(173 days)
Not Found
Yes
The device description explicitly states that the software uses "artificial neural networks" and "neural network model" for rhythm and murmur detection, which are forms of AI/ML.
No
The software generates interpretations and detections of cardiac conditions (murmurs, atrial fibrillation, heart rate, etc.) for physician over-read and is not intended as a sole means of diagnosis or treatment. It supports diagnosis, but does not provide therapy.
Yes
The device analyzes ECG and heart sounds to detect suspected murmurs, atrial fibrillation, and normal sinus rhythm, and calculates cardiac time intervals, which are all diagnostic functions. Although it states it's "not intended as a sole means of diagnosis," it provides information that contributes to a diagnosis, especially "when used in conjunction with physician over-read."
Yes
The device is described as a "cloud-based software API" and its function is to analyze data acquired from previously cleared hardware devices. It does not include any hardware components itself.
Based on the provided information, the Eko Analysis Software is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVD Definition: In Vitro Diagnostics are devices intended for use in the collection, preparation, and examination of specimens taken from the human body (such as blood, urine, or tissue) to obtain information for diagnostic purposes.
- Eko Analysis Software Function: The Eko Analysis Software analyzes physiological signals (heart sounds and ECG) acquired directly from the patient's body using external devices (Eko DUO and Eko CORE). It does not analyze specimens taken from the body.
- Intended Use: The intended use is to provide support for the evaluation of heart sounds and ECGs, detecting suspected murmurs and certain rhythm abnormalities. This is a form of physiological monitoring and analysis, not the analysis of in vitro specimens.
Therefore, the Eko Analysis Software falls under the category of a medical device that analyzes physiological data, not an In Vitro Diagnostic device.
No
The clearance letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The provided text states "Not Found" next to "Control Plan Authorized (PCCP) and relevant text".
Intended Use / Indications for Use
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).
Product codes (comma separated list FDA assigned to the subject device)
MWI, DOD, DPS
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.
- 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.
Mentions image processing
Not Found
Mentions AI, DNN, or ML
Mentions "artificial neural networks" and "neural network model".
Input Imaging Modality
Not Found. The device uses heart sounds and ECG data.
Anatomical Site
Heart
Indicated Patient Age Range
Adults (> 18 years)
Intended User / Care Setting
Physicians
Description of the training set, sample size, data source, and annotation protocol
Not Found. The document only describes the test sets.
Description of the test set, sample size, data source, and annotation protocol
Rhythm Detection: "Testing was carried out on publicly available databases as well as the EKO ECG dataset." The EKO ECG dataset consists of "732 recording were captured from 139 patients using the Eko DUO and 1445 recordings were captured from 236 patients using the Eko CORE." Data sources: 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.
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."
Heart Rate Calculation: "Testing was carried out on publicly available datasets as well as the EKO ECG dataset (described above)."
QRS Duration Calculation: "Testing was carried out using the publicly available PhysioNet QT database."
EMAT Calculation: "Testing was carried out on publicly available Physionet 2016 database, as well as the Eko ECG dataset."
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Rhythm Detection:
Study type: Retrospective analysis.
Sample size: 732 ECG recordings from 139 patients for Eko DUO, and 1445 recordings from 236 patients for Eko CORE in proprietary datasets. 544/732 (74.3%) of ECG recordings in the EKO ECG dataset were classifiable as Normal or Atrial Fibrillation.
Key results: 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:
Study type: Retrospective analysis.
Sample size: Not explicitly stated, but performed on the "Eko Heart Sound Database comprised of data collected using both the Eko CORE and Eko DUO devices."
Key results: 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:
Study type: Retrospective analysis.
Sample size: Not explicitly stated, but performed on publicly available datasets and the EKO ECG dataset.
Key results: Heart rate error measured in the MIT-BIH dataset was 1.14% (95% Cl: 0.95 - 1.34). Bradycardia detection sensitivity was 94.7% (95% Cl: 89.8 - 97.3) and specificity was 99.7% (95% Cl: 99.4 - 99.8). Tachycardia detection sensitivity was 93.6% (95% C1: 90.9 - 95.6) and specificity was 99.0% (95% C1: 98.7 - 99.3).
QRS Duration Calculation:
Study type: Retrospective analysis.
Sample size: Not explicitly stated, but performed on the PhysioNet QT database.
Key results: Absolute Mean Error (ms) for calculating QRS duration was 9.25 (95% Cl: 7.93 - 10.58).
EMAT Calculation:
Study type: Retrospective analysis.
Sample size: Not explicitly stated, but performed on the Physionet 2016 database and the Eko ECG dataset.
Key results: Absolute Error in the Physionet 2016 dataset was 1.68% (95% Cl: 1.06 -2.30).
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Rhythm Detection:
Sensitivity: 100% (95% Cl: 93.8 - 100.0)
Specificity: 96.2% (95% Cl: 93.8 -97.7)
Murmur Detection:
Sensitivity: 87.6% (95% C1: 84.2 – 90.5)
Specificity: 87.8% (95% C1: 85.3 – 89.9)
Heart Rate Calculation (Bradycardia Detection):
Sensitivity: 94.7% (95% Cl: 89.8 - 97.3)
Specificity: 99.7% (95% Cl: 99.4 - 99.8)
Heart Rate Calculation (Tachycardia Detection):
Sensitivity: 93.6% (95% C1: 90.9 - 95.6)
Specificity: 99.0% (95% C1: 98.7 - 99.3)
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
K170798, K131044, K073545, K180234
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 870.2300 Cardiac monitor (including cardiotachometer and rate alarm).
(a)
Identification. A cardiac monitor (including cardiotachometer and rate alarm) is a device used to measure the heart rate from an analog signal produced by an electrocardiograph, vectorcardiograph, or blood pressure monitor. This device may sound an alarm when the heart rate falls outside preset upper and lower limits.(b)
Classification. Class II (performance standards).
0
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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. 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
1
Page 2
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 of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
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 https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-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/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the 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-device-advice-comprehensive-regulatoryassistance/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,
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)
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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.
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K192004
Page 3 of 5
| | Eko Analysis
Software | IDM100 | Sensi Cardiac Mobi
Diagnostic Heart
Murmur
Application | AUDICOR 200 | physIQ Heart Rhythm
Module (version 1.0) |
|--------------------------------|------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------|---------------------------------------------------------------|----------------------------------------------------------|
| 510K
Number | K182119 | K170798 | K131044 | K073545 | K180234 |
| Patient
Population | Adult patients | Neonate (up to 28
days); pediatric (29
days to 12 years,
excepted as
noted); adolescent
(13-17 years); adult
(18 years and
older) | Adult and pediatric
patients | Patients over 18 years
of age | Adult patients |
| Intended
User | Physicians | Physicians and
patients | Physicians | Physician | Physician or other
qualified medical
professionals |
| Standards
Met | IEC 60601-1
IEC 60601-1-2
IEC 60601-2-47
IED 60601-2-25
ANSI/AAMI EC57 | ANSI/AAMI EC53
EN/IEC 60601-2-25
EN/IEC 60601-2-51 | IEC 60601-1
IEC 60601-1-2 | EN 60601-1
EN60601-1-2
IEC 60601-2-25
IEC 60601-2-51 | ANSI/AAMI EC57 |
| Device
Classificati
on | MWI, DQD, DPS | MWI | DQD, DQC | DPS, DQD, MLO | DPS |
| Prescribed | Prescription Only | Prescription Only | Prescription Only | Prescription Only | Prescription Only |
| Componen
ts | Software Only | Software +
Hardware | Software Only | Software + Hardware | Software Only |
| Interface | Application
programming
interface (API) | | | | Callable application
programming interface
(API) |
| Display | No primary display | Yes | No primary display | Yes on Audicor-
enabled laptop | No primary display |
| Physiologi
cal Inputs | Heart sounds and
ECG data | Heart sounds, ECG
data, SpO2, NIBP | Heart sounds | Heart sounds and ECG
data | Heart sounds and ECG
data |
| Murmur
Detection | Yes (classification) | No | Yes (classification) | No | No |
| A-fib
detection | Yes (classification) | No, ECG
acquisition only. | No | No | Yes (classification) |
| EMAT
Calculation | Yes | No | No | Yes | No |
| Heart Rate
Calculation | Yes | Yes | Yes | Yes | Yes |
| QRS
duration
Calculation | Yes | No | No | Yes | Yes |
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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.