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This sunlamp product is intended exclusively for aestetic tanning of the human skin, for one person at a time, at the age of 18 or above.

The primary technical components of sunlamp products are artificial sources of UV radiation as well as a mechanical structure with a defined active surface. UV lamps emit different UV-A and UV-B proportions of the UV radiation. The UV-A proportion primarily generates a superficial tan, which appears rapidly and is intensive but also fades more rapidly. UV-B radiation is primarily responsible for more long-term tanning results. The Ergoline Sunrise 7200 Hybrid Light Technology / Hybrid Technology provides tanning results by combining traditional UV light with red light in a synergistic combination of light spectra.

The provided text is a 510(k) summary for a sunlamp product. This type of document is for demonstrating substantial equivalence to a predicate device, not for proving a device meets specific acceptance criteria through a clinical study in the way an AI diagnostic device would.

Therefore, many of the requested sections about clinical study details (such as sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set details) are not applicable to this document as it describes a Class II sunlamp product, not an AI/ML-driven medical device.

The document primarily focuses on demonstrating that the new device, Ergoline Sunrise 7200 Hybrid Technology, is substantially equivalent to a legally marketed predicate device (Sunrise 6200 and Sunrise 7200, K173565) by comparing their technological characteristics, intended use, and compliance with relevant safety standards.

Here's an attempt to answer the questions based on the available information, noting the inapplicability of some points:

1. Table of Acceptance Criteria and Reported Device Performance

For this type of device, "acceptance criteria" and "reported device performance" are primarily demonstrated through compliance with established safety and performance standards rather than specific diagnostic metrics. The document asserts compliance with these standards.

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

• Not Applicable: This document describes a sunlamp product, not an AI/ML diagnostic or predictive device that typically uses "test sets" of data. The "testing" referred to is for compliance with electrical, mechanical, and safety standards like IEC 62471, IEC 60601-1, IEC 60601-1-2, ISO 10993, and 21 CFR 1040.20. These are engineering/device performance tests, not clinical studies with patient data.

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)

• Not Applicable: As above, this is not an AI/ML diagnostic device requiring expert-established ground truth from clinical data. Compliance is assessed against technical standards.

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

• Not Applicable: No clinical "test set" and thus no adjudication method for ground truth determination.

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 Applicable: This is not an AI-assisted diagnostic device, so no MRMC study would be relevant.

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

• Not Applicable: This is a sunlamp product, not an algorithm, so "standalone performance" in this context is irrelevant.

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

• Not Applicable: The "ground truth" for this device's compliance is defined by the technical specifications and safety standards (e.g., measured irradiance levels, electrical safety parameters, biocompatibility test results). It is not based on clinical outcomes, pathology, or expert consensus on a diagnosis.

8. The sample size for the training set

• Not Applicable: This is a physical sunlamp product and does not involve AI/ML models that require a training set.

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

• Not Applicable: As there is no training set, this question is not applicable.

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