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Light Based Hair Removal Device is an over-the-counter device intended for removal of unwanted body hair.

The Light Based Hair Removal Device 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 Intense Pulsed Light (IPL) technology, and it works below the skin's surface and does not involve any cutting or pulling, reducing hair growth with minimal pain.

The Light Based Hair Removal Device is only powered by the external power adapter and its IPL emission activation is by finger switch. The device contains a Xenon lamp and its built-in skin sensor to detect appropriate skin contact. If the device is not properly and fully applied to the treated skin, the device will not emit the light pulse.

There are A113, A112, and AM001 three models in this application. Their work principle, function, intended use, structure, and composition are the same, with differences being product appearance, size, and energy output density are slight differences, but these parameters are within the predicate device and do not affect or change the intended use of the device.

The provided document is a 510(k) summary for a Light Based Hair Removal Device. It describes the device, its intended use, and compares it to predicate devices. However, the document does not contain the results of a study that establishes acceptance criteria for device performance based on clinical efficacy or specific hair removal results in humans.

This 510(k) summary focuses primarily on demonstrating substantial equivalence to a predicate device through:

• Technological Characteristics Comparison: Showing that the subject device has similar design, wavelength range, energy medium, energy density (within comparable ranges), spot size, pulse duration, pulsing control, and delivery method as the predicate devices.
• Performance Data (Safety Standards): Showing that the device meets various safety standards, including biocompatibility, electrical safety, electromagnetic compatibility (EMC), eye safety, and software verification/validation.

Therefore, I cannot fulfill the request to provide:

1. A table of acceptance criteria and reported device performance (in terms of clinical efficacy for hair removal).
2. Sample size used for the test set and data provenance related to clinical efficacy.
3. Number of experts used to establish ground truth for clinical efficacy.
4. Adjudication method for a clinical test set.
5. MRMC comparative effectiveness study results.
6. Standalone performance related to clinical efficacy.
7. Type of ground truth used for clinical efficacy (e.g., pathology, outcomes data).
8. Sample size for the training set (related to clinical efficacy).
9. How the ground truth for the training set was established (related to clinical efficacy).

The document's "Performance Data" section solely addresses various safety and engineering standards, not clinical efficacy acceptance criteria for hair removal. The "acceptance criteria" discussed in the document are about compliance with these technical safety standards.

Based on the provided document, here is what can be extracted regarding the device performance in terms of safety and engineering standards:

1. Table of Acceptance Criteria and Reported Device Performance (Focus on Safety Standards):

Notes on what cannot be provided from this document:

• This document does not describe a clinical study to prove the device meets acceptance criteria for hair removal efficacy. Instead, it relies on demonstrating substantial equivalence to a predicate device and adherence to various safety and engineering standards.
• There is no mention of sample sizes for clinical efficacy studies, data provenance for such studies, expert involvement in establishing clinical ground truth, or adjudication methods for clinical outcomes.
• No MRMC comparative effectiveness study or standalone algorithm performance for hair removal efficacy is reported.
• The "ground truth" used in this document refers to the established standards for safety, biocompatibility, electrical performance, and software quality, not clinical outcomes related to hair removal.
• The document does not provide details on a training set or how ground truth was established for a training set, as it does not describe an AI/ML-driven device that learns from data in that context. The software validation mentioned is for the device's operational software, not for an AI component for clinical assessment.

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