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Disposable Medical Face Mask is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. This face mask is intended for use in infection control practices to reduce the potential exposure of the wearer to blood and body fluids. The mask is a single use, disposable device, provided non-sterile.

The Disposable Medical Face Mark is blue color, and flat pleated type mask, utilizing ear loops or tie-on way for wearing, and has nose strip design for fitting the facemask around the nose. The colorant used in the mask outer layer is blue: Copper phthalocyanine/ CAS number: 147-14-8). The proposed device is manufactured with three layers, the inner and outer layers made of spunbond polypropylene, and the middle layer is made of melt blown polypropylene filter. The model DY 96, tie-on, is held in place over the user's mouth and nose by four straps welded to the facemask. The straps are made of Spun-bond polypropylene. Its dimension is 17.5x9.5cm, strap is 38 cm, nose strip is 9.5±0.5 cm.

The models MK-34, DY 95 and DY 97, ear loops, are held in place over the user's mouth and nose by two elastic ear loops welded to the facemask. The elastic ear loops are made of Nylon and Spandex, not made with natural rubber latex. The dimension of MK-34 is 14.5x9.5cm, ear loop is 13cm, nose strip is 9.5±0.5 cm. The dimension of DY 95 and DY 97 is 17.5x9.5cm, ear loop is 13 cm, nose strip is 9.5±0.5 cm.

The nose strip contained in the proposed device is in the layers of facemask to allow the user to fit the facemask around their nose, which is made of PE and galvanized iron wire.

The device is sold non-sterile and are intended to be single use, disposable device.

This document is a 510(k) premarket notification for a Disposable Medical Face Mask, not a study describing the performance of a medical device against specific acceptance criteria in the context of an AI/human reader study. Therefore, most of the questions regarding acceptance criteria and study design for AI/human performance are not applicable.

However, I can extract the acceptance criteria and reported performance for the Disposable Medical Face Mask based on non-clinical testing of the physical characteristics of the mask.

Here's the information based on the provided text, focusing on the mask's non-clinical performance and not on AI/human reader studies.

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

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

The document does not specify the exact sample sizes used for each non-clinical performance test (e.g., how many masks were tested for BFE, PFE, etc.). It only provides the results for the different models of the mask. The data provenance is testing conducted for Guangzhou Mei Yi Kang Medical Technology CO., LTD. in China. The tests are non-clinical and relate to product performance, not patient data.

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 question is not applicable. The "ground truth" for this device (a medical face mask) is established by standardized laboratory test methods (e.g., ASTM F2101-14, EN 14683: 2019, ASTM F2299-03, 16 CFR Part 1610, ISO 10993). These are objective measurements performed in a laboratory setting, not based on expert interpretation of medical images or patient outcomes.

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

This question is not applicable. Adjudication methods like 2+1 or 3+1 refer to agreement among experts to establish ground truth in diagnostic studies. The tests conducted for this device are laboratory-based physical and biological performance tests, not diagnostic interpretations requiring expert consensus.

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 question is not applicable. This document is for a Disposable Medical Face Mask, not an AI-powered diagnostic device, and therefore no MRMC study was performed.

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

This question is not applicable. This device is not an algorithm.

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

The "ground truth" for the non-clinical performance of the medical face mask is established by standardized laboratory test methods against predefined performance metrics (e.g., Bacterial Filtration Efficiency, Differential Pressure, Particulate Filtration Efficiency, Synthetic Blood Penetration, Flammability, and Biocompatibility tests according to ISO 10993 standards). These are objective measurements rather than interpretations requiring expert consensus or pathology.

8. The sample size for the training set

This question is not applicable. This document pertains to the performance testing of a physical medical device (face mask), not an AI algorithm. There is no concept of a "training set" in this context.

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

This question is not applicable, as there is no training set for a physical medical device.

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