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510(k) Data Aggregation
(125 days)
Lumilisse IPL Hair Remover
The Lumilisse IPL (Intense Pulsed Light) Hair Remover is an over-the-counter device intended for the removal of unwanted hair.
The Lumilisse IPL Hair Remover (Figure 11.1) is a hair-removal device that eliminates unwanted hair from the body (legs and arms), and from more sensitive areas (underarms, bikini line, lower half of the face - below the cheekbones) using intense pulse light technology.
The Lumilisse IPL Hair Remover is an Intense Pulsed Light (IPL) system consisting of:
- . Handset - contained within the handset is the High Voltage Capacitor, Capacitor Charger, Control Electronics and Firmware, Quartz Light Tube, Cooling System, Skin Tone and Skin Contact Sensors and the firmware for operation and safety.
- External Power Supply – used to convert the electricity from the mains supply (either 110V or 230V, 50/60Hz) to a much lower DC value. This power supply unit is an "off-theshelf" component which meets all the relevant electrical safety standards.
- Skin Color Sensor System - For effective and safe treatment, the Lumilisse IPL Hair Remover is equipped with the Skin Sensor System, a skin color detection system that automatically regulates the light intensity applied to the skin.
- . Levels of Intensity - The Lumilisse IPL Hair Remover features 5 levels of intensity, running from the lowest (level 1) to the highest (level of intensity indicates the intensity of the pulsed light applied to the skin when using the Lumilisse Hair Remover.
The provided text describes a 510(k) premarket notification for the Lumilisse IPL Hair Remover. This type of FDA submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than providing rigorous clinical trial data with predefined acceptance criteria and detailed statistical analyses. While a clinical study was conducted, it is not presented in the format of a typical clinical trial report with specific acceptance criteria.
Therefore, many of the requested details regarding acceptance criteria and the study proving the device meets them cannot be fully extracted from the provided text.
Here's a breakdown of what can be inferred and what information is missing:
1. A table of acceptance criteria and the reported device performance
The document does not specify quantified acceptance criteria (e.g., a specific percentage of hair reduction to be achieved) in a table format. The conclusion of the clinical study states:
- "Each of the two units had a significant effect in lowering the amount and density of hairs in regions tested."
- "The dermatological evaluation was positive for safety, and the final study results, for the large majority of the test Subjects, was that the units had the desired effects."
- "The comparative study concluded the Lumilisse Hair Remover reduction results last for 6 months with over 75% less hair on legs and concluded cutaneous acceptability for legs, underarms and half-upper lip."
- "The study concluded Lumilisse Hair Removal Systems as safe and effective when used according to instructions."
From this, we can infer the following as performance outcomes, but not explicitly stated as acceptance criteria that were defined beforehand:
Inferred Performance Metric | Reported Device Performance |
---|---|
Hair Reduction | Significant reduction in amount and density of hairs; over 75% less hair on legs lasting for 6 months. |
Safety | Only safety events appeared unrelated to the units themselves; dermatological evaluation positive for safety; concluded safe. |
Cutaneous Acceptability | Concluded cutaneous acceptability for legs, underarms, and half-upper lip. |
Effectiveness | Concluded effective for hair removal. |
2. Sample size used for the test set and the data provenance
- Sample Size: Not explicitly stated. The text mentions "the large majority of the test Subjects" but does not give a number.
- Data Provenance: The study compared the "G920 and G930 IPL Hair Remover (European pre-cursor to the IPL960F Lumilisse Hair Remover)". This suggests the data might be retrospective from a European market launch or a study conducted for European regulatory purposes, but this is an inference. It doesn't explicitly state "retrospective or prospective" or the specific "country of origin of the data" beyond "European pre-cursor".
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- This information is not provided. The assessment was a "dermatological evaluation," implying dermatologists were involved, but details on their number or qualifications (e.g., years of experience) are missing.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- This information is not provided.
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
- This is not applicable. The device is an IPL hair remover, not an AI-assisted diagnostic or imaging device used by human readers. The study performed was a clinical study on hair reduction and cutaneous acceptability.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- This is not applicable. The device is a physical IPL hair remover, not a software algorithm. Its performance is inherent to the device itself when used by a person.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- The ground truth for effectiveness appears to be clinical outcome data (reduction in hair amount and density, duration of hair reduction, and cutaneous acceptability) assessed via direct observation.
8. The sample size for the training set
- This is not applicable. As a physical device, there isn't a "training set" in the context of machine learning algorithms.
9. How the ground truth for the training set was established
- This is not applicable.
In summary, the provided FDA 510(k) summary focuses on substantial equivalence based on technological characteristics and a general review of non-clinical and limited clinical performance data. It does not contain the detailed structure of a typical clinical study report that would specify exact acceptance criteria, sample sizes beyond general statements, and granular details about expert involvement or ground truth establishment as would be present for software or AI medical devices.
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