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The subject device is intended for use only by trained healthcare professionals for measurement of a patient's ECG for both diagnostic and monitoring purposes. Use is limited by the indications for use of the connected monitoring or diagnostic equipment.

The Caremed patient cable and lead wires including trunk cable and leadwires, are intended use for transmitting signals from patient surface electrodes to various electrocardiograph recorders/monitors for both diagnostic and monitoring purposes. The type of devices are common to both industry and to most medical establishments. The system is designed to provide a family of lead wires that will link the patient and the compatible patient trunk cable system.

The provided text does not describe acceptance criteria for a medical device in the typical sense of performance metrics for an AI/ML model, nor does it detail a study proving such criteria are met. Instead, it is a 510(k) Premarket Notification summary for "Caremed Patient Cable and Leadwires."

This document focuses on establishing substantial equivalence to a previously cleared predicate device, rather than defining and proving performance against specific quantitative acceptance criteria of an AI/ML system.

However, I can extract the relevant information from the document that pertains to the device's characteristics and the standards it meets, which serve as its "acceptance criteria" in the context of a 510(k) submission for a non-AI medical device.

Here's an interpretation based on the provided text, recognizing it's not about AI performance metrics:

The "acceptance criteria" for this device are its compliance with recognized industry standards and its substantial equivalence to a predicate device. The "study" proving this involves a comparison to the predicate device and demonstration of compliance with relevant safety and performance standards through testing (though detailed test results are not provided in this summary).

Here's the information formatted as requested, with explanations where the categories don't directly apply to this type of medical device submission:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not applicable. For this type of device (patient cables and leadwires), the "test set" for substantial equivalence is primarily a comparison against technical specifications and performance standards, not a clinical data set in the way an AI/ML model would be evaluated. The text indicates "Not applied" for clinical test data.
• Data Provenance: Not applicable. The "data" are technical specifications, material properties, and compliance test results (which are not detailed in this summary).

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

• Not applicable. "Ground truth" in the context of an AI/ML model evaluation does not apply to this device. The "ground truth" here is the established safety and performance requirements set by industry standards and regulatory bodies, along with the characteristics of the predicate device.

4. Adjudication method for the test set

• Not applicable. There's no "adjudication method" described as would be used for expert consensus on AI outputs. The evaluation is based on technical specifications and compliance with standards.

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

• Not applicable. This is not an AI/ML device; therefore, an MRMC study related to AI assistance is irrelevant.

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

• Not applicable. This is not an AI/ML device.

7. The type of ground truth used

• Ground Truth: For this type of device, the "ground truth" is defined by:
  • Regulatory Standards: Specifically, ANSI/AAMI EC53, ANSI/AAMI EC13, 21 CFR Part 898, IEC 60601-1, ISO 10993-5, and ISO 10993-10.
  • Predicate Device Characteristics: The characteristics, indications for use, and performance of the Unimed Disposable ECG lead wires (K142489).

8. The sample size for the training set

• Not applicable. This is not an AI/ML device, so there is no concept of a "training set."

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

• Not applicable. As above, no training set for an AI/ML model; the "ground truth" for compliance testing is established by recognized standards and the clear specifications of the predicate device.

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