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510(k) Data Aggregation
(24 days)
The Optim-Eyes 450 sunglasses are worn by persons to protect the eyes from bright sunlight, including 100% and UVB, and blue light up to 450 nanometers.
The Optim-Eyes 450 are non-prescription sunglasses constructed of commonly used materials for sunglass and spectacle frames and lenses.
The provided text describes the Optim-Eyes 450 Sunglasses, a non-prescription device. The information focuses on its regulatory classification, safety, and substantial equivalence, rather than detailed clinical acceptance criteria or a study proving those criteria.
Here's an analysis based on the provided text, addressing the requested points where possible, and noting where information is not available:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria | Reported Device Performance |
---|---|
Impact Resistance (Drop Ball Test) | All sunglass lots are drop ball tested in accordance with 21 C.F.R. § 801.410. |
UVB Radiation Blockage | Meets and exceeds current ANSI Z80.3 UV standards for "high and prolonged use", blocking virtually 100% UVB radiation. |
UVA Radiation Blockage | Meets and exceeds current ANSI Z80.3 UV standards for "high and prolonged use", blocking virtually 100% UVA radiation. |
Blue Light Attenuation | Strongly attenuates short-wave blue light (up to 450 nanometers as per Indications For Use). |
2. Sample size used for the test set and the data provenance
The document states "All sunglass lots are drop ball tested." This suggests a commitment to testing each manufacturing lot, which implies a sampling strategy rather than a single fixed test set size for regulatory submission. However, the exact sample size per lot or for the UV/blue light testing is not specified.
Regarding data provenance, the testing appears to be conducted by the manufacturer, Taylor/Fox Enterprises, L.L.C. The country of origin of the data is not explicitly stated, but the company is based in Santa Monica, CA, USA, and the submission is to the US FDA, implying testing was likely conducted in the US or under US-standardized conditions. The data is retrospective in the sense that it represents past testing, but it's part of an ongoing quality control process for manufacturing.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This section is not applicable to this device. For non-prescription sunglasses, "ground truth" is established through standardized physical and optical testing against regulatory and industry standards (like 21 C.F.R. § 801.410 for impact and ANSI Z80.3 for UV). It does not involve expert consensus on visual interpretations or diagnoses.
4. Adjudication method for the test set
This section is not applicable. As mentioned above, performance is assessed against objective physical and optical standards, not through expert adjudication of subjective interpretations.
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
An MRMC comparative effectiveness study is not applicable to this device. This type of study is relevant for diagnostic or screening devices where human readers (e.g., radiologists, pathologists) interpret images or data, often with AI assistance. Sunglasses are a protective device, not a diagnostic one.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This section is not applicable. This device is not an algorithm or an AI system. Its performance is inherent to its physical properties.
7. The type of ground truth used
The ground truth used for this device's safety and effectiveness claims is based on:
- Regulatory Standards: 21 C.F.R. § 801.410 for impact resistance.
- Industry Standards: ANSI Z80.3 UV standards for "high and prolonged use" for UV and likely blue light attenuation.
- These are objective, measurable physical and optical properties as defined by established benchmarks, not expert consensus, pathology, or outcomes data in a clinical sense.
8. The sample size for the training set
This section is not applicable. There is no "training set" in the context of this device. A training set is used for machine learning algorithms, which are not involved here.
9. How the ground truth for the training set was established
This section is not applicable for the same reason as point 8.
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