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The Pro Vision Surgical Helmet System consists of disposable surgical apparel and re-usable headgear, battery holder and battery pack. The Pro Vision Surgical Helmet System is intended to be worn by healthcare workers in the operating room during surgical procedures to protect both the healthcare worker and the surgical patient from the transfer of microorganisms, body fluids and particulate material.

The ProVision Surgical Helmet System consists of disposable surgical apparel and re-usable headgear, battery holder and battery pack. The disposable, sterile surgical apparel of the ProVision system include a barrier hood/gown with Hytrel® elastomer, a barrier hood/gown toga with Hytrel, a barrier hood with Hytrel and a paper hood. A molded, polycarbonate face shield is sealed to the hood material. The Hytrel coated material is fluid resistant but vapor transmissive. The gown, toga and hood with Hytrel therefore protect the wearer from fluid borne pathogens, while maintaining "breathability". The barrier hood/gown and barrier hood/gown toga each come in three sizes. The non-sterile, re-usable component of the Pro Vision system is a two piece unit comprised of a helmet and a battery pack. The helmet is a headgear supporting an air delivery system. The air delivery system pulls air from outside the hood or hood/gown, through a filter media, and directs it to the wearer's face/neck area. The air delivery system is powered by a nickel metal hydride battery pack.

The provided text is a 510(k) submission for a surgical helmet system, focusing on its substantial equivalence to existing devices rather than presenting a detailed study with specific acceptance criteria and performance metrics for a novel technology. Therefore, many of the requested categories for a study proving device performance are not applicable or cannot be extracted from this document.

However, I can provide the available information:

Analysis of Acceptance Criteria and Device Performance (Based on provided text)

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

• Not Applicable/Not Provided: The document does not detail a "test set" in the context of a clinical study or a performance study with a specific sample size. The testing mentioned (ASTM ES-21 and ES-22) refers to material property testing, not human subject testing. The provenance of this material testing data (e.g., in-house, third-party lab, country) is not specified.

2. 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)

• Not Applicable: This type of information is relevant for studies involving subjective human assessment (e.g., image interpretation). This submission focuses on material performance and functional equivalence, not human expert evaluations for ground truth.

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

• Not Applicable: There is no "test set" requiring adjudication in the context of this submission.

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: This is not an AI/diagnostic imaging device, and therefore no MRMC study would be relevant.

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

• Not Applicable: This is a physical medical device, not an algorithm, so "standalone performance" in that sense is not relevant. The material tests (ASTM ES-21 and ES-22) could be considered "standalone" tests of the material, but not a software algorithm.

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

• Laboratory Standard Tests: For the material properties, the "ground truth" or standard for acceptance was the successful completion of established laboratory tests (ASTM ES-21 for synthetic blood resistance and ASTM ES-22 for viral penetration).
• Predicate Device Comparability: For the overall system's effectiveness and safety, the "ground truth" for substantial equivalence was its similarity in design and identical intended use to legally marketed predicate devices, and its comparable "adequate filtration efficiency."

7. The sample size for the training set

• Not Applicable: As this is not an AI/machine learning device, there is no concept of a "training set."

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

• Not Applicable: As there is no "training set," this question is not relevant.

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