K Number
K123816
Date Cleared
2013-02-27

(77 days)

Product Code
Regulation Number
870.2340
Panel
CV
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

Digital Electrocardiographs, iE 12A / iE 15S, are intended to acquire ECG signals from adult and pediatric patients through body surface ECG electrodes. The obtained ECG records can help users to analyze and diagnose heart disease. Digital Electrocardiographs shall be used in healthcare facilities by doctors and/or trained healthcare professionals.

Device Description

Digital Electrocardiographs, iE 12A / iE 15 / iE 15S, are designed to acquire, display and record ECG signals from patient body surface by ECG electrodes. After been amplified and filtered, the ECG signals waveforms are displayed in the LCD and recorded in the paper through thermal printer. ECG data result and patient information could be stored in the memory of the device.

All the models. iE 12A / iE 15 / iE 15S, of the proposed device. Digital Electrocardiographs, follow · the same design principle and similar technical specifications.

AI/ML Overview

The provided text describes a 510(k) premarket notification for Digital Electrocardiographs (models iE 12A, iE 15, iE 15S). The submission focuses on demonstrating substantial equivalence to a predicate device (iE 12) rather than presenting a study with specific acceptance criteria related to clinical performance metrics like sensitivity, specificity, or reader improvement.

Therefore, many of the requested details, such as specific acceptance criteria for diagnostic performance, sample sizes for test and training sets for an AI algorithm, expert qualifications, adjudication methods, or MRMC study results, are not available in this document. This document primarily details the technical specifications and safety/EMC standards met by the device.

Here's a breakdown of what is available and what is not:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in the sense of diagnostic performance metrics (e.g., sensitivity, specificity, AUC). Instead, it refers to verifiable technical specifications and compliance with international standards for safety and electrical performance. The "reported device performance" in this context refers to the device meeting these technical specifications and standards.

ITEMAcceptance Criteria (Predicate iE 12)Proposed Device Performance (iE 12A / iE 15 / iE 15S)
LeadStandard 12-leadStandard 12-lead (iE 12A), Standard 12-lead/15-lead (iE 15, iE 15S)
Acquisition modeSimultaneous 12-lead acquisitionSimultaneous 12-lead acquisition (iE 12A), Simultaneous 12-lead/15-lead acquisition (iE 15, iE 15S)
Recording formatAutomatic / Manual / RhythmAutomatic / Manual / Rhythm
Frequency response0.05~150Hz0.05 Hz150 Hz (iE 12A), 0.05 Hz250 Hz (iE 15, iE 15S)
Noise level60dB, >100dB with AC filter>60dB, >100dB with AC filter
Recording SpeedSix levels as 5, 6.25, 10, 12.5, 25, 50mm/sSix levels as 5, 6.25, 10, 12.5, 25, 50mm/s
Input CIR current≤0.1μΑ≤0.1μΑ
Input impedance>50ΜΩ>50ΜΩ
External Input Impedance≥100k Ω≥100k Ω
External Input Sensitivity10mm/V±5%10mm/V±5%
External Output Impedance≤100 Ω≤100 Ω
External Output Sensitivity1V/mV±5% (at 10mm/mV)1V/mV±5% (at 10mm/mV)

Study Proving Acceptance Criteria Met:
The document states: "Bench tests were conducted to verify that the proposed device met all design specifications as was Substantially Equivalent (SE) to the predicate device. The test results demonstrated that the proposed device complies with the following standards: EN 60601-1, EN 60601-2-25, EN 60601-1-2, IEC60601-2-51."

The primary "acceptance criterion" for this 510(k) submission is demonstrating substantial equivalence to the predicate device, which is verified by meeting technical specifications and compliance with relevant safety and performance standards. The differences in frequency response and lead type for the proposed devices compared to the predicate were addressed by conducting relative standard tests to demonstrate compliance.

2. Sample size used for the test set and the data provenance

Not applicable/Not provided within the scope of this document. This submission focuses on technical specifications and substantial equivalence, not a clinical study with a patient test set for diagnostic algorithm performance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable/Not provided. No diagnostic algorithm performance study is described.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable/Not provided. No diagnostic algorithm performance study is described.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No. This document pertains to the hardware and basic signal acquisition capabilities of an electrocardiograph, not an AI-assisted diagnostic system.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

No. This document describes the ECG acquisition device itself, not a standalone diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

Not applicable/Not provided. The "ground truth" here is compliance with engineering standards and technical specifications shown via bench testing.

8. The sample size for the training set

Not applicable/Not provided. No machine learning algorithm is described.

9. How the ground truth for the training set was established

Not applicable/Not provided. No machine learning algorithm is described.

In summary: This 510(k) submission is for a traditional Digital Electrocardiograph hardware device. The "acceptance criteria" and "study" described are focused on engineering specifications, electrical safety, and electromagnetic compatibility (EMC) through bench testing, to demonstrate substantial equivalence to a predicate device. It does not involve a clinical study to evaluate diagnostic performance of an AI algorithm.

§ 870.2340 Electrocardiograph.

(a)
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.(b)
Classification. Class II (performance standards).