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The Carbon Monoxide Breath Sensor System (COBSS) is a breath carbon monoxide monitor intended for single-user use by cigarette smokers in smoking cessation programs to inform the user about how breath carbon monoxide levels are affected by smoking behavior. The device is not intended to be used with other inhaled products.

The Carbon Monoxide Breath Sensor System (COBSS) is a breath carbon monoxide ("CO") monitor intended for single-user over-the-counter ("OTC") use by smokers in smoking cessation programs. The COBSS is a portable, battery-powered device that is composed of the following:

• . CO Breath Sensor. A personal mobile breath sensor capable of measuring the level of CO in exhaled breath.
• . Breath Sensor App. A smart phone app which displays the exhaled breath CO value to the user.

The CO Breath Sensor pairs to the Breath Sensor Application ("BSA") on the smartphone via low-energy Bluetooth. Once paired, the CO Breath Sensor communicates exclusively with the user's phone and is invisible to other devices. The primary screen for the BSA is the CO Log where the most recent exhaled breath CO value in parts-per-million ("ppm") is displayed at the top of the screen. The CO measurements are color coded according to the CO level, and the length of the bar is associated with the ppm value to graphically show the user their relative levels of exhaled breath CO throughout the day and between days.

The Carbon Monoxide Breath Sensor System (COBSS) is a breath carbon monoxide monitor intended for single-user use by cigarette smokers in smoking cessation programs to inform the user about how breath carbon monoxide levels are affected by smoking behavior.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list acceptance criteria in a quantitative table format. However, it implies acceptance through the comparative performance study results and the conclusion of substantial equivalence. Based on the provided text, the implied acceptance criteria were:

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

• Sample Size for Test Set: 70 lay users.
• Data Provenance: The study was a "prospective, open label, single center design." The participants comprised adult smokers, representative of the intended COBSS user profile. The country of origin of the data is not explicitly stated, but given the FDA submission, it is likely the study was conducted in the US.

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

The concept of "ground truth" for the test set is slightly different in this context. The study did not establish a ground truth through expert consensus on CO levels. Instead, it used a predicate device (Micro+ Smokerlyzer) administered by trained personnel as the reference standard for comparative performance. The document states that the predicate device was "submitted with guidance by a health care professional trained in the use of the device." The number and specific qualifications of these "health care professionals" are not detailed beyond "trained in the use of the device."

4. Adjudication Method for the Test Set

There was no explicit adjudication method described for the test set in terms of resolving discrepancies between multiple readers or experts. The comparison was primarily between the COBSS used by lay users and the predicate device used by trained personnel.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a multi-reader multi-case (MRMC) comparative effectiveness study as typically defined for imaging diagnostics (comparing multiple readers' interpretations with and without AI assistance on multiple cases) was not conducted. This study focused on the performance of the device itself (both standalone and with lay users) compared to a predicate, and the usability of the device by lay users. It assessed the ability of lay users to use the device without assistance compared to trained personnel using the predicate device.

• Effect size of human readers improving with AI vs. without AI assistance: Not applicable, as this was not an MRMC study comparing human performance with and without AI assistance. Instead, it compared the COBSS with untrained lay users to a predicate with trained healthcare professionals.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Yes, a standalone performance component was conducted through bench testing. This testing evaluated:

• Sensor performance (accuracy, precision, linearity, H2 Cross Sensitivity)
• Interfering Gases
• Device Use Testing
• Shelf Life/Sensor Drift

These tests evaluate the intrinsic performance of the sensor and device system without human interaction for measurement acquisition or interpretation.

7. Type of Ground Truth Used

The "ground truth" for the comparative performance study was the measurements provided by the predicate device (Micro+ Smokerlyzer) when administered by trained healthcare professionals. This is a form of reference standard comparison against an already cleared and accepted medical device.

8. Sample Size for the Training Set

The document does not provide information on the sample size used for the training set for the COBSS device. This is common for devices of this type where the core technology might be based on established electrochemical sensing, and the "training" may refer more to calibration and validation of the sensor hardware and associated algorithms rather than a conventional machine learning training set with labeled data.

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

Given the lack of information on a "training set" and its size, how ground truth for it was established is also not provided. For sensor-based devices, "ground truth" during development often involves:

• Controlled gas mixtures with known CO concentrations.
• Comparison against highly accurate laboratory reference instruments.
• Characterization of sensor response across its specified range and environmental conditions.

The document mentions "bench testing" which would likely involve such methods for calibrating and validating the sensor's fundamental performance characteristics. However, explicit details on training data ground truth are absent.

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