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The surgical mask is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. These masks are in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, disposable device, provided sterile. Serial number: ZZ-YYKZ-01, size 175x95mm, Blue ZZ-YYKZ-02, size 145x95mm, Blue ZZ-YYKZ-03.size 175x95mm, Black ZZ-YYKZ-04, size 145x95mm, Black

The proposed device, Surgical Mask is a three-layer, plane bandage type mask with ear strap and nose clip. The ear straps are held in place over the users' mouth and nose by two elastic ear straps welded to the facemask. The proposed device includes masks in two colors and two sizes, as shown in Table 1. The device is single use and provided sterile.

This document is a 510(k) Summary for a Surgical Mask, submitted to the FDA. It details the non-clinical testing performed to demonstrate that the proposed device is substantially equivalent to a predicate device.

Here's a breakdown of the requested information based on the provided text:

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

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

• Sample Size for performance tests: For Fluid Resistance, Bacterial Filtration Efficiency, Particulate Filtration Efficiency, Differential Pressure, and Flammability, the sample size was "three lots, 32 per lot" for a total of 96 samples per test.
• Data Provenance: The tests were conducted by the submitting company, Guangdong Zhizhen Biological Medical Co., Ltd, which is based in China. The document does not specify if the data is retrospective or prospective, but based on the nature of device testing for 510(k) clearance, it is typically prospective for the purpose of demonstrating performance.

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)

• The document describes non-clinical laboratory testing (e.g., physical properties, filtration efficiency, biocompatibility). It does not involve "experts" establishing ground truth in the sense of medical diagnosis or interpretation of images. The "ground truth" is established by adherence to standardized test methods (e.g., ASTM, ISO, EN standards) and their predefined acceptance criteria. Thus, the expertise lies in the accredited laboratories and personnel performing these specific, standardized tests.

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

• This is not applicable as the study involves standardized laboratory testing against specific criteria, not human interpretation or adjudication of cases.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is typically relevant for AI/imaging devices, not for a surgical mask.

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 surgical mask, not an algorithm. The performance tests are for the physical properties of the mask (e.g., filtration, fluid resistance).

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

• The "ground truth" for these tests is defined by established international standards and regulations (e.g., ASTM F2100-19, ISO 10993 series, EN 14683, 16 CFR 1610, USP ). The performance of the device is measured against the quantitative and qualitative acceptance criteria specified in these standards.

8. The sample size for the training set

• This is not applicable. The submission describes non-clinical testing of a physical device, not an algorithm that requires a training set.

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

• This is not applicable, as there is no training set for a physical device like a surgical mask.

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