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510(k) Data Aggregation

    K Number
    K070976
    Date Cleared
    2007-04-20

    (14 days)

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

    RII INFRARED EAR THERMOMETER, MODEL TH01BN

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

    The device is an electronic clinical thermometer using an infrared sensor to detect body temperature from the auditory canal in the neonatal, pediatric and adult population used in the home setting.

    Device Description

    The Radiant Innovation Inc., Infrared Ear Thermometer, Model TH01BN are electronic thermometers using an infrared detector (thermopile detector) to detect body temperature from the auditory canal. Its operation is based on measuring the natural thermal radiation emanating from the tympanic membrane and the adjacent surfaces of the patient.

    To measure ear temperature, the ear thermometer is inserted into a patient's outer ear canal. A start button is pressed to start the measurement through the radiation exchanges. The electrical signal read out from the detector is fed to the circuit for amplification and calculation. The measured temperature then appears on a LCD display. The total operation takes a few seconds.

    AI/ML Overview

    The provided text is a 510(k) summary for the Radiant Innovation Inc. Infrared Ear Thermometer TH01BN. It primarily focuses on demonstrating substantial equivalence to a predicate device based on compliance with voluntary standards and bench testing, rather than a clinical study with detailed acceptance criteria and performance data as typically seen in AI/ML medical devices.

    Therefore, much of the requested information (e.g., sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone performance, training set details) is not present in this document because it describes a traditional medical device (thermometer) and not an AI or machine learning-based device. The "study" referenced is primarily conformance to relevant standards for clinical thermometers.

    However, I can extract information related to the acceptance criteria and reported device performance based on the standards mentioned.

    1. A table of acceptance criteria and the reported device performance

    The document states that the device demonstrated compliance to applicable voluntary standards ASTM E1965-98 and EN12470-5:2003 for clinical electronic thermometers. These standards define the acceptance criteria for accuracy.

    Acceptance Criteria (from Standards)Reported Device Performance (Implied by Compliance)
    ASTM E1965-98:
    Accuracy within specified limits for ear thermometersCompliant with ASTM E1965-98
    Temperature range coveredTested and compliant with the standard's requirements for ear thermometers
    Response timeCompliant with ASTM E1965-98
    EN12470-5:2003:
    General requirements for ear thermometersCompliant with EN12470-5:2003
    Accuracy standardsCompliant with EN12470-5:2003
    Temperature measurement uncertaintyMeets the specified uncertainty limits in the standard

    Note: The specific numerical values for accuracy and other parameters from these standards are not detailed in the provided summary, only that the device "compli(ed) to applicable voluntary standards." The device performance is "reported" as being compliant with these standards.

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

    This information is not provided in the document. The "tests performed" refer to bench testing for compliance with standards, not detailed clinical trial data with patient samples.

    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)

    This information is not applicable and not provided. The ground truth for a physical measurement device like a thermometer is established through traceable calibration standards, not expert consensus in the way an AI model's ground truth for medical images would be.

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

    This information is not applicable and not provided. Adjudication methods are typically used in studies involving human interpretation or annotation, which is not the case for a thermometer's performance testing.

    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

    This information is not applicable and not provided. An MRMC study is relevant for AI-assisted diagnostic tools involving human readers, which this device is not.

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

    This information is not applicable in the context of an infrared ear thermometer. The device itself is a "standalone" instrument for measuring temperature. There is no "algorithm only" performance separate from the device's function.

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

    For a thermometer, the "ground truth" for its accuracy is typically established by comparing its readings against a calibrated reference thermometer in a controlled environment, traceable to national/international standards (e.g., against a black body radiator or a liquid-in-glass thermometer of known accuracy). This is part of the bench testing implied by compliance with ASTM and EN standards.

    8. The sample size for the training set

    This information is not applicable and not provided. This device is an infrared ear thermometer, a hardware device, not an AI/ML model that requires a training set.

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

    This information is not applicable and not provided, as there is no training set for this type of device.

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