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AirView is a web based solution for healthcare specialists intended to:

• assist in the diagnosis of sleep disordered breathing in adult patients through analysis of data recorded by an AirView compatible home sleep device.

• transfer and display machine and therapeutic information that has been transmitted remotely from the patient's therapy device. It is intended to support the standard follow-up care of patients that have been prescribed a compatible ResMed therapy device. AirView also provides remote settings capabilities for non-life support devices only.

AirView is a web application that can transfer, store, analyse, manage, and display machine and therapy data (from ResMed compatible therapy devices) and diagnostic data (from ResMed compatible sleep study devices). The data is transferred from the device either wirelessly through a communications module or with the aid of a data card/USB stick and internet technology to a central database and then displayed on the healthcare professional's computer through a web browser such as Internet Explorer.

The software application enables patient machine and therapy data to be shared across several different user groups for the primary purpose of monitoring patient compliance and home sleep studies. Clinical users and other healthcare specialists can access data with ResMed approved user accounts.

AirView can also be used by the healthcare specialist to remotely change the machine settings of compatible therapy devices. This assists in addressing any clinical issues in a timely manner and providing the necessary patient support. This is restricted to non-life support therapy devices only.

The provided document describes the AirView device, a web-based solution for healthcare specialists. It aims to assist in the diagnosis of sleep-disordered breathing and manage patient therapy data. The submission highlights that the modified AirView device underwent non-clinical testing to demonstrate substantial equivalence to its predicate devices (EasyCare Online (K132371) and ResScan (K140054)). No clinical testing was deemed necessary.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based only on the provided text:

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

The document states that "All tests confirmed the product met the predetermined acceptance criteria". However, the specific quantitative acceptance criteria themselves are not explicitly listed in the provided text. The performance is reported in a descriptive manner, focusing on verification activities.

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

The document mentions "End-to-End testing," "Regression Testing," and "Side-by-Side testing," but it does not specify the sample size for any of these test sets, nor does it provide information about the data provenance (e.g., country of origin, retrospective or prospective nature of the data used in these tests).

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)

The document does not mention the use of experts to establish ground truth for the test set. The testing appears to be focused on technical validation (data transfer, functionality, output comparison) rather than clinical interpretation by human experts.

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

The document does not describe any adjudication method as it does not involve expert consensus or human interpretation for the ground truth.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not done or described in the provided text. The AirView device's primary function is data management, transfer, and display, and to "assist in the diagnosis of sleep disordered breathing in adult patients through analysis of data recorded by an AirView compatible home sleep device," not necessarily to directly improve human reader performance in interpreting images or complex diagnostic output requiring "readers." The "analysis" of data for diagnosis is performed by the system itself based on recorded sleep data.

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

The testing conducted ("End-to-End testing," "Regression Testing," "Side-by-Side testing") assessed the standalone performance of the algorithm/software in terms of data transfer, functionality, and output comparability. The device "assists in the diagnosis" through this analysis, implying it has a standalone analytical component without a human "in the loop" for that specific analytical function.

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

Given the nature of the testing (data transfer, functional verification, output comparison), the "ground truth" implicitly refers to:

• Correct data transmission: Ensuring the data sent matches the data received.
• Expected software behavior: Verifying that existing functionalities remain unchanged and new functionalities operate as designed.
• Concordance with predicate device output: Comparing the output of the modified AirView with a known, cleared predicate device (ResScan) to ensure they produce comparable results.

There is no mention of expert consensus, pathology, or outcomes data being used for ground truth in these non-clinical tests.

8. The sample size for the training set

The document does not mention a training set or any machine learning model training. The described activities are verification testing, not model development or validation.

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

As no training set is mentioned, this information is not applicable or provided.

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The S9 WANDA VPAP ST is indicated for the treatment of Obstructive Sleep Apnea (OSA) in patients weighing more than 66 lb (30 kg). It is intended for use in the hospital and home.

S9 WANDA VPAP ST System is similar to the predicate device (S9 VPAP ST (K102513)). Key features include: inline power supply; integrated humidifier; tubing; colour LCD; and simple controls. The S9 WANDA VPAP ST contains a Micro-processor controlled blower system that generates Continuous Positive Airway Pressure (CPAP) from 3-25 cmHzO as required to maintain an "air splint" for treatment of OSA. The system comprises the flow generator, patient tubing, mask (patient interface) and humidifier. The S9 WANDA VPAP ST flow generator includes the same therapy modes as the S9 VPAP ST system (K102513) predicate device. These base therapy modes include: CPAP and CPAP with expiratory pressure relief (EPR) modes the device delivers a continuous positive airway pressure throughout the therapy session Bilevel mode the flow generator augments any breath initiated by the patient by detecting the onset of inspiration or expiration and delivering the set Inspiratory Positive Airway Pressure (IPAP) and Expiratory Positive Airway Pressure (EPAP) VAuto mode - the mean air-way pressure (between IPAP and EPAP) will alter based upon breathing events The functional characteristics of the S9 WANDA VPAP ST system includes all the clinician and user friendly features of the predicate device which have been verified during usability studies in accordance with IEC 62366 Medical devices - Application of usability engineering to medical devices.

Acceptance Criteria and Study for S9 WANDA VPAP ST

The submission for the S9 WANDA VPAP ST primarily relied on bench testing to demonstrate substantial equivalence to its predicate device, the S9 VPAP ST (K102513). Therefore, the "acceptance criteria" discussed below primarily refer to the performance standards met during these bench tests, which were deemed sufficient to prove a similar level of safety and effectiveness to the predicate. No clinical studies are mentioned.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a formal "acceptance criteria" table with specific quantitative thresholds for each test. Instead, it states that "All tests confirmed the product met the predetermined acceptance criteria" and that these criteria were "traced to the S9 WANDA VPAP ST System Specification and to the predicate device's performance."

However, the "Characteristics (differences) between predicate and new device" and "Flow Generator comparison" sections provide some comparative performance data, which can be interpreted as demonstrating the device's fulfillment of implied acceptance criteria based on equivalence to the predicate.

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

• Sample Size for Test Set: Not applicable as no human-subject clinical test set was used. The study relied on bench testing using a "breathing machine" and the device itself.
• Data Provenance: The bench testing was performed by ResMed Ltd., an Australian company. The testing is therefore attributed to the manufacturer's internal testing procedures. The data would be considered prospective in relation to the submission, as it was specifically generated for the purpose of demonstrating substantial equivalence.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Number of Experts: Not applicable. The "ground truth" for the bench testing was established by comparing the S9 WANDA VPAP ST's performance to the "S9 WANDA VPAP ST System Specification" and the "predicate device's performance." These are engineering specifications and previously established performance metrics, not expert human interpretations of data.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. There was no human "test set" requiring adjudication. The assessment was based on objective measurements against engineering specifications and comparison to the predicate device's measured performance during bench testing.

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

• MRMC Study: No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed. The submission explicitly states "Bench testing alone is sufficient to demonstrate Substantial Equivalence."
• Effect Size of Human Readers with/without AI Assistance: Not applicable, as no human-in-the-loop study with AI assistance was conducted.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: Yes, in a sense. The "bench testing" represents a standalone performance evaluation of the device's algorithms and hardware without a human operator directly influencing its core therapeutic function during the test. The "breathing machine" simulates patient input, and the device's response is objectively measured. This is not "algorithm only" in the modern sense of a software-as-a-medical-device (SaMD) study, but rather the performance of the integrated device's therapeutic functions.

7. Type of Ground Truth Used

• Type of Ground Truth: The ground truth for the bench testing was based on:
  • Engineering Specifications: The S9 WANDA VPAP ST System Specification defined the expected performance.
  • Predicate Device Performance: Direct comparison to the measured performance of the legally marketed S9 VPAP ST (K102513) further served as a "ground truth" for demonstrating equivalence. This is an objective, measured ground truth.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This device is a hardware-based medical device with integrated software that controls its mechanical functions (like pressure generation and response to breathing patterns). It does not employ machine learning or AI models that require a separate "training set" of data in the way modern AI/ML devices do. The software development likely involved traditional engineering verification and validation.

9. How Ground Truth for the Training Set Was Established

• How Ground Truth for Training Set Was Established: Not applicable, as there was no training set in the context of machine learning. The device's operational parameters and control logic were developed through engineering design process, adhering to established medical device standards (e.g., IEC 60601-1, IEC 62304) and based on the predicate device's proven functionality.

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