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The Hair Growth System (Model: KN-8000B/KN-8000C/KN-8000E) is intended for the promotion of hair growth in females with androgenic alopecia who have Ludwig-Savin Classifications I-II, and in males with androgenetic alopecia who have Norwood Hamilton Classifications Ila-V; and both genders having Fitzpatrick Classification of Skin Phototypes I-IV.

The Hair Growth System (Model: KN-8000B/KN-8000D/KN-8000E) is hands-free, portable, noninvasive, low-level laser device, which consists of red visible light diode lasers and/or LEDs, to produce red light operating at 650nm wavelength (maximum output power of each is 5mW). The laser sources are arranged in a dot matrix arrangement in the inner of the helmet, which could take into account of every hair follicle and promote rapid hair growth. The device will automatically pause therapy if the user's head is moved outside of the zone of radiation and will resume therapy when the correct head position is reestablished.

The device could be powered by internal rechargeable li-on battery (Rated 7.2Vd.c. 2100mAh), and it can also be supplied by specified external adapter with rated Input 100-240Vac. 50/60Hz and rated Output 9Vdc 3A.

For KN-8000D and KN-8000E, the device emits an audible voice prompt when the treatment is going to start/pause/end, and the device is going to shut down.

This document is a 510(k) premarket notification for a medical device called "Hair Growth System" (Models: KN-8000B/KN-8000C/KN-8000D/KN-8000E). It seeks to demonstrate substantial equivalence to previously cleared devices.

The information provided does not include details about specific acceptance criteria, reported device performance measurements, sample sizes, ground truth establishment, or clinical study designs in the way typically expected for a detailed AI device study. Instead, the submission relies on demonstrating substantial equivalence to predicate devices through technical comparisons and compliance with recognized standards.

Here's an analysis based on the provided text, addressing your questions where possible:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding device performance metrics (e.g., sensitivity, specificity, accuracy). Instead, it relies on demonstrating substantial equivalence to predicate devices through technical comparisons and compliance with relevant safety and performance standards. The "performance" is implicitly demonstrated through adherence to these standards and similarity to already-cleared devices.

The tables provided (pages 6-7) are comparison tables showing technical characteristics of the subject device against predicate devices, with "Verdict" indicating if they are substantially equivalent (SE) or have minor differences. These are not performance metrics in the typical sense for AI, but rather technical specifications.

2. Sample Size Used for the Test Set and the Data Provenance

The document explicitly states: "Clinical performance is not deemed necessary." (Page 10)

Therefore, there was no clinical test set with a specific sample size, nor information on data provenance for such a set. The submission focuses on non-clinical testing and substantial equivalence.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

Since no clinical test set was used, there were no experts establishing ground truth for such a set.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set was used.

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 device is a standalone hardware device (infrared lamp/laser for hair growth), not an AI-powered diagnostic or assistive tool that would involve human readers or MRMC studies.

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

This refers to a standalone hardware device, not a software algorithm. Its "standalone performance" is assessed through compliance with electrical safety, EMC, biocompatibility, usability, and software verification standards. The comparison tables illustrate that its technical specifications (wavelength, output, number of diodes/LEDs) are within ranges or similar to those of its predicate devices, which have already been deemed safe and effective.

7. The Type of Ground Truth Used

Given that "Clinical performance is not deemed necessary," there was no "ground truth" in the sense of expert consensus, pathology, or outcomes data from a clinical trial for the subject device to evaluate its effectiveness. The ground truth for its safety and function is established by compliance with engineering and safety standards (e.g., IEC 60601-1, IEC 60825-1, ISO 10993) and the demonstrated substantial equivalence to predicate devices, which were presumably cleared based on their own safety and effectiveness data (either clinical or through substantial equivalence to even earlier devices).

8. The Sample Size for the Training Set

Not applicable. This is a hardware device submission, not an AI/machine learning algorithm that requires a training set.

9. How the Ground Truth for the Training Set Was Established

Not applicable.

Summary of Device Evaluation in the Document:

The "Hair Growth System" was evaluated through:

• Lab bench testing for:
  • Electrical safety and performance (IEC 60601-1, IEC 60825-1, IEC 62471, IEC 60601-2-57)
  • Electromagnetic compatibility (IEC 60601-1-2)
  • Biocompatibility (ISO 10993-5, ISO 10993-10) for patient-contacting materials
  • Usability (IEC 62366)
  • Software verification and validation (FDA guidance for software in medical devices)
• Comparison to predicate devices (DermaScalp Laser Cap, Capillus devices, iRestore Hair Growth System, iRestore Professional 282) to establish substantial equivalence in terms of:
  • Intended Use
  • Device Type (LLLT)
  • Prescription status (OTC)
  • Waveform and Wavelength (655nm ±5nm, 655nm ±20nm for LED)
  • Amounts of laser diodes/LEDs
  • Laser radiation output (

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