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The myAir app is indicated for patients:
• prescribed with a compatible ResMed Air11 platform device to simulate therapy prior to using their device with their prescribed settings. It is an optional software accessory to allow patients to acclimate to their therapy device.
• prescribed a NightOwl wearable device to provide the user interface to operate the connected device and aid in the home sleep testing process.
The device is intended for home and hospital use for:
• new and existing patients of ResMed Air11 PAP therapy devices and
• new users who are prescribed a compatible NightOwl home sleep test (HST).

myAir is a companion mobile medical application ("app") for self-monitoring use of the compatible devices that serve as a patient Home Sleep Test (HST), pre-therapy, and engagement platform for positive airway pressure (PAP) therapy. The app allows the patient to connect via Bluetooth to a compatible hardware device for temporary control of their prescribed HST or PAP device and to allow self-tracking of device usage data. myAir can also be used as a communication pathway using the Bluetooth connection with the compatible device in order to send or receive data. Analysis of patient diagnostic data or display of diagnostic results are not in scope of myAir features.
The subject device modifies the predicate device by adding interoperability with the NightOwl HST (Stella functions) in addition to sustaining previously cleared medical device function of connecting to the Air 1 platform.

The provided text does not contain detailed information about specific acceptance criteria or a dedicated study proving the device meets those criteria. The document is primarily a 510(k) summary for the myAir app, outlining its substantial equivalence to a predicate device and a reference device. It mentions "non-clinical verification and validation testing" but does not elaborate on the specific tests, acceptance criteria, or results.

Therefore, I cannot provide the requested table or detailed information regarding the study.

However, I can extract the available relevant information:

Acceptance Criteria and Device Performance:

The document states: "Non-clinical verification and validation testing completed for NightOwl HST interoperable (Stella) functions introduced with the modifications to the myAir app demonstrated that the device met all intended performance requirements."

This is a general statement that the device met its intended performance requirements, but no specific acceptance criteria (e.g., accuracy metrics, thresholds for errors) or reported device performance data (e.g., a measured accuracy of X%) are provided in the text.

Regarding the study (based on limited information):

• Sample size used for the test set and data provenance: Not specified. The document only mentions "non-clinical verification and validation testing," implying a test set was used, but details on its size or provenance (country of origin, retrospective/prospective) are absent.
• Number of experts used to establish the ground truth for the test set and their qualifications: Not specified. The information provided is about software testing, not clinical performance evaluation that would typically involve expert ground truth.
• Adjudication method: Not applicable/specified. This type of method is typically used in clinical studies with human assessors, which is not described here.
• Multi-reader multi-case (MRMC) comparative effectiveness study: Not mentioned. The document focuses on software interoperability and functional testing, not comparative clinical effectiveness with human readers.
• Standalone (i.e., algorithm only without human-in-the-loop performance) study: The "non-clinical verification and validation testing" likely includes standalone software testing, but specific details or results are not provided. The myAir app acts as a user interface and data transfer mechanism, not an algorithm for diagnostic analysis or interpretation.
• Type of ground truth used: Not specified. For software functional testing, ground truth would typically be defined by expected system behavior and output under various conditions.
• Sample size for the training set: Not applicable and not specified. The myAir app described here is a companion mobile medical application for control and data transfer, not one that employs machine learning models requiring a training set for diagnostic purposes.
• How the ground truth for the training set was established: Not applicable and not specified.

Summary of what is available from the text:

The document concerns the ResMed myAir app (K241216). It states that non-clinical verification and validation testing was performed for the NightOwl HST interoperable (Stella) functions. This testing "demonstrated that the device met all intended performance requirements." The testing followed FDA guidance documents: "Content of Premarket Submissions for Device Software Functions: June 2023" and "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions: September 2023."

The core of the submission is to establish Substantial Equivalence because:

• The subject device (myAir) and predicate device (Galapagos, K200565) have the same intended use.
• They have similar technological characteristics and operating principles.
• The subject device adds interoperability with the NightOwl HST (Stella functions) to its existing cleared function of connecting to the Air11 platform.
• The differences do not raise any new questions of safety or effectiveness.
• It is as safe and effective as the predicate devices.

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