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Microlife Digital Underarm Thermometer MT18E1-2 is designed specifically for measuring underarm (axillary) temperatures in children ages infant to 6 years old.

Unlike regular thermometers, the unique elbow of the Digital Underarm thermometer is designed to find the "hotspot" easily and comfortably every time. With its predictive technology, it would be able to speed up the measurement time. With these characteristics, this thermometer can provide both a very high clinical accuracy and quick measurement time.

The basic principle of this thermometer is that change of thermistor resistance, caused by changes of temperature, are converted to changes of frequency of R-C oscillator circuit, Therefore, temperature can be given by measuring the frequency of oscillator.

The thermometer adds a fixed offset to match the actual underarm temperature.

Here's a breakdown of the acceptance criteria and study information for the Microlife Digital Underarm Thermometer, Model MT18E1-2, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states compliance with ASTM E1112 and ASTM E1965. For electronic thermometers, these standards typically define accuracy requirements. Although specific numerical acceptance criteria (e.g., ± 0.1°C) and the exact reported device performance (e.g., mean bias, standard deviation of differences) are not detailed in this 510(k) summary, the summary states: "Clinical data was presented which evaluated clinical bias, clinical uncertainty and clinical repeatability per the Microlife Clinical Test Protocol outline." The FDA's issuance of the 510(k) indicates that these criteria were met.

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

• Sample Size: The document does not explicitly state the sample size used for the clinical tests. It only mentions "Controlled human clinical studies were conducted."
• Data Provenance: Not explicitly stated (e.g., country of origin). The studies were "Controlled human clinical studies." Given it's a 510(k) submission to the FDA, it's presumed to be a prospective clinical study, as typical for such submissions.

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

This information is not provided in the document. For thermometer studies, ground truth is typically established by highly accurate reference thermometers and not necessarily "experts" in the same way a diagnostic imaging study would use radiologists.

4. Adjudication Method for the Test Set:

Not applicable or not described in this context. Adjudication methods like 2+1 or 3+1 are typically used for subjective assessments by multiple human readers, not for objective measurements by a thermometer.

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

Not applicable. This is a medical device for measuring temperature, not a diagnostic imaging AI algorithm that would typically involve human-in-the-loop performance measurement or MRMC studies. The device is standalone.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

Yes, a standalone study was performed. The device is a digital thermometer, which inherently functions as a standalone algorithm/device without human input on the measurement itself (beyond correct placement). The clinical studies evaluated the device's direct performance against a reference standard.

7. Type of Ground Truth Used:

The ground truth for thermometer studies is typically highly accurate reference temperature measurements (e.g., using a high-precision clinical reference thermometer or a standardized temperature bath) as defined by standards like ASTM E1112 and E1965. The document states studies were conducted "in accordance with ASTM E1965," which dictates methods for establishing reference temperatures.

8. Sample Size for the Training Set:

Not applicable. This device is a digital thermometer with a fixed algorithm for temperature conversion; it does not involve machine learning with a "training set" in the conventional sense. The "algorithm" refers to the conversion of thermistor resistance to temperature, which is a deterministic process.

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

Not applicable, as there is no "training set" for this deterministic device. The algorithm's accuracy is ensured through calibration and design validation to meet the specified standards.

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