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The PerfectSmooth is an over-the-counter device intended for removal of unwanted hair such as but not limited to small areas such as underarm and facial hair below the chin line and large areas such as legs.

The PerfectSmooth is a personal, light-based, hair reduction device intended to be sold over-the-counter directly to the end user. The device provides hair reduction using IPL technology. And it consists of IPL base unit and AC adapter, and a detachable lamp cap located in the IPL base unit which is the source of optical radiation, namely a Xenon flashlamp. The device is power from AC adapter via an external power.

The provided text describes a 510(k) premarket notification for the "PerfectSmooth" device, which is an over-the-counter light-based hair reduction device. While it details performance data, it primarily focuses on nonclinical testing (biocompatibility, electrical safety, software, eye safety) and a usability study. It does not provide specific acceptance criteria or the results of a study designed to prove the device meets those criteria in terms of clinical effectiveness for hair removal.

Therefore, many of the requested details about acceptance criteria and clinical performance studies cannot be extracted from the provided document.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

This information is not provided in the document. The document lists performance data categories (biocompatibility, electrical safety, software, eye safety, usability, appearance, function, package, reliability) but does not define specific acceptance criteria or report quantitative results for these beyond stating that testing was "completed" or "demonstrated" compliance. Importantly, no clinical performance data for hair reduction is presented.

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

• Clinical Performance Test Set: Not applicable, as a clinical performance study for hair reduction is not detailed.
• Usability Study Test Set:
  • Sample Size: 20 subjects
  • Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).

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 information is not provided in the document. For the usability study, it's not specified how "device human factors" and "label comprehension" were evaluated or if experts were involved in establishing "ground truth" for these assessments. For a clinical study, this information would be critical, but such a study is not described.

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

This information is not provided in the document. Adjudication methods are typically relevant for clinical studies where expert consensus on outcomes is required, which is not detailed here.

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

This is not applicable. The device described is a physical hair reduction device (IPL technology), not an AI-assisted diagnostic or imaging device that would involve human readers.

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

This is not applicable. The device is a physical hardware device, not an algorithm, and its intended use is direct application by the end-user (human-in-the-loop).

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

For the usability study, the "ground truth" would implicitly be the observed human factors and comprehension levels. However, the method of establishing this "ground truth" (e.g., through structured observation, questionnaires, or expert assessment) is not detailed. For clinical efficacy, no ground truth is described because no clinical efficacy study is reported.

8. The sample size for the training set

This is not applicable. The document does not describe an AI/ML model that would require a training set. It refers to "Software verification and validation," implying traditional software development and testing, not machine learning.

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

This is not applicable for the same reason as point 8.

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