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iHelmet Hair Growth System (Model: LTD200S) is indicated to promote hair growth in females with androgenetic alopecia who have Ludwig-Savin Classifications I - II, in males with androgenetic alopecia who have Norwood Hamilton Classifications IIa - V and for both, Fitzpatrick Classification of Skin Phototypes of I - IV.

iHelmet Hair Growth System consists of laser diodes that are spread throughout the helmet. The product uses diode lasers to cover the entire area of the head that is normally covered with hair, and this unique design allows the treatment of the entire scalp without manual movement. The product will pause automatically treatment if the sensor detects that the head is not in close proximity to the sensor, and will resume again once close enough. At the end of the treatment, an audible tone beeps to indicate the treatment is over and then the helmet automatically shut off.

The provided text is a 510(k) summary for the iHelmet Hair Growth System (Model: LTD200S). It focuses on establishing substantial equivalence to a predicate device, rather than presenting a detailed study proving the device meets specific acceptance criteria based on clinical outcomes.

Therefore, many of the requested details about acceptance criteria, clinical study design, sample sizes for test and training sets, ground truth establishment, expert involvement, and MRMC studies are not explicitly provided in this regulatory document. This document primarily addresses safety and performance through bench testing and comparison to a predicate device.

Here's a breakdown of the information that can be extracted or inferred from the provided text, addressing your points where possible:

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

The document does not present clinical acceptance criteria for hair growth or efficacy. Instead, it relies on demonstrating substantial equivalence to a predicate device based on technical specifications and safety standards. The "acceptance criteria" here are compliance with recognized safety standards and similarity to the predicate device.

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

The document describes bench testing of the device for safety and compliance with standards. It does not mention a clinical test set of patients for efficacy evaluation in the way you might expect for an AI algorithm. Therefore, details about sample size, country of origin, or retrospective/prospective nature of a clinical efficacy study are not provided.

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 this document focuses on regulatory clearance via substantial equivalence and bench testing, not a clinical efficacy study relying on expert-established ground truth. Expert involvement would be for regulatory review, not for establishing ground truth for a test set.

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

Not applicable, for the same reasons as point 3.

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. The iHelmet Hair Growth System is a physical device (infrared lamp) for promoting hair growth, not an AI diagnostic or assistive tool for human readers.

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

Not applicable. This is not an AI algorithm. The device's performance is standalone in its function as a physical device.

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

For the safety aspects, the "ground truth" is compliance with international safety standards (e.g., IEC, ISO).
For the equivalence claim, the "ground truth" is the established safety and efficacy profile of the predicate devices.
There is no mention of a primary clinical efficacy study using patient outcomes data for the iHelmet itself to establish de novo "ground truth" for hair growth.

8. The sample size for the training set

Not applicable, as this is not an AI algorithm requiring a training set.

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

Not applicable, as this is not an AI algorithm requiring a training set.

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