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The device measures the body temperature of a patient by means of a sensor coupled with an electronic signal amplification, conditioning and digital LCD (display) unit. The device is reusable and intended for oral, axillary or rectal temperature measurements for home use on people of all ages.

The 10-second digital thermometer, ST87, ST89, ST80, and ST8B, are the electronic thermometers by using a the temperature sensor. The signal of sensor is calculated and displayed by an ASIC (Application Specific IC) - controlled circuit, which is considered the hard-wire control instead of programmable control. From the construction point of view, the digital thermometer comprises of a thermistor for measuring sensor, a reference resistor for comparison of temperature, a buzzer for sounding effect an ASIC for calculating, and LCD for displaying the measuring temperature digitally for which the thermistor contacts. This system uses a 1.5V DC battery for operation of complete system whenever the battery is low, the ASIC circuit will detect the low battery condition automatically, and displays 'Low battery' in LCD display. Regarding the performance of ST87, ST89, ST80, and ST8B, it was designed and verified according to the US standard ASTM E 1112-98.

This is a 510(k) summary for a digital thermometer, which is a medical device. The information provided heavily references standards for medical devices and does not describe AI/ML software. Therefore, most of the requested information regarding AI/ML clinical studies is not available in the provided text.

Here's an analysis based on the provided text:

Acceptance Criteria and Device Performance (for a digital thermometer)

Note: The provided document is for a digital thermometer, not an AI/ML device. Therefore, the acceptance criteria are based on medical device standards for thermometers, focusing on accuracy, safety, and electromagnetic compatibility.

The following information is not available in the provided text as it pertains to AI/ML device studies, which this device is not.

• Sample size used for the test set and the data provenance: Not applicable. The device is a digital thermometer, not an AI/ML algorithm. Testing would typically involve physical measurements against reference standards, not data sets.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a thermometer is established through calibration against known temperature standards.
• Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
• 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: Not applicable. This is not an AI-assisted device.
• If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. This is a standalone physical device, not an algorithm.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For a digital thermometer, the ground truth would be established by calibrated reference thermometers or temperature sources traceable to national or international standards. This is not mentioned in detail, but implied by adherence to ASTM E1112.
• The sample size for the training set: Not applicable. There is no AI/ML model to train.
• How the ground truth for the training set was established: Not applicable. There is no AI/ML model to train.

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