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Ageless Health Medical Digital Thermometers are intended for the measurement and monitoring of human body temperature by doctor or consumers in the hospital or home. lt can be used for axillary measurement, oral measurement and rectal measurement.

Ageless Health Medical Digital Thermometers comprises a thermistor for getting temperature signal, a reference resistor for comparing the resistance of the thermistor, a buzzer for sounding effect, an ASIC for processing the target temperature digitally, and a LCD for displaying the temperature result. The design principle of thermometer is based on thermos sensor and ASIC technology. A thermistor is used as thermos sensor. The ASIC gets the sensor's signal from human body, then processes the signal and calculates the result, after that displays the temperature result by a LCD.

The provided document is a 510(k) summary for the "Ageless Health Medical Digital Thermometer." It details the device's characteristics and compares it to predicate devices to establish substantial equivalence.

Here's an analysis of the acceptance criteria and study information based on the document:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the device are largely based on adherence to recognized standards and specific performance metrics, particularly measurement accuracy and range.

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

The document states that the device's safety and performance were evaluated by "lab bench testing" according to a list of standards. However, it does not provide details on the sample size used for these tests. There's also no explicit information on data provenance in terms of country of origin or whether the tests were retrospective or prospective, beyond being "lab bench testing." It is implied that these tests were conducted as part of the device development and verification process.

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

The document does not mention the use of experts to establish ground truth for a test set. The validation appears to be based on engineering and performance testing against established standards for temperature measurement devices.

4. Adjudication method for the test set

Since there is no mention of experts or a subjective assessment test set, there is no adjudication method described. The evaluation is against objective engineering and performance standards.

5. 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

This type of study is not applicable to a digital thermometer. The device is a direct measurement tool, not an AI-assisted diagnostic device requiring human interpretation of complex data. Therefore, an MRMC comparative effectiveness study was not performed, nor is there any mention of AI assistance.

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

The device is inherently a standalone measurement tool. Its performance is evaluated purely on its ability to accurately measure temperature according to the specified standards, without human intervention in the measurement process itself. So, in a sense, a "standalone" performance evaluation was done on the device's core function.

7. The type of ground truth used

The ground truth used for this type of device is established by:

• Reference standards and calibrated equipment: The "lab bench testing" implicitly relies on highly accurate and traceable reference thermometers and controlled environmental conditions as the ground truth for temperature measurement.
• Biological evaluation standards: ISO 10993-5 (in vitro cytotoxicity) and ISO 10993-10 (irritation and skin sensitization) involve standardized biological assays where the "ground truth" is determined by the absence or presence of adverse biological reactions as defined by the standards.

8. The sample size for the training set

The concept of a "training set" is not applicable here as this is a traditional medical device (digital thermometer) and not an AI/machine learning device. The device's operation is based on fixed physical principles and programmed logic, not learned from data.

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

As there is no training set for this device, this question is not applicable. The device's functionality is designed and verified against established engineering and medical standards, not by training on a dataset.

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Ageless Health Medical Digital Thermometers are intended for use in measuring human body temperature (Armpit or Oral).

Ageless Health Medical Digital Thermometers comprises a thermistor for getting temperature signal, a reference resistor for comparing the resistance of the thermistor, a buzzer for sounding effect, an ASIC for processing the target temperature digitally, and a LCD for displaying the temperature result. The design principle of thermometer is based on thermosensor and ASIC technology. A thermistor is used as thermosensor. The ASIC gets the sensor's signal from human body, then processes the signal and calculates the result, after that displays the temperature result by a LCD.

The provided text is a 510(k) summary for the Ageless Health Medical Digital Thermometer, a medical device. It outlines the device's technical specifications and demonstrates its substantial equivalence to a predicate device. However, this document does not contain the information requested regarding acceptance criteria and the study that proves an AI/ML powered device meets those criteria.

Specifically, the document discusses:

• Device identification: Ageless Health Medical Digital Thermometer.
• Regulatory information: Class II medical device, product code FLL, regulation number 21 CFR 880.2910, 510(k) number K152508.
• Intended Use: Measuring human body temperature (armpit or oral).
• Device Description: It's a digital thermometer using a thermistor, reference resistor, buzzer, ASIC, and LCD display.
• Predicate Device: SHENZHEN PUMP MEDICAL SYSTEM CO., LTD. Electronic thermometer (K131210).
• Test Summary: Mentions lab bench testing according to various IEC, ASTM, and ISO standards (e.g., IEC 80601-2-56 for clinical thermometers, ASTM E1112 for electronic thermometers, ISO 10993 for biocompatibility), but does not provide the results of these tests in detail or the specific acceptance criteria met. It only states that "The same tests on Ageless Health Medical Digital Thermometer and the predicate device demonstrate the substantial equivalence of the two."
• Comparison to Predicate Device: A table comparing various elements, including measurement range, accuracy, ambient temperature, and response time. It notes some differences but concludes substantial equivalence because both comply with relevant performance standards.

Therefore, I cannot fulfill the request to describe the acceptance criteria and the study proving the device meets them based on the provided text, as this information is not present for an AI/ML powered device. The document relates to a traditional digital thermometer and focuses on substantial equivalence based on existing standards and predicate device comparison, rather than a novel AI/ML performance evaluation.

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