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The Aerobika* Oscillating Positive Expiratory Pressure device intended for use as a Positive Expiratory Pressure (PEP) device. The Aerobika* Oscillating PEP device may also be used simultaneously with nebulized aerosol drug delivery. The device is intended to be used by patients capable of generating an exhalation flow of 10 lpm for 3 – 4 seconds.

The Aerobika* OPEP with Manometer device combines Positive Expiratory Pressure (PEP) with oscillations upon exhalation with visual feedback relative to the patient's expiratory pressure. The device is mechanically driven using only the energy from the patient's exhaled breath. Upon exhalation, a portion of the patient's exhaled breath is routed through the manometer device and exits through it. While the manometer is pressurized by the patient's exhaled breath, an indicator contained within the manometer housing indicates the patient's exhaled pressure. The manometer adapter consists of plastic components constructed of polypropylene material, and the manometer is a purchased component to TMI, and is previously cleared under K040991.

This document, a 510(k) Premarket Notification for the Aerobika* OPEP with Manometer, describes non-clinical testing performed to establish substantial equivalence to a predicate device. It does not contain information about clinical studies with human participants. Therefore, many of the requested details about acceptance criteria for clinical performance, ground truth, expert adjudication, or MRMC studies are not applicable or available in this document.

Here's a breakdown of the available information:

1. A table of acceptance criteria and the reported device performance

The document details several non-clinical tests performed. While explicit "acceptance criteria" are not numerically stated in a table format, the narrative indicates that the device "meets specifications and performs comparably to the predicate Aerobika* OPEP device." The performance reported is that the device did meet these specifications.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This document describes non-clinical laboratory testing. Specific sample sizes for each mechanical or environmental test are not provided in this summary. The data provenance is Trudell Medical International, located in London, ON, Canada, conducting design verification and validation activities. The studies are prospective in nature as they are conducted for the purpose of the 510(k) submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. This document describes non-clinical mechanical and material testing, not diagnostic or clinical performance requiring expert ground truth establishment.

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

Not applicable. This document describes non-clinical mechanical and material testing, not diagnostic or clinical performance requiring adjudication.

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 not an AI-assisted diagnostic tool, and no MRMC study was conducted.

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

Not applicable. This device is a mechanical OPEP device, not an algorithm. The "standalone" performance refers to the device's inherent mechanical function. The non-clinical testing evaluates this.

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

For the non-clinical tests, the "ground truth" is established by engineering specifications, recognized standards (like ISO 10993-1:2009 for materials), and the performance characteristics of the legally marketed predicate device (Aerobika* OPEP device, K123400).

8. The sample size for the training set

Not applicable. This document describes a medical device, not a machine learning algorithm that requires a training set.

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

Not applicable, as there is no training set for a mechanical device.

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