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NuvoAir Air Next is intended to test lung function and spirometry in adults and children 5 years of age and older.

It can be used in hospitals, in the clinical setting, and at home.

The Air Next is not intended for use in an operating room.

The user is not intended to interpret or take clinical action based on the device output without consultation of a qualified healthcare professional.

Air Next is intended to perform basic lung function and spirometry testing. It measures parameters such as the forced expiratory volume in 1 sec (FEV1) and the forced vital capacity (FVC) in a forced expiratory maneuver. These measures can be used for detection, assessment and monitoring of diseases affecting the lung function, such as bronchial Asthma, COPD and Cystic Fibrosis.

Air Next is a hand-held spirometer, weighing 75g and it is powered by 2 AAA alkaline 1.5V batteries. It consists of 3 main components: the Air Next device, the NuvoAir disposable turbine (delivered in one package) and the Air Next mobile application downloadable from Apple's and Google's Play Stores.

The provided text describes the 510(k) premarket notification for the "Air Next" diagnostic spirometer. While it extensively details the device's characteristics, comparison to a predicate device, and compliance with various standards (electrical safety, EMC, usability, biocompatibility), it does not contain a specific section detailing acceptance criteria for performance, nor a study report proving the device meets these criteria with quantitative results from a test set.

The document states that the device "Meets ATS accuracy requirements" and "Air Next complies with the currently recognized safety and EMC standards," but it does not provide the measured performance data or the specific acceptance criteria in a quantifiable table as requested.

However, based on the information provided, we can infer some criteria and the general approach:

Inferred Acceptance Criteria based on Comparison to Predicate and Standards:

The document repeatedly references compliance with ISO 26782:2009 for spirometers and the Standardization of Spirometry 2019 Update (ATS/ERS guidelines). These standards and guidelines define accuracy requirements for spirometry parameters.

From the "SUMMARY OF TECHNOLOGICAL CHARACTERISTICS AND COMPARISON TO PREDICATE DEVICE" table, we can infer the acceptance criteria are likely to match or exceed the predicate device's performance and meet the relevant standards for the following parameters:

• Volume accuracy: ±3% of reading or ±0.050 L, whichever is greater
• Flow accuracy: ±5% or 200 mL/s (likely for PEF)
• Flow resistance: <0.5 cmH2O/L/s
• Volume range: Up to 10 L
• Flow range: 0-15L/s (for Air Next, predicate 0-16 L/s)

Regarding the Study Proving Device Meets Acceptance Criteria:

The document mentions that the device "Meets ATS accuracy requirements" and "Air Next complies with the currently recognized safety and EMC standards." This implies that testing was performed against these standards. However, the specific details of the performance study (methodology, results, sample size of test set, ground truth derivation, expert involvement, etc.) are not explicitly provided in the given text.

Therefore, many parts of your request cannot be answered from the provided document.

Here's a breakdown of what can be extracted or inferred, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

Missing: Specific quantitative results (e.g., actual measured accuracy values, standard deviations, confidence intervals) from a dedicated performance study. The table above only re-states the specifications it claims to meet.

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

• Sample Size: Not specified in the provided text.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The testing would likely be bench testing against calibrated flow/volume simulators rather than human subject data for primary accuracy claims, but specifics are missing.

3. Number of Experts and Qualifications for Ground Truth:

• Not Applicable / Not Specified: For spirometers, primary accuracy testing is typically done using mechanical test lungs and known volume/flow outputs, calibrated against highly accurate reference devices, rather than human experts establishing "ground truth" for each measurement in a test set. This type of device does not involve expert interpretation of images or signals in the same way an AI-powered diagnostic device would.

4. Adjudication Method for the Test Set:

• Not Applicable / Not Specified: Adjudication is typically for subjective expert evaluations (e.g., image review), which does not directly apply to the objective, quantitative measurements of a spirometer's mechanical accuracy.

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

• No: The document does not describe an MRMC study. This type of study is more common for diagnostic AI systems where human reader performance is a key variable. The Air Next is a measurement device.

6. Standalone Performance (Algorithm Only without Human-in-the-Loop):

• Yes, implied for Device Accuracy: The core performance measurements (volume, flow accuracy) are inherent to the device and its algorithms, independent of human interaction beyond operating it. The device itself (Air Next) calculates the spirometry parameters (FEV1, FVC, etc.) based on the turbine's readings. The stated compliance with ISO 26782 implies standalone algorithmic performance testing.
• Missing: Details of this standalone performance test.

7. Type of Ground Truth Used:

• Inferred: Reference Standards/Calibrated Outputs: For spirometers, the ground truth is established by using highly accurate, calibrated flow and volume generators (e.g., syringes or flow controllers) that produce known, precise airflows and volumes. These are the gold standard for verifying spirometer accuracy according to ISO 26782 and ATS/ERS guidelines.
• Not: Expert consensus, pathology, or outcomes data, as these are not relevant to the primary function of a spirometer.

8. Sample Size for the Training Set:

• Not Applicable / Not Specified: This device measures physical parameters (airflow, volume) using a turbine and a digital infrared interruption sensor, not a machine learning model that requires a "training set" of data in the common sense. Its "algorithm" is a conversion from rotations to airflow. If there is any internal calibration or minor adjustment based on manufacturing tolerances, it would be done during production, not through a "training set" in the AI/ML context.

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

• Not Applicable / Not Specified: As explained above, there's no "training set" in the typical AI/ML sense for this device. The physical principle of operation and conversion algorithms are based on established physics and engineering, and then verified against calibrated standards.

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