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The Wireless thermometer, model TT-100, is a battery-operated electronic device with intended use of measuring human body temperature precisely. This device is single-use and intended for armpit temperature measurement for persons of all age.

The TempTraq™, Model TT-100 patch consists of a temperature sensor integrated circuit mounted to a flexible electronic printed circuit board that also contains a microprocessor and a Bluetooth Low Energy (BLE) radio transmitter. Two 1.5V flexible batteries are attached to the circuit board to supply 3.0V DC internal power. The temperature sensor integrated circuit utilizes diode technology where voltage varies with temperature. The sensor circuit is factory calibrated and converts the voltage to an output temperature. The algorithm for conversion is a proprietary algorithm which compensates for the nearly linear behavior of the diode voltage, providing an extremely accurate temperature measurement.

The Blue Spark Technologies TempTraq™, Model TT-100 is a battery-operated electronic device intended for measuring human body temperature precisely, specifically for armpit temperature measurement for persons of all ages. This device is single-use.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document states that "Clinical testing was not required to establish equivalency of the device." Therefore, there is no test set of clinical data from human subjects reported in this summary. The performance was demonstrated through "bench tests," "System Verification," "Software Verification and Validation," and compliance with voluntary standards.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
Since no clinical testing was performed on human subjects for the test set, no experts were used to establish ground truth for a clinical test set.

4. Adjudication Method for the Test Set
Not applicable, as no clinical test set on human subjects was used.

5. If a Multi-reader Multi-case (MRMC) Comparative Effectiveness Study Was Done
No, an MRMC comparative effectiveness study was not done. The document explicitly states, "Clinical testing was not required to establish equivalency of the device."

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
The document describes "bench tests" and "System Verification" which would inherently be standalone performance evaluations of the device itself and its integrated software/firmware. However, it does not explicitly use the term "standalone performance" in the context of an algorithm or AI. The device's primary function is a temperature sensor and transmitter, not an AI-driven diagnostic algorithm. The accuracy specified (±0.1 °C between 30 °C ~ 42.4 °C) likely comes from these standalone bench tests comparing the device's readings against a known accurate temperature source.

7. The Type of Ground Truth Used
For the bench tests and system verification, the ground truth would have been established by known, calibrated reference temperatures generated by laboratory equipment. This is implied by the nature of "bench tests" for thermometer accuracy.

8. The Sample Size for the Training Set
Not applicable. This device is a thermometer, and its core function relies on direct physical measurement via a diode's voltage proportionality to temperature, combined with a proprietary calibration algorithm. This kind of device does not typically involve "training" in the machine learning sense to establish its fundamental measurement accuracy for in-vitro/in-silico testing. The "proprietary algorithm" for temperature conversion is likely a fixed mathematical model based on physical principles and factory calibration, not a trained machine learning model requiring a training dataset.

9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no mention or implication of a machine learning "training set" for this device. The "factory calibrated" nature of the sensor circuit suggests a one-time calibration process against precise reference temperatures during manufacturing.

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