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The NC Thermometer (Gen3) is used orally for the intermittent measurement and monitoring of human body temperature. The device can be used by adults and children over the age of 5 years old.

The purpose of this traditional 510(k) premarket notification is to introduce NC° Thermometer (Gen3). NC° Thermometer (Gen3) is a battery powered, thermistor- based Bluetooth Low Energy (BLE) and Near Field Communication (NFC) enabled adjusted mode digital thermometer that uses a predictive algorithm for the measurement and monitoring of human body temperature. Body temperature is measured orally with the NC° Thermometer. Temperature measurements are displayed on the thermometer and can also (optionally) be transmitted to the Natural Cycles application on the user's smartphone by women over the age of 18. The compatible application displays the thermometer temperature value. The thermometer is reusable for home use on adults and children ages 5 and above. The thermometer is made of biocompatible metals and resins. The thermometer consists of a Negative Temperature Coefficient (NTC) thermistor located in the probe tip to sense human body temperature, three input user facing buttons, an output buzzer for audio indications, a screen for user display, and back lights for illuminating the buttons.

The context provided is for a clinical electronic thermometer, not an AI-powered medical device. Therefore, the information typically requested in questions related to acceptance criteria and study designs for AI/ML-based medical devices (such as sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set details) is not directly applicable or available in this document.

The document primarily focuses on demonstrating substantial equivalence of the NC° Thermometer (Gen3) to a predicate device (Kinsa QuickCare Thermometer) based on technical characteristics, non-clinical testing, and a clinical validation study for its accuracy as a thermometer.

However, I can extract the relevant information regarding the device's performance and the study that proves it meets acceptance criteria as per the provided text for a clinical electronic thermometer.

Device: NC° Thermometer (Gen3)

Device Type: Clinical electronic thermometer

1. Table of Acceptance Criteria and Reported Device Performance

Regarding the study that proves the device meets the acceptance criteria (Clinical Validation Study):

The document provides details of a clinical validation study specifically for the clinical accuracy of the thermometer.

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

   • Sample Size: 105 participants.
   • Data Provenance: Not explicitly stated, but it's a clinical validation study performed to support the performance of the device, implying prospective data collection for this specific purpose. No mention of country of origin.
   • Participant Demographics:
     • 32 (30%) were febrile.
     • All participants were over the age of 5 years old.
     • 64 participants (61%) were female and 41 participants (39%) were male.

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

   • This question is not applicable in the context of a clinical electronic thermometer where the "ground truth" for temperature measurement is typically established by physical reference thermometers or established clinical methods, not by expert interpretation as in imaging AI.
   • The study evaluated the clinical performance of the NC° Thermometer (Gen3) "to a reference clinical thermometer." This reference thermometer established the "ground truth" for temperature.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable. Adjudication methods are typically for subjective expert interpretations (e.g., in radiology image reading), not for objective measurements by a thermometer compared to a reference thermometer.

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:

   • Not applicable. This device is a thermometer, not an AI-assisted diagnostic tool that would involve human readers or MRMC studies.

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

   • The "standalone performance" of the device in this context refers to its intrinsic measurement accuracy and predictive algorithm performance. The non-clinical testing (Design Verification, Software Verification, etc., against standards like ISO 80601-2-56 and ASTM E1112) essentially assesses this standalone performance. The clinical study then validated this performance in a real-world setting.
   • The device does use a "predictive algorithm for the measurement and monitoring of human body temperature," which is an algorithmic component. Its performance is evaluated through the described testing against the standards.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • The ground truth for temperature measurement in the clinical study was established by a reference clinical thermometer compliant with relevant standards (implied, as the study itself was in accordance with ISO 80601-2-56).

8. The sample size for the training set:

   • Not explicitly stated in this document. The document refers to a "predictive algorithm," but details on the dataset used to train this algorithm are not provided within this text. This document focuses on the validation of the final device.

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

   • Not explicitly stated. As above, details regarding the training of the predictive algorithm are not within the scope of this FDA 510(k) summary, which focuses on demonstrating substantial equivalence and validation.

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