate devices. The Eko Analysis Software has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences in indications do not alter the intended diagnostic use of the device and do not raise different questions of safety and effectiveness when used as labeled. In addition, the minor technological differences between the Eko Analysis Software and its predicate devices raise no new issues of safety or effectiveness. Performance data demonstrate that the Eko Analysis Software is as safe and effective as the predicate devices. Thus, the Eko Analysis Software is substantially equivalent.