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Curbell patient cables are used to connect electrodes and/or sensors placed at the appro priate sites on the patient to a monitoring device for general monitoring and/or diagno stic evaluation by a healthcare professional.

Curbell Patient Monitoring Cables and Lead Wires. Curbell patient cables are used to connect electrodes and/or sensors placed at the appropriate sites on the patient to a monitoring device for general monitoring and/or diagnostic evaluation by a healthcare professional.

The provide document is a 510(k) summary for Curbell Patient Monitoring Cables. It asserts substantial equivalence to a predicate device (Merit Cables, Inc. K942321) rather than establishing novel performance criteria through a study. Therefore, the information requested regarding acceptance criteria and a study proving the device meets those criteria, particularly in the context of AI/ML performance, is not directly applicable to this document.

However, based on the provided text, I can extract information related to how this device demonstrates equivalence for its intended use. The "acceptance criteria" here are effectively the performance characteristics and standards met by the predicate device, and the study is the nonclinical performance data demonstrating the Curbell device also meets these.

Here's an interpretation based on the provided document:

1. A table of acceptance criteria and the reported device performance

For this 510(k), the "acceptance criteria" are implied by the characteristics of the predicate device, and the "reported device performance" is the claim that the Curbell device possesses substantially equivalent characteristics.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not detail a "test set" in the context of data for an AI/ML device. Instead, the testing pertains to nonclinical performance data of the physical device. The provenance of the data is that it was generated through testing of Curbell Patient Monitoring Cables against established standards. No specific sample sizes for these tests are mentioned beyond the implication that sufficient samples were tested to demonstrate compliance with the referenced standards. The data is likely prospective, generated specifically for this submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This document is for a medical device (patient monitoring cables), not an AI/ML algorithm that requires expert ground truth labeling. Therefore, this information is not applicable. The "ground truth" for compliance testing is defined by the technical specifications and requirements of the referenced standards (e.g., AAMI EC 53).

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

Not applicable for this type of medical device submission. Adjudication methods are typically relevant for human interpretation of data where consensus among experts is needed for ground truth.

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, nor does it involve human readers interpreting data enhanced by AI.

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

Not applicable. This is a physical medical device (cables and lead wires), not an algorithm.

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

The "ground truth" for the device's performance is based on the requirements and methodologies outlined in recognized national and international standards:

• 21 CFR 898
• IEC 60601-1, Subclause 56.3(c)
• ANSI/AAMI EC53:1995(R)2001

Compliance with these standards, as demonstrated through electrical, mechanical, and material testing, serves as the basis for asserting safety and effectiveness.

8. The sample size for the training set

Not applicable. This is a physical medical device, not an AI/ML algorithm requiring a training set.

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

Not applicable. There is no training set for this device.

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Sure-Lock electrode clips provide a connection between lead wires and ECG/EKG electrodes (button & tab style).

ECG/EKG electrode clip

This document describes a Special 510(k) submission for a Sure-Lock electrode clip, focusing on changes to the device rather than a new AI/ML device. Therefore, many of the requested elements for an AI/ML device (like sample sizes for test/training sets, expert qualifications, MRMC studies, standalone performance, etc.) are not applicable to this submission.

The acceptance criteria and "study" proving the device meets them are related to the safety and effectiveness of the proposed changes compared to the predicate device, demonstrated through non-clinical performance data and adherence to recognized standards.

Here's the breakdown of the information that is applicable:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Not Applicable. This is a device modification submission, not an AI/ML study involving a test dataset for algorithm performance. The "test set" here refers to the actual physical devices undergoing engineering testing. Data provenance would be from internal engineering tests conducted by Curbell Electronics, Inc.

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 study is not relevant here. The "ground truth" for this device modification is compliance with established performance standards and the predicate device's baseline performance. This would have been established by Curbell's internal engineering and quality personnel.

4. Adjudication method for the test set

• Not Applicable. No human adjudication of diagnostic output from an algorithm is involved. Device performance testing would follow standard engineering and quality control procedures.

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, and no MRMC study was performed.

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

• For the physical device modifications, the "ground truth" involves compliance with industry performance standards (ANSI/AAMI EC53:1995 and EC53/A1:1998) and comparison to the established performance of the legally marketed predicate device (K884592). Additionally, internal engineering test reports serve as evidence for the specific material, cleaning, sterilization, and electrode compatibility changes.

8. The sample size for the training set

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

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

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

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