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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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Surgical mask (with different trade names: Face Mask, Surgical Mask, Surgical Face Mask) is intended for single use by operating room personnel and other general healthcare workers to protect both patients and healthcare workers against transfer of microorganisms, blood and body fluids, and airborne particulates.

Surgical Mask is single use multi-layer mask with outer layer and inner layer (spunbond polypropylene) that sandwich a meltblown polypropylene filter material. There are 2 options for the surgical mask to be secured on user - via earloops or ties. Earloops are of urethane elastic fiber and latex-free; and ties are of spunbond polypropylene and also latex-free. The nose piece is a pliable white aluminum strip, covered by PP covering. All of the materials used in the construction of the Surgical Mask are being used in currently marketed devices.

This is a medical device, not an AI/ML device. The provided text is a 510(k) Summary for a surgical mask, which is a physical product, not a software algorithm. Therefore, the questions regarding acceptance criteria and studies for an AI/ML device are not applicable.

The document discusses the substantial equivalence of the surgical mask to a predicate device based on material, intended use, mask style, design features, and performance test results against established consensus standards (e.g., ASTM, MIL-M, ISO).

Here's a breakdown of the relevant information provided for the surgical mask:

Acceptance Criteria and Device Performance (Surgical Mask)

The acceptance criteria for the surgical mask are implicitly defined by the performance characteristics of the predicate device (K061716) and relevant consensus standards. The study demonstrates that the device "meets" these criteria by showing its performance is similar to or better than the predicate device.

Irrelevant/Not Applicable Information for AI/ML Device Study:

The following questions are not applicable to this 510(k) submission for a surgical mask:

1. Sample sized used for the test set and the data provenance: Not applicable. Performance tests for physical masks follow specific standard protocols, not "test sets" in the AI sense.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for physical mask performance is based on standardized physical and chemical tests, not expert consensus on data interpretation.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
4. 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.
5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Ground truth for a surgical mask's performance is based on physical and chemical testing according to recognized standards (e.g., ASTM, ISO).
7. The sample size for the training set: Not applicable.
8. How the ground truth for the training set was established: Not applicable.

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This device is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material.

FACE MASK, SURGICAL

The provided text is a letter from the FDA regarding a 510(k) premarket notification for a "Face Mask, Surgical Mask, Non-Sterile." This document does not describe an AI/ML device or its performance criteria.

Therefore, I cannot provide the requested information, as the input document does not contain details about:

• Acceptance criteria for an AI/ML device
• A study demonstrating performance against such criteria
• Sample sizes for test or training sets
• Data provenance
• Ground truth establishment or type
• Expert qualifications or adjudication methods
• MRMC studies or standalone algorithm performance.

The document essentially states that the surgical face mask is substantially equivalent to legally marketed predicate devices and can proceed to market.

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