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The Cardy302Max Compact Digital Holter Recorder System is intended to acquire ambulatory 2 or 3 channel ECG signals from the chest surface of pediatric or adult patients. The device stored this data along with patient demographic information onto a removable SD memory card.

The Cardy302Max Compact Digital Holter Recorder System is intended to be used by trained operators under the direct supervision of a licensed healthcare practitioner in a hospital or medical professional's facility.

The Cardy302Max Compact Digital Holter Recorder System does not perform any analysis of the ECG data.

The Cardy302Max Compact Digital Holter Recorder System is not intended for use on patients weighing less than 10 kg.

The Cardy302Max Compact Digital Holter System is designed to acquire ambulatory 2 or 3 channels of ECG signal from the chest surface of pediatric or adult patients for up to 48 hours. The device stores the acquired ECG data on its removable memory card.

The Cardy Controller02 downloads patient demographic information into the Cardy302Max Compact Digital Holter Recorder and allows the user to check the signal quality of the ECG data at hookup time. At the end of recording, the ECG data can be transferred to the controller by removing the SD memory card from the recorder and installing it into the Cardy Controller02.

The provided document describes the acceptance criteria and study for the Kenz® Cardy302Max Digital Holter System.

This device is a digital ambulatory Holter recorder that acquires ECG signals but does not perform any analysis of the ECG data. Therefore, the acceptance criteria and studies focus on the hardware's safety, performance, and compliance with relevant standards, rather than the diagnostic accuracy of an AI algorithm.

Here's a breakdown based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

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

Not applicable for an AI algorithm test set. The testing described focuses on hardware and software functional verification against engineering standards. The document does not specify a "test set" in the context of clinical data for AI performance evaluation.

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

Not applicable. The device does not perform analysis, so clinical ground truth (e.g., diagnosis by experts) is not relevant for its mechanical and electrical performance verification.

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

Not applicable, as there's no clinical "test set" requiring adjudication.

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 device is not an AI analysis system. It is a data acquisition device, and therefore, an MRMC study comparing human readers with AI assistance is not relevant or described.

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

No. This device is a hardware system for recording ECG data. It does not contain an "algorithm" for independent diagnostic performance without human-in-the-loop intervention. The software verification confirmed the device's operational functionality, not diagnostic accuracy.

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

The "ground truth" for this device's performance is based on regulatory and engineering standards compliance. This includes:

• Compliance with IEC 60601-1, IEC 60601-1-2, and IEC 60601-2-47 for safety and essential performance.
• Compliance with IEC 60529:2001 for water ingress protection.
• Software verification and validation outputs demonstrating that the software operates "as designed" and "in accordance with the indications for use."

8. The sample size for the training set

Not applicable. This device is a data acquisition hardware system and does not employ machine learning or AI algorithms requiring a training set.

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

Not applicable, as there is no training set for an AI algorithm.

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