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ThermoFlash™ is an infrared thermometer for body surface and forehead temperature measurement for infants and adults without contacting to human body. It can be used by consumers in household environment and doctor in clinic as reference.

ThermoFlash™, including LX-26, LX-261, LX-260 and LX-260T, are handheld electronic thermometer that measures the body temperature based on the infrared sensor technology. All objects emit energy by radiation. The intensity of this energy depends on the temperature of the object. ThermoFlash™ is, therefore, able to measure the temperature of a person by the energy the person emits. Infrared sensor can sense the infrared emissions from the human body (forehead) and environment; then the electronic signal will be transferred by AD module to the digital signal and displayed on the LCD screen.

• A LX-26 is a thermometer with basic temperature measurement functions.
• A LX-260 is an advanced model to LX-26, which provides three additional keys which allow user to select the measurement directly;
• ア LX-261 is an advanced model to LX-260, which provides a rechargeable station base and inner Li rechargeable battery which can be recharged;
• LX-260T is an advanced model, which provides voice indicating of measured temperature.

The provided text is for a 510(k) submission for an infrared thermometer, not an AI/ML powered device. As such, it does not include information typically associated with AI/ML device testing, such as:

• Acceptance criteria directly related to AI/ML performance metrics (e.g., sensitivity, specificity, AUC for a diagnostic algorithm)
• Study design for AI/ML performance evaluation
• Sample sizes for test sets in an AI/ML context
• Data provenance for AI/ML training/testing
• Expert adjudication methods or qualifications
• Multi-reader multi-case (MRMC) studies
• Standalone algorithm performance
• Detailed ground truth descriptions for AI/ML validation
• Training set sample size or ground truth establishment for AI/ML

Therefore, I cannot directly answer your request based on the provided text using the categories you've specified for an AI/ML device.

However, I can extract the acceptance criteria and study information that is present in the document for this non-AI medical device:

Acceptance Criteria and Study for ThermoFlash™ Infrared Thermometer (K112929)

The device, ThermoFlash™ Infrared Thermometer (Models: LX-26, LX-261, LX-260, LX-260T), is intended for body surface and forehead temperature measurement for infants and adults without contacting the human body.

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample size used for the test set and the data provenance:

• Sample Size: Not explicitly stated in the provided text. The document mentions "Bench tests were conducted."
• Data Provenance: Not explicitly stated. Bench tests generally imply controlled laboratory settings.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable/Not stated. This is a non-AI/ML device where performance is typically validated against established measurement standards and reference devices, not human expert interpretation of outputs.

4. Adjudication method for the test set:

• Not applicable/Not stated. Performance is assessed by direct comparison to standard measurements, not expert adjudication.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• No. This type of study is not relevant for this device.

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

• Yes, effectively. The "Bench tests" would represent the standalone performance of the device against a reference standard without human interpretation influencing the measurement itself, beyond proper operation.

7. The type of ground truth used:

• The ground truth would be established by reference standards and calibrated equipment as per the requirements of the listed ASTM and IEC standards for medical thermometers. This would involve comparing the device's readings against highly accurate and traceable temperature measurements.

8. The sample size for the training set:

• Not applicable/Not stated. This device is not an AI/ML product developed through a training set.

9. How the ground truth for the training set was established:

• Not applicable. This device is not an AI/ML product developed through a training set.

Summary of Study:

The primary study mentioned is non-clinical bench testing. These tests were conducted to verify that the proposed device met all design specifications and was Substantially Equivalent (SE) to its predicate device (Remote Infrared Thermometer, RC002, K090361). The documented results demonstrated compliance with:

• IEC 60601-1 (General Requirements for Safety)
• IEC 60601-1-2 (Electromagnetic Compatibility)
• ASTM E1965-98 (R2009) (Standard Specification for Infrared Thermometers for Intermittent Determination of Patient Temperature).

The key conclusion was that the differences between the proposed device and the predicate (additional features like voice indicator, rechargeable battery, and different power supply specifications) were determined "not to affect the performance and effectiveness." This conclusion supports the finding of Substantial Equivalence.

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