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Indications: The ANScore™ System is intended for use in heart rate variability measurements in response to paced respiration and controlled exercises. It is not intended for any specific clinical diagnosis. Assessment is indicated for patients in the physician office or hospital environment

The ANScore™ System is a cart-based system with a computer-based user interface and data acquisition system for testing, data collection and data transmission for remote processing. The device features a 3 lead ECG, an optional blood pressure monitor, and a breathing apparatus.

The provided text is a 510(k) Summary for the ANScore™ System. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does not contain detailed information about specific acceptance criteria for performance metrics, nor does it describe a study that explicitly "proves" the device meets such criteria in terms of quantitative performance metrics, such as sensitivity, specificity, or accuracy derived from a clinical study.

The primary focus of this 510(k) Summary is to demonstrate substantial equivalence to legally marketed predicate devices, not to present a de novo clinical study with detailed performance results against acceptance criteria.

I will interpret "acceptance criteria" here as the general requirements for safety and performance typically expected for such a device to be cleared by the FDA through the 510(k) pathway, based on the information provided.

Here's the breakdown of what can be extracted and what information is not available from the provided text, categorized by your requested points:

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

Note: The provided document is a 510(k) summary, which generally focuses on substantial equivalence rather than explicit performance metrics from a full clinical trial. Quantitative acceptance criteria (e.g., sensitivity, specificity, accuracy thresholds) and their corresponding reported device performance values are not specified in this document. The "tests" mentioned are general statements about compliance and usability.

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

• Sample Size for Test Set: Not specified. The document mentions "Psysiological input was simulated using calibrated instrumentation representative of a range of test subjects and physiological states" but does not give a sample size of real patient data for a test set. A "usability study" was performed by clinicians, but no sample size for that is given either.
• Data Provenance (Country of Origin, Retrospective/Prospective): Not specified. The testing appears to be internal verification and validation ("Psysiological input was simulated"). There is no mention of a clinical study involving data from patients, nor its origin or study design.

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

• Number of Experts: Not applicable/Not specified. The document does not describe the establishment of ground truth for a test set using experts in the way one would for diagnostic imaging or AI algorithms for clinical decision support. The testing described appears to be technical validation against simulated physiological inputs and a usability study by "clinicians." The "ground truth" for the simulated input would be the known parameters of the calibrated instrumentation.
• Qualifications of Experts: The usability study was performed by "clinicians." No specific qualifications (e.g., number of years of experience, specialty) are provided.

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

• Adjudication Method: Not applicable/Not specified. No external adjudication method is described for performance evaluation. The "tests" mentioned are internal performance tests and a usability study.

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

• MRMC Comparative Effectiveness Study: No. The ANScore™ System is described as a device for "heart rate variability measurements" and "paced respiration and controlled exercises" and "not intended for any specific clinical diagnosis." It is not presented as an AI-powered diagnostic tool that assists human readers/clinicians, so an MRMC study comparing human performance with and without AI assistance is not relevant or described.

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

• Standalone Performance: The core function of the device is to measure heart rate variability. While its system performance was tested (e.g., against simulated physiological input), the concept of "standalone performance" for an AI algorithm is not directly applicable in the way it would be for a diagnostic AI. The device itself performs the measurements; its performance is what is being verified, not an AI component that offers an interpretation or diagnosis without human input. No specific data or metrics on this type of standalone performance (e.g., accuracy of algorithmic interpretation) are provided beyond the general statements of "compliance with functional requirements and performance specifications" and "measurement technology... similar" to predicates.

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

• Type of Ground Truth: For the technical performance tests, the ground truth was likely based on the calibrated instrumentation used to simulate physiological input. For the usability study, the "truth" would be the subjective feedback and observations from the clinicians. There is no mention of ground truth established via expert consensus, pathology, or outcomes data, as the device is not for diagnosis, but for physiological measurement.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable/Not specified. The document describes a device that performs measurements, not an AI algorithm that requires a "training set" in the context of machine learning.

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

• Ground Truth for Training Set: Not applicable/Not specified. As the device is not described as involving a machine learning algorithm requiring a training set, this information is not relevant or provided.

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