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The Clever Forehead Thermometer/Clever Medical Forehead Thermometer (TD-1241) is an infrared thermometer intended for the non-contact measurement of human body temperature in people of all ages and may be used by medical professionals or by consumers in a home environment.

The Clever Forehead Thermometer/Clever Medical Forehead Thermometer (TD-1241) is a handheld, battery powered, infrared forehead thermometer with a non-contact body temperature measuring function. It detects infrared energy emitted from forehead within 1.2 - 5 cm and converts to a body temperature. This device can be used on people of all ages by medical professionals and consumers in a home environment. The final measured temperature will be displayed on the LCD screen of the device. The users can transmit temperature results from the Clever Forehead Thermometer/Clever Medical Forehead Thermometer to Healthy Check on their mobile devices and Health care management system on pc via Bluetooth. The Healthy check and Health care management system provide an overview of users record with historical data and trend graph.

The provided text describes the regulatory submission for the Clever Forehead Thermometer/Clever Medical Forehead Thermometer (TD-1241). It includes information about non-clinical and clinical testing performed to demonstrate substantial equivalence to a predicate device.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The core performance acceptance criteria for the device are related to its accuracy, as defined by ASTM E1965-98 (2016). The reported performance indicates compliance with this standard.

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

• Sample Size for Clinical Accuracy Test Set: 250 subjects.
• Data Provenance: The text does not explicitly state the country of origin. It does state that the study was "clinical accuracy testing," implying a prospective study where data was collected directly for the purpose of the study.

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

The text states that the clinical accuracy testing compared the Clever Forehead Thermometer/Clever Medical Forehead Thermometer with a "comparator method (WelchAllyn SureTemp PLUS model 690 Thermometer)." This implies that the ground truth was established by a reference device, rather than human experts. Therefore, the concept of "number of experts" or their qualifications is not applicable in this context.

4. Adjudication Method for the Test Set

The concept of an "adjudication method" (like 2+1 or 3+1) is typically used when human experts are disagreeing on a diagnosis or measurement, and a process is needed to resolve those disagreements to establish ground truth. Since the clinical accuracy study used a comparator device as the ground truth, an adjudication method is not described or applicable in this context.

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

No, an MRMC comparative effectiveness study was not reported. The study focused on the accuracy of the device itself against a comparator device, not on how human readers' performance improves with or without AI assistance.

6. Standalone Performance Done

Yes, a standalone performance study was done for the algorithm (the device itself). The "Clinical accuracy testing" directly evaluated the performance of the Clever Forehead Thermometer/Clever Medical Forehead Thermometer (TD-1241) against a comparator method (WelchAllyn SureTemp PLUS model 690 Thermometer) without human-in-the-loop assistance for interpretation.

7. Type of Ground Truth Used

The ground truth used for the clinical accuracy study was established by a comparator device, specifically the "WelchAllyn SureTemp PLUS model 690 Thermometer." This is a form of reference standard.

8. Sample Size for the Training Set

The provided text does not mention a training set sample size. This type of device (an infrared thermometer) typically relies on physical principles and calibration, not a machine learning model that requires a "training set" in the conventional sense of AI/ML. The "software and cybersecurity" section mentions "software life cycle processes" and "software verification and validation," implying traditional software development rather than AI/ML training.

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

As there is no mention of a training set for an AI/ML model, the establishment of ground truth for a training set is not applicable based on the provided text. The device's calibration and accuracy are validated against physical standards and a comparator device.

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