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CAPOGEN Laser Cap is indicated to promote hair growth in males with androgenic alopecia who have Norwood-Hamilton classifications of Ila-V or females with androgenic alopecia who have Ludwig-Savin Classifications of I-II and both with Fitzpatrick Skin Phototypes I-IV.

The CG-272 CAPOGEN Laser Cap is a dome-shaped low level laser therapy (LLLT) device designed to promote hair growth in women and men by exposing the entire scalp to the photobiostimulation of 272visible red light-emitting diodes at 650mm and 5mW each. The Cap is designed with an outer plastic cover and a protective inner (containing the electronics and laser array) and is powered by an included battery pack. The CG-148 CAPOGEN Laser Cap is exactly the same as the CG-272 with the exception of the number of diodes which is respective of model (148 diodes in CG-148).

The provided text is a 510(k) summary for the CAPOGEN Laser Cap. It outlines the device, its intended use, and a comparison to a predicate device to establish substantial equivalence.

Crucially, this document does NOT describe the acceptance criteria and the study that proves the device meets those acceptance criteria in the format typically associated with an AI/ML medical device approval for performance.

This 510(k) is for a "Laser Cap" (a physical device for hair growth), not an AI/ML algorithm. The performance data section refers to:

• Biocompatibility Testing: Ensuring the device materials are safe for human contact.
• Electrical and EMC Safety: Ensuring the device operates safely in terms of electrical hazards and electromagnetic compatibility.
• Laser Classification: Confirming the laser system meets safety standards.

The "study that proves the device meets the acceptance criteria" in this context is the sum of these engineering and biological safety tests, demonstrating that the device is as safe and effective as its predicate. There is no AI/ML component described, therefore no need for the detailed AI/ML-specific study design elements you requested (sample size for test/training, expert adjudication, MRMC studies, standalone performance, ground truth establishment, etc.).

Therefore, it is not possible to fill in the requested table and information as the document does not pertain to the performance evaluation of an AI/ML medical device for diagnostic or prognostic purposes.

The closest analogue to "acceptance criteria" here would be passing the specified safety and biocompatibility standards, and for "reported device performance," it would be the statement "CAPOGEN Laser Cap was found to have a safety and effectiveness profile that is same as the predicate device."

Summary of what CANNOT be extracted from this document regarding AI/ML device performance:

1. Table of acceptance criteria and reported device performance: Not applicable for AI/ML performance metrics. The "performance" here is about safety and electrical compliance.
2. Sample size for the test set and data provenance: No test set in the AI/ML sense is mentioned.
3. Number of experts used to establish ground truth and qualifications: Not applicable.
4. Adjudication method: Not applicable.
5. Multi Reader Multi Case (MRMC) comparative effectiveness study: Not applicable.
6. Standalone (i.e. algorithm only) performance: Not applicable, as there's no algorithm.
7. Type of ground truth used: Not applicable.
8. Sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

The document demonstrates substantial equivalence based on design, materials, intended use, and safety performance compared to a predicate device, which is a common pathway for physical medical devices.

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