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The ACON™ 30 Second Reliable Digital Thermometer and the ACON™ Digital Thermometer Probe Covers are intended for the quantitative detection of body temperature, which can be obtained orally, under the arm, and/or rectally. It is intended to be sold over-the-counter for home use by lay persons without any professional training.

The ACON™ 30 Second Reliable Digital Thermometer consists of a temperature sensor within a metal probe and a Liquid Crystal Display all situated within a pen-like housing. The device is intended for the quantitative detection of body temperature, which can be obtained orally, under the arm, and / or rectally. It is intended to be sold over-the-counter for home use by laypeople without any professional training. And it could be used in hospitals as a substitute for the traditional mercury thermometer.

The provided document is a 510(k) summary for the ACON™ 30 Second Reliable Digital Thermometer and its associated probe covers. It details the device's characteristics, intended use, and substantial equivalence to a predicate device.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a pass/fail form for the clinical study. However, it does provide "Technical Specifications" which can be considered the performance targets for the device. The clinical study then aimed to demonstrate substantial equivalence to a predicate, implying these specifications were met.

The conclusion states that a clinical study demonstrated that the device obtained "comparable body temperature measurement data" to a legally marketed digital thermometer and that it was "safe, accurate and easy-to-use," which implies these technical specifications and other performance aspects were met.

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

• Sample Size for Test Set: The document states "Controlled human clinical studies were conducted," and "Clinical study results indicate that the non-professional, inexperienced lay persons were able to obtain comparable body temperature measurement data when using the ACON™ 30 Second Reliable Digital Thermometer." However, the specific sample size (number of subjects or measurements) for these clinical studies is not provided.
• Data Provenance: The document does not explicitly state the country of origin for the data. Given the submitter's identification (ACON Laboratories, Inc. in San Diego, California), it is suggested that the studies likely took place within the United States, but this is not explicitly confirmed. The studies appear to be prospective as they were "conducted" for the purpose of demonstrating equivalence for the 510(k) submission.

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

The clinical studies involved "non-professional, inexperienced lay persons" using the device. The ground truth appears to be based on comparison to a "legally marketed digital thermometer, BD Flexible Digital Thermometer, Model #524034 (K935267)." Therefore, the study did not use "experts" to establish a ground truth in the traditional sense (e.g., radiologists interpreting images). Instead, the reference standard was another device.

4. Adjudication Method for the Test Set

Since the ground truth was established by comparison to a predicate device, and the study focused on "lay persons" obtaining measurements, a formal adjudication method (like 2+1 or 3+1) involving human experts is not applicable or described in this context. The comparison would likely involve statistical analysis of the measurements taken by the ACON thermometer versus the predicate device.

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 is not applicable to this device. This is a digital thermometer, not an AI-assisted diagnostic imaging device that involves human readers interpreting results. The study described is a comparison of a new thermometer to a predicate thermometer.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

This is not applicable in the context of an algorithm. The device itself is a standalone thermometer. Its performance was evaluated in terms of its ability to measure temperature. The "standalone" performance is the device's performance, as it directly outputs a temperature reading. The study evaluated its performance with "human-in-the-loop" in the sense that laypersons used it to take measurements.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The ground truth for the clinical study was based on comparison to a legally marketed predicate device (BD Flexible Digital Thermometer, Model #524034). This means the accuracy and performance of the ACON thermometer were validated against the established performance of another cleared thermometer.

8. The Sample Size for the Training Set

The document does not specify a separate training set. This is typical for a medical device like a thermometer, which does not involve machine learning or AI models that require a distinct "training set" for algorithm development. The device's design and calibration would have been established through engineering and laboratory testing.

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

As there is no explicit training set described in the context of machine learning, this question is not directly applicable. Any calibration or validation for the device's internal operation would have been established by the manufacturer through controlled laboratory conditions, likely using highly accurate reference thermometers or temperature standards.

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