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The Medical infrared forehead thermometer (Model: HGO1, HGO1 V1, HGO6 ) is a non-contact thermometer intended for the intermittent measurement of human body temperature from forehead for people of one year old and above. The device is reusable for home use and clinical use.

The proposed device. Medical infrared forehead thermometer, which includes model HGO1 VI, HGO6 are hand-held, reusable, battery powered device, which are intended to detect body temperature from forehead of people aged over 1 year.

The proposed devices measure temperatures of people by detecting the infrared energy radiated directly from the forehead without physical contact. The distance of the measurement is 3cm~5cm. The proposed device uses a temperature sensor, which can detect the object temperature [human body temperature], environment temperature of sensor itself; these temperatures are then transfer to electronic signal and amplified; and then it is transferred to digital signal by AD module in MCU of the proposed device. MCU will calculate the body temperature, and then transfer to screen for display.

The devices have the following features: About one-second measuring Body or Ambient temperature, 32-memory recalls, 9 and 9F unit switchable, over range message (Hi/Lo), low battery indication, auto shut-off when the device is idle for 15 seconds. When completes, the results will be displayed on the LCD display screen, and the buzzer will tell the measurement has been completed. The device will display 3 different background colors according to the result.

The power supply of Medical infrared forehead thermometer is 3.0V DC, it is powered by two AAA batteries. The package includes the following parts:

2xAAA batteries, 1xManual and 1 pcs thermometer

This document is a 510(k) summary for a Medical infrared forehead thermometer, demonstrating its substantial equivalence to a predicate device. The information provided focuses on the safety and effectiveness testing for regulatory clearance.

Here's a breakdown of the requested information based on the provided text:

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

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

• Sample Size for Test Set: 100 subjects for clinical tests.
• Data Provenance: The document does not explicitly state the country of origin for the clinical data or whether it was retrospective or prospective. Given the manufacturer's location in China, it is plausible the study was conducted in China.

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

The document does not specify the number or qualifications of experts used to establish ground truth for the clinical test set. It mentions "clinical tests were conducted," and the "clinical accuracy of the proposed device was evaluated by ISO 80601-2-56 - clinical bias with stated uncertainty and clinical repeatability." This implies a comparison against a reference thermometer, but not necessarily against expert human readers.

4. Adjudication method for the test set

The document does not describe any adjudication method (e.g., 2+1, 3+1) for the test set. The clinical study focused on comparing the device's temperature readings against a reference method as per ISO 80601-2-56, not on human interpretation or adjudication of results.

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

No, an MRMC comparative effectiveness study was not done. This device is an infrared thermometer, not an AI-assisted diagnostic device that would involve human readers interpreting images or data. The clinical study was to assess the accuracy of temperature measurement.

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

Yes, a standalone performance assessment was done for the device. The clinical trials evaluated the device's ability to measure temperature accurately on its own. The "device" in this context refers to the thermometer and its embedded algorithms/sensors, not a separate AI algorithm being applied to external data.

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

The ground truth for the clinical performance test was established by comparison with a reference thermometer, implied by the adherence to ISO 80601-2-56, which specifies accuracy testing against a traceable temperature standard. The document mentions "clinical bias with stated uncertainty and clinical repeatability."

8. The sample size for the training set

The document does not explicitly state a "training set" sample size. For simple medical devices like thermometers, there isn't typically a distinct "training set" in the machine learning sense. The device's internal algorithms are developed and calibrated during manufacturing and design, and then validated through laboratory and clinical testing.

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

Not applicable in the machine learning sense of a training set. The "ground truth" for the device's development and calibration would have been established through controlled laboratory measurements using highly accurate reference temperature sources and then verified in a clinical setting as described in point 7.

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