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To measure the human body temperature in regular mode orally, rectally or underarm. The devices are reusable for clinical or home use on people of all ages.

The GF-MT501 and GF-MT502 digital thermometer comprise of a thermistor for measuring sensor, a reference resistor for comparison of the temperature, a buzzer for sounding effect, an ASIC for calculating, and LCD for displaying the measuring temperature digitally for which the thermistor contacts. The thermometers use a DC 1.5V battery for operation of complete system whenever the battery is low, the ASIC circuit will detect the low battery condition automatically, and displays ' in LCD display.

Here's an analysis of the provided information regarding the GF-MT501 and GF-MT502 digital thermometers:

1. Table of Acceptance Criteria and Reported Device Performance:

Note on "Complied with requirements": The provided text states the devices "complied with the requirements" of the listed standards and that bench testing "confirmed" various performance aspects. However, it does not provide specific numerical values for accuracy, temperature range, resolution, or repeatability from these tests. These specific performance metrics are typically defined within the cited standards.

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

• Sample size: Not explicitly stated. The document refers to "bench testing" but does not specify the number of units tested or the number of measurements taken.
• Data provenance: Not explicitly stated. However, since the manufacturer is Hangzhou Universal Electronic Co., Ltd. located in China, it is reasonable to infer the testing was likely conducted in China. The study appears to be prospective bench testing as it was performed to demonstrate compliance for the 510(k) submission.

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

• Not applicable. This study involves bench testing of a medical device (digital thermometer) against technical standards. It does not involve human expert interpretation of data or images to establish a "ground truth" in the way a diagnostic AI study would. The ground truth for temperature measurement would be established by calibrated reference thermometers in a controlled laboratory environment.

4. Adjudication method for the test set:

• Not applicable. As this is bench testing of a physical device against technical standards, there is no need for expert adjudication. The compliance is determined by measurements against specified thresholds and methodologies outlined in the standards (e.g., ASTM E1112).

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. This is a regulatory submission for a simple digital thermometer, not an AI-powered diagnostic device, so an MRMC study is not relevant or included.

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

• Yes, in essence. The testing described is standalone performance testing of the digital thermometer itself. The device's measurement capabilities (accuracy, resolution, etc.) were assessed independently against established standards and reference measurements, without human interaction influencing the measurement process (beyond operating the device in a standard way). However, it's not "algorithm only" in the context of AI, but rather the device's inherent design and functionality.

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

• The ground truth for the bench testing would be calibrated reference measurements from highly accurate and traceable temperature sensors/probes in a controlled laboratory environment, as specified by the testing standards (e.g., ASTM E1112).

8. The sample size for the training set:

• Not applicable. This device is a digital thermometer, not an AI/machine learning model, so there is no concept of a "training set" in the context of the provided documentation.

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

• Not applicable. As there is no training set for an AI model, this question does not apply.

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