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The HT-820D Body Infrared Thermometer is intended to measure human body temperature by measuring the forehead from a distance of 5-8 cm. The device can be used on the home and professional healthcare facilities.

The Infrared thermometer is an electronic thermometer using an infrared sensor to detect human body temperature by measuring forehead. The device can be used on people of all ages.

The Infrared thermometer has the following features

• 1 Non-Contact Design.
• 2 Quick results response time less than 1 second.
• Memory function; Memory recall of 34 reading. 3
• 4. Switching between mute and un-mute.
• கு Switching between Fahrenheit and Celsius.
• Power management: auto power off; power display; low power reminder 6
• (7) Automatically power-off, if no operation for 7 seconds.
• Different temperature range display different backlight, over 37.5℃ signals warning tone (8)
• இ Prompt for high temperature.

The provided text describes the acceptance criteria and a study proving that the Dongguan Xintai Instrument Co., Ltd. Body Infrared Thermometer HT-820D meets these criteria for FDA 510(k) clearance.

Here's an analysis of the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

For a clinical electronic thermometer, the primary acceptance criterion is accuracy, typically specified by a standard like ASTM E1965-98 and ISO 80601-2-56. The document explicitly states the subject device's accuracy and the predicate device's accuracy.

Note on Accuracy: While the subject device's stated accuracy (±0.3°C) appears marginally less precise than the predicate's stated best-case accuracy (±0.2°C in a specific range), the "Analysis 2" section clarifies that the subject device "has passed both the non-clinical testing requirements of the ISO80601-2-56 and ASTM E1965-98 testing standards for infrared thermometers and therefore does not raise additional concerns of safety and effectiveness." This implies that its overall performance, including accuracy, meets the established standards for this type of device. The clinical study further verifies non-inferiority.

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

• Sample Size for Test Set (Clinical Study): Total 161 subjects. The subjects were divided into three age groups:
  • Age 0-1: 40 subjects
  • Age 1-5: 36 subjects
  • Age above 5: 85 subjects
  • The study included both febrile and afebrile persons.
• Data Provenance: Not explicitly stated regarding country of origin. However, the manufacturer is Dongguan Xintai Instrument Co., Ltd. in China, and the designated submission correspondent is Beijing Believe-Med Technology Service Co., Ltd. in China. Given this, it is highly probable the clinical study was conducted in China. The study was prospective as it involved conducting controlled human clinical studies on the device.

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

• This information is not provided in the given text. For clinical thermometers, the "ground truth" and comparison are typically established against a reference thermometer (e.g., rectal thermometer or an approved ex-vivo black body calibrator), not human expert readers in the way they would for imaging diagnostics. The text indicates "clinical bias, clinical uncertainty and clinical repeatability have been evaluated per clinical validation for infrared thermometer."

4. Adjudication Method for the Test Set

• This concept is not applicable in the context of a thermometer's accuracy study. Adjudication methods (like 2+1, 3+1) are usually used for interpreting subjective data, such as images where multiple readers assess findings and disagreements need resolution. For a thermometer, the "ground truth" is a measured temperature from a reference device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

• A MRMC study was not conducted. This type of study is primarily relevant for AI-assisted diagnostic tools where human readers interpret medical images or other complex data. For a thermometer, the focus is on the device's accuracy against a reference measurement, not on how it assists human interpretation.
• The study was a comparative effectiveness study in the sense that the subject device's performance was compared to a predicate device (K182597). The "Clinical Test Conclusion" states: "The clinical trial results verify that the clinical accuracy of the subject device is not inferior to that of predicate device." This implies an assessment of non-inferiority, which serves as the effect size/outcome measure, rather than an improvement in human reader performance.

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

• Yes, performance evaluation for the thermometer is inherently standalone for the device itself. The clinical study evaluated the device's accuracy and performance criteria (clinical bias, clinical uncertainty, clinical repeatability) against the predicate device and established standards. The device is a direct measurement tool, not an AI algorithm that assists human interpretation.

7. The Type of Ground Truth Used

• The ground truth for the clinical study was established by comparison to a reference method, as is standard for clinical thermometer validation. The study was conducted "in accordance with ASTM E1965-98," which specifies methods for clinical validation. This typically involves simultaneous measurements using the test thermometer and a highly accurate reference thermometer (e.g., a calibrated contact thermometer) on the same subjects. The text states "clinical bias, clinical uncertainty and clinical repeatability have been evaluated."

8. The Sample Size for the Training Set

• This information is not applicable to this device. The Body Infrared Thermometer HT-820D is a traditional measuring instrument, not a machine learning or AI-based device that requires a "training set" in the computational sense. Its performance is based on its hardware design and embedded firmware, which are validated through non-clinical and clinical testing, not trained on data.

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

• This question is not applicable for the same reason as point 8.

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