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

The Livocare Surgical Mask is a single use, three-layer, flat-folded mask with ear loops and nose piece. The Surgical Mask is manufactured with three layers, the inner and outer layers are made of spun-bond polypropylene, and the middle layer is made of melt blown polypropylene filter. The ear loops are held in place over the users' mouth and nose by two elastic ear loops welded to the surgical mask. The nose piece in the layers of surgical mask is to allow the user to fit the mask around their nose, which is made of malleable polyethylene wire. The mask is a single use, disposable device, provided non-sterile. This device is not made from Natural Rubber Latex.

The provided text is a 510(k) summary for the Livocare Surgical Mask (K201380). It details the device's technical characteristics, intended use, and comparison to a predicate device (K182515). However, this document does not describe a study involving an AI/Machine Learning device. Instead, it outlines the non-clinical performance testing for a surgical mask, an entirely different type of device.

Therefore, I cannot extract information related to acceptance criteria and studies for an AI/ML device because the provided text is about a physical medical device (a surgical mask).

If you have a document describing an AI/ML device, please provide it, and I will be happy to answer your request.

Based on the provided document for the LIVOCARE SURGICAL MASK:

I will extract the requested information as it pertains to this surgical mask, even though it's not an AI/ML device, to demonstrate the structure of the answer you're looking for, given the limitations of the input.

Acceptance Criteria and Study for Livocare Surgical Mask (K201380)

This document describes the premarket notification for a physical medical device, a surgical mask, not an AI/Machine Learning device. Therefore, the "study" described refers to non-clinical performance testing rather than an AI model's performance. Many of the requested categories are not applicable to the evaluation of a surgical mask (e.g., number of experts for ground truth, adjudication method, MRMC study, training set).

1. Table of acceptance criteria and the reported device performance:

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

• Fluid Resistance (ASTM F1862): The test involved 32 samples (implied from "32 out of 32 passed").
• Other performance tests: Specific sample sizes for other tests (Particulate Filtration Efficiency, Bacterial Filtration Efficiency, Differential Pressure, Flammability) are not explicitly stated, but the ASTM/MIL standards typically define the number of samples required.
• Biocompatibility (Cytotoxicity, Irritation, Sensitization): Not specified, but standard biological evaluation batches would be used.
• Data Provenance: The document does not specify the country of origin of the data or whether the tests were retrospective/prospective outside of the standard testing protocol. It is implied these are prospective tests conducted on manufactured samples.

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

• Not Applicable: For a surgical mask, "ground truth" is established by laboratory measurements according to recognized standards (e.g., ASTM, ISO). It does not involve human expert interpretation in the way an AI medical imaging device would. The tests are purely performance-based lab evaluations.

4. Adjudication method for the test set:

• Not Applicable: As these are objective laboratory measurements, no human adjudication for interpreting results is mentioned or would typically be required beyond standard laboratory quality control.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• Not Applicable: This is a physical device (surgical mask), not a diagnostic device involving human reader interpretation. No MRMC study was performed or is relevant for this device.

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

• Not Applicable: This is a physical device; there is no algorithm or human-in-the-loop component. The "standalone performance" refers to the intrinsic performance of the mask itself under specified test conditions.

7. The type of ground truth used:

• Objective Laboratory Measurements/Standardized Test Results: The "ground truth" is defined by the physical and chemical properties of the mask as measured by standardized testing protocols (e.g., fluid penetration, filtration efficiency, flammability, biocompatibility assays).

8. The sample size for the training set:

• Not Applicable: This is a physical device, not an AI/ML model. There is no concept of a "training set" in the context of its premarket evaluation.

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

• Not Applicable: As per #8, there is no training set.

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