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The physIQ Heart Rhythm and Respiration Module (Version 3.0) is intended for use by a physician or other qualified medical professionals for the calculation of heart rate variability, the detection of atrial fibrillation and determination of respiration rate using ambulatory ECG and triaxial accelerometer data. The physIQ Heart Rhythm and Respiration Module is intended to be integrated by the customer organization into an end-to-end system (biosensor data collection to clinician display).

The physIQ Heart Rhythm and Respiration Module may only be used with FDA-cleared, chest-worn biosensors using "wet electrode" technology that capture single-lead digital ECG data at 125Hz or higher and integrated triaxial accelerometer data at 15Hz or higher and that are recorded in a compatible format for analysis.

The physIQ Heart Rhythm and Respiration Module is for use in adult patients in subacute clinical settings for remote patient monitoring. The physIQ Heart Rhythm and Respiration Module is not for use in patients requiring life-supporting or life-sustaining systems or as ECG or respiration alarm devices.

The physIQ Heart Rhythm and Respiration Module (Version 3.0) is a computerized all-software callable function library in the Python programming language that is designed for calculating heart rate and heart rate variability and for detecting atrial fibrillation and determining respiration rate determined by automated analysis of any single electrocardiogram (ECG) channel collected by commercially-available ECG biosensor devices with triaxial accelerometers. The physlQ Heart Rhythm and Respiration Module (3.0) will be integrated by the customer organization into an end-to-end system (biosensor data collection to clinician display) that makes calls into the product, most typically via a Python middleware script. The "middleware" accesses the source ECG and triaxial accelerometer data from a customer's data collection system, most likely via its own application programming interface (API), and makes calls to the physIQ Heart Rhythm and Respiration Module (3.0) to input ECG and triaxial accelerometer data for processing into the vital sign outputs of the product. These outputs are returned to the middleware, which may insert these results into a downstream monitoring system for clinical use.

The provided text describes the physIQ Heart Rhythm and Respiration Module (Version 3.0) and its substantial equivalence to a predicate device. However, it does not contain the specific acceptance criteria and detailed study information requested in the prompt.

The document states that "performance testing demonstrates that the physIQ Heart Rhythm and Respiration Module (3.0) meets its intended use and any differences in technological characteristics between the physIQ Heart Rhythm and Respiration Module (3.0) and the predicate device do not raise any new issues and is substantially equivalent to the predicate device."

It also mentions that "Performance testing following guidelines of ANSI/AAMI EC572012: Testing and Reporting Performance Results of Cardiac Rhythm and ST segment Medsurement Algorithms was applied to heart rate variability, and atrial fibrillation algorithms in a previous Traditional 510(k) submission for the physIQ Heart Rhythm and Respiration Module (K183322) predicate device." and that "In this submission, performance of all algorithms including Heartbeat Detector, Heart Rate, Heart Rate Variability, Atrial Fibrillation, and Respiration Rate have been repeated and evaluated using the modified technology. The respiration rate algorithm met its corresponding acceptance criteria and performed comparably to the predicate device."

Based on the provided text, I cannot extract the following information:

• A table of acceptance criteria and the reported device performance. While it mentions that algorithms met acceptance criteria, the specific criteria and reported values are not present.
• Sample size used for the test set and the data provenance.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts.
• Adjudication method for the test set.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size.
• If a standalone (i.e., algorithm only without human-in-the-loop performance) was done. (It implies standalone testing as it refers to algorithm performance, but doesn't explicitly state it or provide details).
• The type of ground truth used.
• The sample size for the training set.
• How the ground truth for the training set was established.

Therefore, I can only provide the information that is explicitly stated or strongly implied from the text:

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

• Not explicitly provided. The document states that the respiration rate algorithm met its corresponding acceptance criteria and performed comparably to the predicate device. However, the specific numerical criteria for heart rate variability, atrial fibrillation, and respiration rate, and the reported performance metrics, are not included in this document.

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).

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

• Not specified.

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

• Not specified.

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 mentioned. The document focuses on the algorithm's performance and substantial equivalence, not human-AI collaboration.

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

• Implied yes. The document repeatedly refers to the "performance of all algorithms" and the "physIQ Heart Rhythm and Respiration Module (3.0)" in isolation, suggesting standalone algorithm testing was performed to assess its functionality and accuracy.

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

• Not specified.

8. The sample size for the training set

• Not specified.

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

• Not specified.

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