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This device is to be used for general relaxation training when used with supported amplifier/encoders.

This software-only component of an EEG biofeedback system uses industry-accepted standard Microsoft Windows-based computers to accept EEG data from external FDAapproved amplifier/encoders and provide biofeedback information. The software does not provide any diagnostic conclusions nor provide any index, classification, diagnosis, or clinical interpretation of the data. The device processes EEG information, separates it into user-specified frequency bands, and displays the results as biofeedback indications to a user.

The provided 510(k) summary for EEGer4 does not contain the kind of detailed study information typically requested for AI/ML-based medical devices or those requiring performance validation against acceptance criteria. This submission is for a much simpler software-only device that processes EEG data for biofeedback, without making diagnostic claims.

Therefore, many of the requested categories cannot be answered from the provided text. The device's "performance" is primarily described by its specifications and comparison to predicate devices, rather than a clinical study establishing diagnostic accuracy.

Here's a breakdown of what can be extracted and what cannot:

1. Table of Acceptance Criteria and Reported Device Performance

For this specific device, a software-only EEG biofeedback system, the "acceptance criteria" are implied by its functional specifications and substantial equivalence to predicate devices, rather than specific accuracy metrics for a diagnostic task. The performance revolves around its ability to process EEG data and display biofeedback.

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

• Not Applicable / Not Provided. This document does not describe a clinical performance study using a test set of patient data, as it's a software for biofeedback, not diagnosis. The "test" in such a context would typically involve software verification and validation (V&V) against functional requirements, but this detail isn't in the summary.

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

• Not Applicable / Not Provided. No ground truth establishment by experts is described for a test set, as no such study is presented.

4. Adjudication method for the test set

• Not Applicable / Not Provided. No test set or adjudication process is described.

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. An MRMC study was not done. This device is not an AI-assisted diagnostic tool; it's a biofeedback display software.

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

• Not Applicable / Not Provided. While the software operates "standalone" in the sense that it processes data and displays it, this refers to its direct functional performance in processing and displaying EEG data according to its specifications, not in making an independent diagnostic decision. The document doesn't detail specific standalone performance metrics in a study context.

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

• Not Applicable / Not Provided. No ground truth for a diagnostic or classification task is used because the device expressly states it "does not provide any diagnostic conclusions nor provide any index, classification, diagnosis, or clinical interpretation of the data."

8. The sample size for the training set

• Not Applicable / Not Provided. This device is not described as an AI/ML model that would require a training set. It is a deterministic software that processes and displays EEG data using established signal processing techniques (separating into frequency bands).

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

• Not Applicable / Not Provided. As noted above, there is no mention of a training set or ground truth establishment for such a set.

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