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Aluna 2 is intended for monitoring FEV1 (Forced exhalation in the first second) and PEF (Peak Expired Flow Rate) for home use. The device is designed for pediatric to adult users. Aluna is not recommended for children under 5 years of age. Additionally, the device may be used by clinicians for in-office monitoring.

Aluna 2 consists of three main components:

• A small hand-held peak flow meter that captures differential pressure, converts it to digital data points, and transmits the data to a mobile device via Bluetooth.
• A mobile application that collects and transmits the differential pressure readings from the spirometry device and processes it to estimate the exhaled air flow rate and volume.
• An Application Programming Interface (API) to facilitate communication with a cloud server used for data storage.

The provided text is a 510(k) summary for the medical device Aluna 2, a peak flow meter for spirometry. It compares the Aluna 2 to its predicate device, the original Aluna, and details the non-clinical testing performed to establish substantial equivalence.

However, the document explicitly states: "Clinical testing was not required." This means there was no clinical study conducted involving human subjects to directly prove the device meets acceptance criteria for improved human reader performance with AI assistance, or standalone performance against clinical ground truth.

Therefore, many of the requested points regarding acceptance criteria and study design for clinical or AI-driven performance cannot be answered from the provided text, as this type of study was not performed. The device's substantial equivalence was demonstrated through non-clinical bench testing and adherence to standards for accuracy, safety, and software.

Here's an analysis of what can be extracted from the document regarding acceptance criteria and performance, focusing on the technical specifications and non-clinical testing:

Acceptance Criteria and Reported Device Performance (Non-Clinical)

The acceptance criteria are derived from the specified accuracy, linearity, repeatability, and impedance/resistance limits required by the "2019 ATS Update v. 2005 ATS Guidelines" and ISO standards. The reported device performance is implicitly demonstrated by the statement: "The results of these tests indicate that Aluna 2 is substantially equivalent to the predicate device." and the fact that it tightened some specifications compared to the predicate.

As for the specific questions regarding a study that proves the device meets acceptance criteria, based on clinical performance or AI-driven insights, the document explicitly states:

1. Sample sizes used for the test set and the data provenance: Not applicable. No clinical test set involving human data was used for a clinical study comparing AI performance or human reader improvement. The "test set" for non-clinical performance would be the calibrated flow and volume generators used in the lab. Data provenance is not specified beyond "non-clinical performance bench testing."
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No human experts were involved in establishing ground truth for a clinical or AI performance test, as there was no clinical study. The ground truth for bench testing would be from calibrated reference standards.
3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. No clinical test set requiring adjudication.
4. 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. The device is a direct measurement spirometer, not an AI-assisted diagnostic imaging or classification tool for human readers.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The device is largely standalone in its primary operation (measuring FEV1 and PEF). The "algorithm only" performance is evaluated by the non-clinical bench testing for accuracy, linearity, and repeatability against calibrated flows and volumes. The table above details these performance metrics.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the performance (accuracy, linearity, repeatability) of the device, the ground truth was established by calibrated reference standards/simulators as per ISO and ATS guidelines during bench testing. No biological or clinical ground truth (like pathology or outcomes) was used for device functional performance evaluation for this 510(k).
7. The sample size for the training set: Not applicable. This refers to an AI/machine learning training set. The Aluna 2 is a measurement device that calculates FEV1 and PEF based on differential pressure readings, not a device that uses machine learning models trained on large datasets.
8. How the ground truth for the training set was established: Not applicable, for the same reason as above.

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Aluna is intended for monitoring FEV1 (Forced exhalation in the first second) and PEF (Peak Expired Flow Rate) for home use. The device is designed for children 5 years of age or older, adolescent and adult subjects. Additionally, the device may be used by clinicians for in-office monitoring.

Aluna is a small hand-held peak flow meter that captures lung health information and makes it available through a mobile application. Aluna is intended for monitoring FEV1 (Forced Expiratory Volume in one second) and PEF (Peak Expiratory Flow) for over-the-counter use. Aluna is designed for use by pediatric to adult users. Aluna is not recommended for children under 5 years of age. Additionally, the device may be used by clinicians for in-office monitoring.

Here's an analysis of the provided text to extract the acceptance criteria and study information for the Aluna device:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document states that the technological differences (rechargeable battery, cloud data storage, game function) "have undergone testing to ensure the device is as safe and effective as the predicate" and that "non-clinical performance bench testing including FEV1/PEF measurement accuracy and repeatability per 2005 American Thoracic Society document ATS/ERS Task Force: Standardization of Lung Function Testing" was performed. While the specific numerical performance results are not explicitly listed in a separate "reported performance" column, the conclusion section states that "performance characteristics for the proposed Aluna are assessed to be substantially equivalent to the predicate device," implying that the device met these stated accuracy criteria.

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

The provided FDA 510(k) summary does not specify the sample sizes used for the FEV1/PEF measurement accuracy and repeatability testing. It only mentions that these tests were performed as "non-clinical performance bench testing."

Regarding data provenance, the document does not explicitly state the country of origin or if the data was retrospective or prospective. Given it's a bench test, the data would be generated in a controlled laboratory environment.

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

The document does not mention the use of experts to establish ground truth for the test set. For FEV1/PEF accuracy testing, the "ground truth" is typically established by comparing the device's readings against a highly accurate standard spirometer calibrated to known volumes and flows, or established physical simulators that produce precise airflow patterns. This is a technical measurement, not an expert interpretive judgment.

4. Adjudication Method for the Test Set

Not applicable. The accuracy testing described is a technical comparison against a standard, not an interpretive task requiring expert adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. The Aluna device is a peak-flow meter, which measures physiological parameters. Its effectiveness is assessed through accuracy and repeatability against established standards, not through human reader interpretation of images or data. Therefore, a study comparing human readers with and without AI assistance is not relevant to this type of device.

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

Yes, a standalone performance assessment was done. The FEV1/PEF measurement accuracy and repeatability testing assesses the algorithm's ability to accurately measure lung function parameters by itself, without human intervention in the measurement process (though a human operates the device).

7. The Type of Ground Truth Used

For the FEV1/PEV measurement accuracy and repeatability testing, the ground truth would be established by:

• Highly accurate standard spirometry equipment or flow/volume simulators: These devices are precisely calibrated and serve as the reference standard against which the Aluna device's measurements are compared. The "2005 American Thoracic Society document ATS/ERS Task Force: Standardization of Lung Function Testing" explicitly details the methods and standards for this type of testing, which involves comparing the device's output to known, accurate flow and volume signals.

8. The Sample Size for the Training Set

The document does not provide information on a "training set" sample size. The Aluna is a medical device for measuring physical parameters, not an AI model that learns from a dataset in the traditional sense (e.g., machine learning for image classification). While there might be internal algorithms for signal processing or data analysis within the device, the summary does not detail the development or validation of such algorithms using a distinct training set. The emphasis is on the device's performance against established physical measurement standards.

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

Not applicable, as a traditional "training set" and associated ground truth establishment (as seen in AI/ML contexts) are not described for this device in the provided document. The device's performance is validated through specific bench testing against established physical and physiological measurement standards.

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