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510(k) Data Aggregation

    K Number
    K172427
    Manufacturer
    Date Cleared
    2018-04-19

    (252 days)

    Product Code
    Regulation Number
    880.2910
    Reference & Predicate Devices
    Predicate For
    N/A
    Why did this record match?
    Reference Devices :

    K081160

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    AViTA Radar Thermo NT16 Series IR Thermometer is an infrared thermometers intended for the intermittent measurement of human body temperature from the forehead in people of all ages.

    Device Description

    AViTA Radar Thermo NT16 Series IR Thermometer is hand-held and battery-operated, taking skin temperature mainly in the middle of the forehead. The AVITA Radar Thermo NT16 Series IR Thermometer uses the principle of surveying the natural emission of infrared thermal radiation from the forehead of human body.

    AI/ML Overview

    1. Table of Acceptance Criteria and Reported Device Performance:

    FeatureAcceptance Criteria (from Subject Device)Reported Device Performance (from Subject Device)
    Accuracy (Human Body)$\pm$ 0.2 °C for 34°C ~ 43 °CMeets ASTM E1965, ISO 80601-2-56 (Implied that the device performs within this range)
    Precision (SD)<0.6 °C<0.6 °C
    Repeatability<0.3 °C<0.3 °C (Meets EN 12470-5)
    Operating Temperature Env.15 °C ~ 35 °C15 °C ~ 35 °C (Meets ASTM E1965, ISO 80601-2-56)
    Measurement Range1. Human Body(Forehead) : 34°C ~ 43 °C2. Object : 0°C ~ 100°C1. Human Body(Forehead) : 34°C ~ 43 °C2. Object : 0°C ~ 100°C

    2. Sample Size for Test Set and Data Provenance:

    The document mentions "Clinical evaluation for accuracy was conducted according to ISO 80601-2-56". However, the specific sample size used for the clinical test set is not explicitly stated in the provided text. The data provenance (country of origin, retrospective/prospective) is also not explicitly stated.

    3. Number of Experts and Qualifications for Ground Truth:

    The document does not provide information on the number of experts used or their qualifications to establish ground truth for the test set.

    4. Adjudication Method:

    The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for the test set.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

    The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study, nor does it provide an effect size for human reader improvement with AI assistance. This device is a thermometer, not an AI-assisted diagnostic tool for image interpretation.

    6. Standalone Performance Study:

    A standalone performance study was done for the device, as indicated by the "Clinical evaluation for accuracy was conducted according to ISO 80601-2-56 for the AviTA Radar Thermo NT16IR Thermometer." The results of this study are used to demonstrate substantial equivalence to the predicate device.

    7. Type of Ground Truth Used:

    For the clinical accuracy testing, the ground truth would typically be established by a reference standard thermometer (e.g., a rectal thermometer for core body temperature, or a highly accurate contact thermometer) in a controlled clinical setting, as dictated by standards like ISO 80601-2-56 and ASTM E1965-98 for clinical accuracy of infrared thermometers. The document does not explicitly state the exact method for establishing ground truth, but refers to these standards.

    8. Sample Size for the Training Set:

    The device is an infrared thermometer and is not described as using machine learning or AI that would typically involve a "training set" in the context of image analysis or similar AI applications. Therefore, there is no mention of a training set sample size.

    9. How the Ground Truth for the Training Set Was Established:

    As there is no mention of a traditional "training set" for an AI algorithm, this question is not applicable to the information provided related to this device. The device's operation relies on infrared emission principles and an "algorism," which is likely a fixed mathematical algorithm rather than a machine learning model.

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