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The Propeller System includes the Propeller Sensor Model 2018-S. The sensor is an accessory device intended for singlepatient use to assist physicians and patients in recording and monitoring the actuations of prescribed pMDI usage for the Symbicort device.

The Propeller Mobile Application records, stores, and transmits usage events from Propeller Sensors, or via manual user entry, to a remote storage system. With the Propeller Mobile Application the user can review information collected from the pMDI sensor, and report and review symptoms and other information about their disease management and its impact. The user may also share their information with their caregivers, physician, and healthcare providers.

The Propeller Web Application is software that, like the Propeller Mobile Application, is intended to allow users to review the collected information and characteristics of their pMDI and its use, to capture other patient-reported information and outcomes, and to allow that information to be shared with their caregivers, physicians, and health care providers.

When used with a prescribed pMDI, the system can report on information captured during the normal course of use, such as the time between actuations that can be helpful in assessing pMDI technique.

The Propeller System is intended to be used in populations from Child (>2 years) to Adult.

The Propeller System can be used both indoors; home, work, and clinical settings, as well as on aircraft.

The Propeller System may also be used in clinical trials where researchers need to know information about the use of pMDI medication(s) by a participant.

The output of the Propeller System is not intended to diagnosis provided by a licensed physician. The Propeller System is not intended for use as an pMDI dose counter, nor is it intended to indicate the quantity of medication remaining in an pMDI.

Pressurized Metered Dose Inhaler (pMDI) / Symbicort Accessory that monitors inhaler usage. The portable sensor mounts to the back of the pMDI and records inhalation events when the inhaler is used.

This document is a 510(k) Premarket Notification from the FDA regarding the "Propeller Sensor for Symbicort" (Model 2018-S). It asserts that the device is substantially equivalent to a previously cleared predicate device (Propeller Sensor Model 2017-B).

Based on the provided text, the device in question is a sensor that attaches to a Pressurized Metered Dose Inhaler (pMDI) to record and monitor its usage. The main purpose of the testing described here is to demonstrate that the new model (2018-S) is substantially equivalent to the previous model (2017-B), especially regarding its ability to detect and record inhaler actuations, and its safety.

Here's an analysis based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or a direct performance table for features like accuracy of actuation detection. Instead, it relies on demonstrating substantial equivalence to a predicate device. The "Test Summary" statement, "Test results indicate that the Propeller Sensor Model 2018-S and its predicate Propeller Sensor Model 2017-B complies with predetermined specifications. Software verification and validation testing confirms this result," acts as the overall conclusion of meeting the implicit criteria of functioning similarly and safely to the predicate.

The primary comparison is regarding technological characteristics and their sameness between the new device and the predicate. The table on page 6-7 serves as the direct "comparison" showing where the devices are similar or identical.

Here's how we can infer the "acceptance criteria" and "performance" from this document:

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

• Sample Size: The document does not specify a sample size for any specific "test set" or the number of devices or uses tested. It generally refers to "bench testing."
• Data Provenance: Not explicitly stated, but given it's a submission to the FDA for a medical device company in Madison, WI, the testing would typically be conducted by the manufacturer, which is usually in the U.S. or through their contract labs. The document does not indicate if data was retrospective or prospective in the sense of clinical study data, as no clinical testing was required or performed.

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

• Not applicable. This submission focuses on engineering and performance testing to demonstrate substantial equivalence, not on establishing a "medical ground truth" from experts interpreting diagnostic data (like radiology images). The device's function is to record actuation events, not to interpret complex medical data.

4. Adjudication Method for the Test Set

• Not applicable. As there's no interpretation of complex data by multiple readers necessitating adjudication, this method is not relevant to the type of testing described (bench testing, software verification/validation, electrical safety).

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

• No. An MRMC study was not conducted. The document explicitly states: "Clinical Testing: No clinical testing was required." The device is intended as an accessory to record pMDI usage, not to provide diagnostic interpretations that would assist human readers in an MRMC setting.

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

• Yes, in essence. The testing described (bench testing, software verification/validation) is a form of standalone performance evaluation of the device's ability to detect and record inhaler actuations, and its software's ability to process and display that data accurately. The core function of the device (detecting actuation) is an algorithmic function performed by the sensor. The reported "Test Summary" and "Conclusion" indicate this standalone performance meets "predetermined specifications" and is "substantially equivalent" to the predicate.

7. The Type of Ground Truth Used

• For the core function of detecting pMDI actuations: The "ground truth" would be the actual physical actuation events of the pMDI during bench testing. This would be established by direct observation or synchronized, validated measurement techniques during the testing process. The device's recorded actuation event would be compared against the actual event occurring.
• For compliance with standards (IEC, ISO): The ground truth is the specified requirements within those engineering and safety standards. The device's performance is measured against these established quantitative and qualitative criteria.

8. The Sample Size for the Training Set

• Not applicable. This device is a sensor that records physical events and transmits data. It's not described as an AI/ML algorithm that requires a "training set" in the conventional sense of machine learning for classification or prediction tasks based on complex data (e.g., image analysis). The "algorithms" would be embedded logic for event detection and data processing, which are validated through standard software V&V and bench testing.

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

• Not applicable. (See point 8).

In summary, this 510(k) submission establishes substantial equivalence primarily through comparing the new device's engineering specifications and performance (demonstrated through bench testing and compliance with recognized standards) to a previously cleared predicate device. It avoids significant clinical studies or complex AI/ML "training/ground truth" methodologies because its function is a relatively straightforward data acquisition task rather than a diagnostic interpretation or predictive AI model.

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