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510(k) Data Aggregation

    K Number
    K211352
    Date Cleared
    2021-09-09

    (129 days)

    Product Code
    Regulation Number
    880.2910
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Electronic Thermometer (XHF2001, XHF2002)

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

    The Electronic Thermometer (XHF2001, XHF2002) is intended to measure the body temperature under the arm and to be used by consumers in household environments for the people of one month of age and above.

    Device Description

    The Electronic Thermometer is hand-held, predictive, thermistor-based, stick themometer capable of measuring temperature. The thermometer uses a negative temperature coefficient thermistor embedded in a measurement tip that is in contact with the measurement site. As the themistor changes tem perature, the resistance of the thermistor also changes, which is measured by the thermometer and converted to a measurement of the temperature of the the thermometer.

    This temperature, following the use of the predictive a lgorithm, is then displayed to theend user. Because the thermometer displays the measurement for the physiological site at which it is used, it does not need to convert this temperature via clinical offset.

    The Electronic Thermometer comprises a probe which includes a thermistor for getting temperature signal, a buzzer for sounding effect, an build-in software for processing the target temperature digitally, battery compartment with cover, a LCD for displaying the temperature result and indicator information, and a Power (On/Off) switch key.

    There are two models of Electronic Thermometer, XHF2002. The two models share same specification, main components (such as LCD, probe, electric circuit and CPU), the only differences are size and appearance.

    The size XHF2001 is 105 x 22 x 12 mm, and the XHF2002 is 125 x 18 x 9.5 mm.

    AI/ML Overview

    The provided document describes the 510(k) premarket notification for the Electronic Thermometer (XHF2001, XHF2002). The information regarding acceptance criteria and supporting studies is extracted and organized below.

    1. Table of Acceptance Criteria and Reported Device Performance

    The device is evaluated against the international standard ISO 80601-2-56: Medical electrical equipment - Part 2-56: Particular requirements for basic safety and essential performance of clinical thermometers for body temperature measurement.

    Acceptance Criteria (from ISO 80601-2-56 and ASTM E1112)Reported Device Performance (XHF2001, XHF2002)
    Accuracy
    $32 ~ 36.9°C (89.6°F~98.42°F) \pm 0.2°C$$32 ~ 36.9°C (89.6°F~98.42°F) \pm 0.2°C$
    $37 ~ 39°C (98.6°F~102.2°F) \pm 0.1°C$$37 ~ 39°C (98.6°F~102.2°F) \pm 0.1°C$
    $39.1 ~ 42.9°C (102.38°F~109.22°F) \pm 0.2°C$$39.1 ~ 42.9°C (102.38°F~109.22°F) \pm 0.2°C$
    Clinical BiasComplies with ISO 80601-2-56
    Clinical ConsistencyComplies with ISO 80601-2-56
    Clinical RepeatabilityComplies with ISO 80601-2-56

    2. Sample Size Used for the Test Set and Data Provenance

    • Test Set Sample Size: A total of 110 subjects were included in the clinical study. These were divided into three age groups:
      • 1 month - 1 year (35 subjects)
      • 1-5 years (35 subjects)
      • Above 5 years (40 subjects)
        The study also included both febrile and afebrile persons.
    • Data Provenance: The document does not explicitly state the country of origin for the clinical study data or whether it was retrospective or prospective. However, the sponsor and correspondent are based in China, suggesting the study likely took place in China. The "Controlled human clinical studies were conducted" implies a prospective study.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

    The document does not provide details on the number or qualifications of experts used to establish the ground truth for the test set. The clinical study evaluated the device's performance against the requirements of ISO 80601-2-56, which typically involves comparing the device's readings to reference thermometer readings.

    4. Adjudication Method for the Test Set

    The document does not describe a specific adjudication method for the test set.

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

    No MRMC comparative effectiveness study was mentioned. The study focused on the standalone performance of the device against a standard.

    6. Standalone Performance

    Yes, a standalone performance study was conducted. The "Controlled human clinical studies were conducted on proposed device with predicates in accordance with ISO 80601-2-56." This involved evaluating the clinical bias, clinical consistency, and clinical repeatability of the proposed device.

    7. Type of Ground Truth Used

    The ground truth used for the clinical study was based on the requirements and methodologies outlined in ISO 80601-2-56. This standard typically involves comparing the electronic thermometer's readings to those of a highly accurate reference thermometer, often under controlled clinical conditions, to determine accuracy, bias, and repeatability.

    8. Sample Size for the Training Set

    The document does not mention a separate "training set" in the context of machine learning. The device described (Electronic Thermometer XHF2001, XHF2002) is a medical device that relies on a thermistor and a predictive algorithm, not a machine learning algorithm that typically requires a large training set in the sense of AI. The software verification and validation were conducted according to general guidance for software in medical devices, not specific to AI/ML training data.

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

    As there is no mention of a traditional machine learning "training set" in the context of this device, this question is not applicable. The "predictive algorithm" in the device is likely based on established physiological models and calibration rather than a trained AI model.

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