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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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The IPL Hair Removal Device is an over-the-counter device intended for removal of unwanted body and or facial hair.

IPL Hair Removal Device (Model: BSXT101, BSXT102, BSXT103, BSXT105, BSXT106, BSXT108), is an over-the-counter, home-use and personal device for hair reduction by using Intense Pulsed Light (IPL). It works below the skin's surface and does not involve any cutting or pulling, reducing hair growth with minimal pain. The device is only powered by the external power adapter (a.c.100~240V 50/60Hz) and its IPL emission activation is by finger switch. It contains a skin sensor to detect appropriate skin contact, if the Light Outlet of the device is not in full contact with the skin, the device cannot trigger a light pulse. The device have six models and these models share the same performance, structure and operation, the only difference is their enclosure color.

The provided document does not contain information about specific acceptance criteria related to clinical performance metrics (e.g., hair reduction percentage, adverse event rates) or a detailed study demonstrating the device meets such criteria. Instead, it focuses on non-clinical studies for safety and functional equivalence to predicate devices.

Therefore, the following information cannot be extracted from the document:

• A table of acceptance criteria and the reported device performance regarding hair removal efficacy.
• Sample size used for a test set (clinical or performance efficacy).
• Data provenance for a clinical test set.
• Number of experts used to establish ground truth for a clinical test set and their qualifications.
• Adjudication method for a clinical test set.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done.
• If a standalone (algorithm only) performance study was done.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.) for a clinical study.
• The sample size for the training set (as no AI/algorithm performance study is described).
• How the ground truth for the training set was established.

However, the document does describe non-clinical studies conducted to demonstrate substantial equivalence, focusing on safety and technical performance.

Here's a summary of the non-clinical studies and their conclusions as presented:

Acceptance Criteria and Reported Device Performance (Non-Clinical):

The document states that non-clinical tests were conducted to verify that the IPL Hair Removal Device meets all design specifications and complies with various safety standards. While specific numerical acceptance criteria for each test are not explicitly detailed (e.g., current limits, specific temperature ranges), compliance with the listed standards serves as the acceptance criterion for these non-clinical aspects.

Study Details:

The non-clinical studies were conducted to support the conclusion of Substantial Equivalence (SE) to predicate devices. These are laboratory-based tests rather than clinical trials with human subjects for efficacy.

1. Sample size used for the test set and the data provenance: Not applicable in the context of clinical efficacy; these were non-clinical, laboratory-based tests on the device itself.
2. 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 ground truth in this context refers to compliance with established technical and safety standards, not clinical diagnoses or outcomes. The tests were performed by a "reliable third-party lab" for biocompatibility.
3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable for non-clinical compliance testing.
4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: No.
5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: No (not an AI/algorithm device in this context).
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For non-clinical tests, the "ground truth" is adherence to the specifications and requirements set forth by the cited international and national standards (e.g., ISO, IEC, ANSI AAMI).
7. The sample size for the training set: Not applicable, as no AI/machine learning algorithm requiring a training set is described in relation to clinical efficacy.
8. How the ground truth for the training set was established: Not applicable.

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