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510(k) Data Aggregation

    K Number
    K202137
    Date Cleared
    2021-03-04

    (216 days)

    Product Code
    Regulation Number
    878.4040
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Disposable Medical 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.

    Device Description

    Disposable Medical Masks are single use, three-layer, flat -folded masks with ear loops and nose clip. The Disposable Medical Masks are 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 which are welded to the facemask. There are two types of ear loops for the disposable medical masks, one shaped in thin rope is made of Nylon and spandex, and the other shaped in narrow band is made of spun-bond polypropylene and elastic body. The ear loops are not made with natural rubber latex. The nose clip in the layers of facemask is to allow the user to fit the facemask around their nose, which is made of malleable polypropylene coating with iron wire. The medical masks will be provided in blue. The medical masks are sold non-sterile and are intended to be single use, disposable devices.

    AI/ML Overview

    This is a 510(k) premarket notification for a Disposable Medical Mask (Model: Y01, Y02) and as such, it does not involve the use of AI. The provided document details the substantial equivalence of the proposed medical mask to a predicate device based on non-clinical performance and biocompatibility testing. Therefore, the questions related to AI-specific acceptance criteria, test sets, ground truth establishment, expert adjudication, MRMC studies, and standalone algorithm performance are not applicable.

    Here's the information extracted from the document regarding the acceptance criteria and the study results for the medical mask:

    1. Table of acceptance criteria and the reported device performance

    ItemReported Device Performance (3 lots)Acceptance Criteria (Level 1, as per ASTM F2100)Result
    Fluid Resistance Performance ASTM F186232 out of 32 pass at 80 mmHg≥ 29 out of 32 pass at 80 mmHgPASS
    Particulate Filtration Efficiency ASTM F229999.12%, 99.45%, 99.56%≥ 95%PASS
    Bacterial Filtration Efficiency ASTM F210199.92%, 99.93%, 99.92%≥ 95%PASS
    Differential Pressure (Delta P) EN 14683 Annex C3.0mmH2O/cm², 4.2mmH2O/cm², 3.7mmH2O/cm²< 5.0mmH2O/cm²PASS
    Flammability 16 CFR 1610Class 1Class 1PASS
    CytotoxicityUnder the conditions of the study, the device is non-cytotoxic.Non-CytotoxicPASS
    IrritationUnder the conditions of the study, the device is non-irritating.Non-IrritatingPASS
    SensitizationUnder the conditions of the study, the device is non-sensitizing.Non-SensitizingPASS

    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 for performance testing: The document specifies "3 lots" for the performance tests (Fluid Resistance, Particulate Filtration Efficiency, Bacterial Filtration Efficiency, Differential Pressure). For fluid resistance specifically, it states "32 out of 32" which refers to the number of mask samples tested within each lot.
    • Sample size for biocompatibility testing: Not explicitly stated as a number of devices, but the results indicate tests were performed and conditions observed.
    • Data provenance: The testing was conducted by or on behalf of U-Play Products Corporation, located in Wuhu City, Anhui Province, China. The document does not specify if the testing was prospective or retrospective, but it's typical for these non-clinical tests to be conducted specifically for the submission.

    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)

    Not applicable. This device is a disposable medical mask, and the "ground truth" for its performance is established through standardized laboratory tests (e.g., ASTM, EN, ISO standards), not expert interpretation of medical images or diagnoses.

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

    Not applicable. The tests are laboratory-based, following standardized protocols, and their results are objectively measured rather than requiring adjudication among experts.

    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 is not an AI-powered device.

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

    Not applicable. This is not an AI-powered device.

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

    The "ground truth" for the device's performance is based on the established technical standards and regulatory requirements (e.g., ASTM F2100 for medical face mask performance, ISO 10993 for biocompatibility). The acceptance criteria for each test (e.g., ≥95% filtration efficiency, non-cytotoxic) serve as the benchmark against which the device's performance is measured.

    8. The sample size for the training set

    Not applicable. This is not an AI-powered device, so there is no training set in the context of machine learning.

    9. 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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