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Children Face Mask is a single use, disposable device that is intended to be worn by children (recommended ages 5-10) to cover the nose and mouth to provide a barrier for the respiratory tract for microorganisms, body fluid and particulate materials. The mask is specifically for child or pediatric patients to provide protection for the respiratory tract. This face mask is recommended for use in a healthcare setting with appropriate adult supervision.

Children Face Mask is a single use, disposable device that is intended to be worn by children (recommended ages 5-10) to cover the nose and mouth to provide a barrier for the respiratory tract for microorganisms, body fluid and particulate materials.

This document is a 510(k) premarket notification decision letter from the FDA regarding a Child Face Mask. It does not contain information about an AI/ML medical device, clinical study, acceptance criteria, or ground truth establishment.

Therefore, I cannot answer your request based on the provided text. The document is about a physical medical device (face mask) and its regulatory clearance, not about the performance or validation of an AI system.

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The Medical 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. This is a single use, disposable device(s), provided non-sterile.

The Medical Face Masks are Flat Pleated type mask, utilizing Ear Loops way for wearing, and they all have Nose Piece design for fitting the face mask around the nose. The Medical Face Masks are manufactured with three layers. The outer layer is made of spun-bonded polypropylene (PP) non-woven fabric. The middle layer with filtration function is made of melt blown polypropylene (PP) non-woven fabric. The inner layer contact with face is made of polypropylene (PP) fabric. The face mask is provided white color. The Medical Face Masks are single use, disposable device, provided non-sterile.

The provided text describes the 510(k) summary for a Medical Face Mask, comparing it to a predicate device. It details the device's characteristics, indications for use, and the non-clinical testing performed to establish substantial equivalence.

However, the request asks for information related to a study proving a device meets acceptance criteria, specifically in the context of an AI/algorithm-based medical device. The provided document is for a physical medical device (face mask) and therefore does not contain the information requested regarding:

• AI/algorithm performance metrics
• Sample sizes for test sets and training sets in an AI context
• Data provenance for AI models
• Number of experts and their qualifications for AI ground truth
• Adjudication methods for AI ground truth
• Multi-reader multi-case (MRMC) studies for AI
• Standalone algorithm performance
• Types of ground truth (pathology, outcomes data) for AI
• Ground truth establishment for training sets in an AI context

Given this discrepancy, I will extract the available "acceptance criteria" and "performance" information from the provided document, which are related to the physical properties and performance of the medical face mask. I will clearly state where the requested information is not applicable or not present in the document.

Acceptance Criteria and Device Performance for Medical Face Mask

The acceptance criteria for the Medical Face Mask are established through its compliance with specific international and national standards. The "device performance" is demonstrated by the test results showing that the proposed device meets these standards and is substantially equivalent to the predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document states that "test results demonstrated that the proposed device complies with the following standards," indicating that the device met the performance requirements specified within each standard for its intended classification (ASTM Level 2).

2. Sample size used for the test set and the data provenance

• Sample Size: Not explicitly stated for each specific test in the provided summary. Performance testing is generally conducted on a representative sample of the device.
• Data Provenance: The tests were conducted by the manufacturer (Shandong Shengquan New Material Co., Ltd., China) to support the 510(k) submission. The document implies these were laboratory tests, not clinical studies.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not applicable. This device is a physical product, not an AI/algorithm-based diagnostic tool requiring expert consensus for ground truth on medical images or data. Ground truth for its performance is established through standardized laboratory testing protocols (e.g., measuring filtration efficiency, fluid resistance, biocompatibility).

4. Adjudication method for the test set

• Not applicable. This is not an AI/algorithm study involving human interpretation or adjudication for ground truth. The evaluation is based on objective, standardized laboratory test results.

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. This is a physical medical device (face mask), not an AI-assisted diagnostic tool. No MRMC study was performed or is relevant.

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

• No. This is a physical medical device, not an AI algorithm. Its performance is inherent to its physical properties, not an algorithm.

7. The type of ground truth used

• The "ground truth" for this device is based on objective measurements and laboratory testing against established physical and biological standards (e.g., filtration rates, fluid resistance, cytotoxicity, skin sensitization). It is not based on expert consensus, pathology, or outcomes data in the context of diagnostic accuracy.

8. The sample size for the training set

• Not applicable. This is a physical device, not an AI model. There is no concept of a "training set" in this context.

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

• Not applicable. As there is no "training set" for a physical medical device, there is no ground truth to be established for it in this context.

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

The Protective Face Mask for Medical Use is a single use, two-panel, flat-folded mask with ear loops and nose piece. The mask is designed into a C-shape when flat-folded. The C-shaped design allows for an expanded chamber for the mask in use. The mask materials include four layers, the inner and outer layers are made of spun-bond polypropylene, and the two middle layers are melt-blown polypropylene and non-woven polypropylene filters, respectively. The elastic ear loops are made of spandex and polyester, which are welded to the facemask to hold the mask in place over the users' mouth and nose. The elastic ear loops are not made with natural rubber latex. The nose piece is a malleable aluminum strip covered with sponge, which is welded to the facemask top edge to allow the user to fit the facemask around their nose. The mask is a single use, disposable device, provided non-sterile in white color.

This document is a 510(k) Premarket Notification submission for a medical device, specifically a "Protective Face Mask for Medical Use." It focuses on demonstrating substantial equivalence to a predicate device based on non-clinical testing.

Here's an analysis of the acceptance criteria and study proving the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document provides a "Performance testing" table (Table 2) that directly addresses this point.

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