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IPL Hair Removal Device is indicated for the removal of unwanted hair. The device is also indicated for the permanent reduction in hair regrowth, defined as the long-term, stable reduction in the number of hairs regrowing when measured at 6, 9 and 12 months after the completion of a treatment regime.

IPL Hair Removal Device (Models:T1, T2, T3, T7, T10),is an over-the-counter, home-use and singleperson-use 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 and its IPL emission activation is by finger switch. This product adopts irreplaceable flash window and is suitable for multiple hair removal areas. There are four function modes including skin, face,body and bikini for T1 and T7, but only body mode for T3, and five modes including skin, face,underarm,body and bikini for T2 and T10. There are five levels for each mode. The device contains a skin sensor to detect appropriate skin contact, if the device is not in full contact with the skin, the device cannot emit the treatment light pulses.

IPL Hair Removal Device, models:T1, T2, T3, T7, T10 have the same indication for use, performance, structure design and operation. The main difference mainly contains product appearance, dimension , weight , number of keys and function modes, spot size and energy density . The five models are in two colors, one set is in white and the other set is in green.

This document is a 510(k) Summary for an IPL Hair Removal Device. It is a regulatory submission to the FDA, demonstrating substantial equivalence to a predicate device. This type of document does not contain studies on device performance in the way an academic paper or a clinical trial report would, especially regarding specific "acceptance criteria" and "reported device performance" in terms of clinical effectiveness for hair removal.

Instead, the "performance data" section focuses on safety and regulatory compliance rather than clinical efficacy metrics. It confirms that the device meets safety standards (biocompatibility, electrical safety, EMC, eye safety) and software validation requirements.

Therefore, many of the requested categories for acceptance criteria and study details cannot be directly answered from this regulatory summary.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

This document does not present clinical acceptance criteria for hair removal efficacy (e.g., percentage reduction in hair regrowth) or reported device performance against such criteria. The "performance data" section focuses on safety and engineering standards.

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

• For Biocompatibility, Electrical Safety, Eye Safety, and Software Validation: These tests are typically performed on a limited number of device units or components in a laboratory setting. The specific "sample size" of devices or components tested is not provided, but it would not be a "test set" of patient data. The provenance for these engineering and safety tests is typically the manufacturing environment or a third-party testing lab. The document confirms these were conducted by a "reliable third-party lab" (for biocompatibility).
• For Clinical Hair Removal Efficacy: This document does not describe any clinical study for hair removal efficacy with a patient test set. The claim for "permanent reduction in hair regrowth" is listed under "Indications for Use," which implies it is an intended function, but the document does not include data from a study directly demonstrating this on a test set for this specific device. It relies on substantial equivalence to predicate devices which have likely demonstrated this.

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. The document does not describe a clinical study for which a ground truth based on expert consensus would be established for a human test set. For the engineering and safety tests, the "ground truth" is adherence to established international standards, verified by testing specialists at accredited labs.

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

Not applicable, as no human test set or clinical study requiring adjudication is detailed.

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/imaging device, and no MRMC study is described.

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

Not applicable. This is not an algorithm, but a physical IPL device. "Standalone performance" in this context refers to the device operating according to its design specifications regarding light emission, safety features, etc., which is covered by the safety and engineering tests.

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

• For safety and engineering tests: The "ground truth" is compliance with international standards (e.g., ISO 10993, IEC 60601, IEC 62471) as verified by laboratory measurements and procedures.
• For hair removal efficacy: While "permanent reduction in hair regrowth" is stated in the Indications for Use, which would typically require clinical outcomes data or expert assessment in a clinical trial to establish, this document does not present such data for this specific device. It relies on the substantial equivalence to predicate devices, implying those predicate devices have acceptable evidence for this claim.

8. The sample size for the training set

Not applicable. This document does not describe a machine learning or AI model that would require a "training set." The "software" mentioned is for operational control and safety features, not for learning from data related to hair removal.

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

Not applicable, as there is no training set for a machine learning model.

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