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Advocate Non-Contact Infrared Thermometer is a non-sterile, reusable, handheld device. It can be used by consumers in homecare environment and doctors in clinic as reference. It is intended for measuring human body temperature of all ranges of people by detecting infrared heat from the forehead.

The Advocate Non-Contact Infrared Thermometer, model EF001S, measures temperatures of people by detecting the infrared energy radiated directly from the forehead without physical contact. The device is composed of a Probe of metals with infrared sensor inside to detect the infrared energy, an LCD Display, a SCAN button to start measuring temperatures, a Power switch button to switch on or off the device, a Body/Ambient button to switch between two measuring modes, and an Enclosure of ABS. The device has the following features: one-second measuring time, measuring Body or Ambient temperature, 12-memory recalls, "F/"C unit switchable, over range message (Hi/Lo), low battery indication, auto display for the last reading when power is on, auto shut-off when the device is idle for 60 seconds and voice function.

Here's a breakdown of the acceptance criteria and study information for the Advocate Non-Contact Infrared Thermometer, Model EF001S, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are derived from the referenced standards, and the reported device performance is indicated by the "Pass" verdict for all tests. Specific numerical criteria are provided for measuring accuracy.

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

• Sample Size for Test Set (Clinical Accuracy): 120 subjects
  • 40 subjects in each age group: infants (0-1 year), children (1-5 years), and adults (>5 years).
• Data Provenance: The document does not explicitly state the country of origin or whether the study was retrospective or prospective. It only mentions "EF001 Clinical Test" and that it "had been clinically assessed."

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

This information is not provided in the document. The study description focuses on meeting the criteria of the referenced standards rather than on a ground truth established by experts in a typical diagnostic AI setting. For a thermometer, the "ground truth" for temperature measurement is typically a highly accurate reference thermometer measurement, not an expert's interpretation.

4. Adjudication Method for the Test Set

This information is not provided in the document. Adjudication methods like 2+1 or 3+1 are typically used for subjective diagnostic tasks involving human readers, which is not directly applicable to a thermometer's performance evaluation against a reference standard.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and 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 type of study is relevant for AI-assisted diagnostic tools where human interpretation is involved. The Advocate Non-Contact Infrared Thermometer is a direct measurement device; its performance is assessed against a technical standard for accuracy, not against human readers.

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

• Yes, a standalone performance assessment was done. The device's accuracy was tested against the standards ASTM E1965-98(2016) and ISO 80601-2-56:2017 directly, without a human in the loop for the temperature measurement itself. The "Clinical Accuracy" testing evaluates the device's ability to accurately measure body temperature.

7. The Type of Ground Truth Used

• The ground truth for the clinical accuracy testing is implicitly the reference measurements of body temperature taken concurrently with the device being tested, as required by the ASTM E1965-98(2016) standard. This standard outlines procedures for evaluating the accuracy of infrared thermometers for intermittent determination of patient temperature, which involves comparing the device's readings to established, highly accurate temperature measurements.

8. The Sample Size for the Training Set

• This information is not provided as this is not an AI/machine learning device that typically involves a distinct training set. The "software validation report" mentioned relates to the device's embedded software functionality, not a learning algorithm trained on data.

9. How the Ground Truth for the Training Set was Established

• This information is not applicable as there is no mention of a training set for a learning algorithm. The software validation ensures the embedded software functions as intended and meets regulatory guidelines.

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