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The Mini-Wright Digital is a handheld, battery operated, electronic Peak Flow Meter and FEV1 monitoring device with an internal memory capable of storing 240 sets of readings. This product will be sold as an OTC device with appropriate instructions. When used to monitor conditions such as asthma, this device should be used under the direction of a physician or licensed health care professional. The device is intended for use with paediatric and adult patients in both home and clinical settings.

The Mini-Wright Digital is a handheld, battery operated, electronic Peak Flow Meter and FEV I monitoring device with an internal memory capable of storing 240 sets of readings. This product will be sold as an OTC device with appropriate instructions.

The provided text describes the 510(k) summary for the Mini-Wright Digital, a Peak Flow/FEV1 Meter. It outlines its indications for use, technological differences from a predicate device, and performance data.

Here's an analysis of the acceptance criteria and study information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a distinct "test set" sample size in terms of number of patients or individual measurements. Instead, it mentions "Non-clinical performance data has been compiled by testing the Mini-Wright Digital in accordance with the methods described in the American Thoracic Society's document 'Standardization of Spirometery' 1994 update." This implies laboratory or bench testing rather than a clinical study with human subjects.

The data provenance is not explicitly stated as retrospective or prospective human data, given it's non-clinical performance data. It is implied to be laboratory-generated. The applicant is Clement Clarke Int. Ltd from the United Kingdom, so the testing was likely conducted there.

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

This information is not provided in the document. The testing appears to be based on a recognized technical standard (American Thoracic Society's "Standardization of Spirometery" 1994 update), which would define objective performance metrics rather than relying on expert consensus for ground truth.

4. Adjudication Method for the Test Set

This information is not applicable/not provided. As the testing was non-clinical and based on objective standards, there wouldn't be a need for an adjudication method among experts.

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

There is no mention of a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. The device is a standalone peak flow/FEV1 meter, not an AI-assisted diagnostic tool for human readers.

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

Yes, this was a standalone performance study in the sense that the device's accuracy and repeatability were tested as a unit. While it's an electronic device, the term "algorithm only" in the context of AI isn't directly applicable here, as it's a measurement device, not an AI diagnostic algorithm. Its performance was evaluated on its own based on established spirometry standards.

7. The Type of Ground Truth Used

The ground truth for the performance reported was based on technical standards and established recommendations for monitoring devices, specifically the "American Thoracic Society's document 'Standardization of Spirometery' 1994 update." This implies a comparison to a gold standard of measurement defined by the ATS guidelines.

8. The Sample Size for the Training Set

This information is not applicable/not provided. The device is an electronic measurement instrument, not an AI system that undergoes "training" in the typical machine learning sense. Its design and calibration would be based on engineering principles and conformity to standards rather than a training dataset.

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

This information is not applicable/not provided for the reasons stated in point 8.

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