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The Face Masks are intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. These face masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. The Face Masks are single use, disposable devices, provided non-sterile.

Face Mask is composed of three layers and is flat-pleated. The mask materials consist of an outer layer (spun-bond polypropylene), a middle layer, between the outer layer and inner layers (melt-blown polypropylene), and an inner layer (spun-bond polypropylene). Each mask contains ear loops to secure the mask over the users' mouth and face and includes a malleable nose piece (Iron wire covered by polypropylene) to provide a firm fit over the nose.

There are two models for Face Mask with different colors and sizes.

For Type A model is in blue, barrier level 2 and size 145mm95mm, ear loop type. For Type B model is in blue, barrier level 2 and size 175mm95mm, ear loop type.

The provided text describes the acceptance criteria and performance data for a medical device (Face Mask) in the context of an FDA 510(k) premarket notification. It focuses on demonstrating substantial equivalence to a predicate device, primarily through non-clinical performance testing.

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

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

Note on Acceptance Criteria: For this 510(k) submission, the "acceptance criteria" are implicitly defined by the performance of the legally marketed predicate and reference devices, as well as by established ASTM and other relevant standards mentioned. The goal is to show that the subject device performs as well as or better than these.

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: The document does not explicitly state the total sample size for each test. For Fluid Resistance (ASTM F1862), it states "32 out of 32 pass," indicating a sample size of 32 for that specific test. For other tests (PFE, BFE, Differential Pressure, Flammability, Biocompatibility), the document states "Pass" or similar, without specifying the exact number of samples tested for each.
• Data Provenance: Not explicitly stated, but given the submission is from Jinhua Jingdi Medical Supplies Co., Ltd. in China, and the submission correspondent is in Shanghai, China, it's highly likely the testing was conducted in China. The document does not specify whether the tests were retrospective or prospective, but performance tests for regulatory submissions are typically conducted prospectively.

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)

This section is not applicable to this document. The "ground truth" for the performance of a surgical face mask is established through objective, standardized laboratory tests (e.g., measuring filtration efficiency, fluid resistance) against predefined metrics, not through expert consensus or interpretation of complex medical imagery. Therefore, there's no mention of experts establishing ground truth in the way one would for an AI diagnostic device.

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

Not applicable. As noted in point 3, the evaluation of face masks relies on objective physical and biological performance tests, not human interpretation that would require adjudication.

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 face mask, not an AI diagnostic tool. Therefore, MRMC studies and AI assistance are not relevant.

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

Not applicable. This device is a physical medical product, not an algorithm.

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

The "ground truth" for this device is the objective measurement of its physical and biological performance characteristics, defined by recognized standards (e.g., ASTM F2100, ASTM F1862, ASTM F2299, ASTM F2101, MIL-M-36954C, 16 CFR PART 1610, ISO 10993 series). This includes:

• Fluid resistance (measured in mmHg)
• Particulate filtration efficiency (measured as a percentage)
• Bacterial filtration efficiency (measured as a percentage)
• Differential pressure (measured in mmH$_2$O/cm$^2$)
• Flammability classification
• Biocompatibility (cytotoxicity, irritation, sensitization, assessed as non-cytotoxic/non-irritating/non-sensitizing)

8. The sample size for the training set

Not applicable. This is a physical medical device, not an AI/machine learning model, so there is no concept of a "training set."

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

Not applicable. See point 8.

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