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The Non-Contact Forehead Thermometer (Model: UT30H) is a reusable, infrared thermometer intended for the intermittent measurement of human body temperature on the forehead of people of all ages. It can be used by consumers in the home environment and doctors in the clinic environment as reference.

The Non-Contact Forehead Thermometer (Model: UT30H) is a hand-held, non-sterile, reusable, batteny powered device designed to measure human body temperature wa body sites: the skin of the forehead.

The Infrared Forehead Thermometer is a battery powered, infrared Thermometer that coverts a user's forehead temperature, using the infrared energy emitted from the area around the user's forehead, to an oral equivalent temperature when placed within 1-5 cm to the subject's forehead with no contact. It uses a thermopile sensor with integrated thermistor for ambient temperature readings.

It composed by a measuring sensor, set buttons, a start button, battery compartment, Buzzer, a LCD and a ABS plastic enclosure, and measuring without probe cover.

The power supply of the thermometer are 3.0V DC, it is supplied by two A AA batteries.

The main functions of Non-Contact Forehead Thermometer are as followings:

• Forehead measure function
• Wide range of temperature readings: from 32.0℃ to 45.0℃(89.6℃ -113.0℃))
• The big LCD display showing clear measure result.
• Low battery indicator

The provided text describes the 510(k) summary for the "Non-Contact Forehead Thermometer (UT30H)" and includes information about its acceptance criteria and the study conducted.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the Non-Contact Forehead Thermometer (UT30H) are primarily based on international standards for clinical thermometers. The reported device performance is stated to be compliant with these standards.

2. Sample size used for the test set and the data provenance

• Sample Size for Test Set: 150 subjects.
• Data Provenance: Not explicitly stated regarding country of origin. The study was a "clinical accuracy study" and did not specify if it was retrospective or prospective, but the phrasing "were performed to determine the clinical accuracy" suggests a prospective clinical study.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not provided in the document. For a non-contact thermometer, ground truth would typically be established by a reference thermometer (e.g., orally, rectally, or invasively) rather than expert consensus on individual readings.

4. Adjudication method for the test set

This information is not provided in the document. Given the nature of a clinical thermometer accuracy study, an adjudication method for individual readings is typically not relevant. The assessment would involve comparing the device's readings against a reference method.

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 is not applicable as the device is a non-contact thermometer, not an AI-assisted diagnostic tool that involves human readers or interpretation of complex medical cases.

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

This is not applicable as the device is a physical thermometer measuring temperature, not an algorithm, and it always involves a human user to operate it. The "standalone" performance here refers to the device's inherent accuracy, which was indeed evaluated.

7. The type of ground truth used

The ground truth used for the clinical accuracy study was presumably a reference body temperature measurement obtained through a validated clinical method (e.g., oral, rectal, or potentially tympanic/temporal, though not specified) against which the non-contact forehead thermometer's readings were compared. The text mentions the device converts to an "oral equivalent temperature," implying a comparison to oral temperature as a ground truth or a gold standard.

8. The sample size for the training set

This information is not applicable or not provided. Clinical thermometers are typically hardware-based devices with embedded algorithms, not machine learning models that require a separate "training set" in the conventional sense. Their calibration and internal algorithms are developed during manufacturing and validated through performance testing rather than a separate training phase.

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

This is not applicable for the reasons stated in point 8.

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