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The Smartinhaler™ is intended for single-patient use in the home environment as a medication reminder and electronic data capture accessory for recording actuations of prescribed MDI usage. This may be used in the following applications: · In clinical trials, where researchers need to know when a patient has actuated their trial MDI medication. · In clinical practice, where specialists, general practitioners, nurses, and educators need to know if a patient has actuated their prescribed MDI medication. · In self-management, where patients need to track their medication use as part of their management plan. The Smartinhaler™ is compatible only with the following MDIs: Ventolin® HFA, Flovent® HFA, ProAir® HFA, and QVAR® HFA. The intended MDI is specified on the product labeling. The Smartinhaler™ is not intended to indicate remaining quantity of medication in an MDI and does not include a dose counting function.

Smartinhaler™ is used to provide a medication reminder and actuation recording function for use as an accessory with a Metered Dose Inhaler (MDI) as part of normal daily use of the MDI. Smartinhaler™ is a clip-on device that attaches externally around the housing of an MDI. The Smartinhaler™ comes in rechargeable and non-rechargeable models. Each Smartinhaler™ is compatible only with one of the following MDIs: Ventolin® HFA (90 mcg), Advair® HFA (45/21, 115/21, 230/21 mcg), Flovent® HFA (44, 110, 220 mcg), ProAir® HFA (90 mcg), QVAR® HFA (40, 80 mcg). The intended MDI is indicated on the device labeling. Optical and pressure sensors are used to detect MDI presence and actuation, and the device logs the usage history of the MDI. The Smartinhaler™ contains an electronic clock and calendar that is used to log the date and time of MDI actuation. The Smartinhaler™ user interface consists of one LED indicator and one control button to check device status, initiate communications functions, and cancel medication reminders. The Smartinhaler™ has a Bluetooth interface to wirelessly exchange medication and reminder setting data with a paired communications device and compatible mobile software applications.

The provided text describes the 510(k) summary for the Smartinhaler™ device. This is a premarket notification for a medical device and typically relies on demonstrating substantial equivalence to a legally marketed predicate device rather than extensive clinical efficacy studies in the same way a new drug would.

Based on the provided text, here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present a formal table of quantitative acceptance criteria for performance with corresponding results for accuracy, sensitivity, or specificity in detecting MDI actuations. Instead, it refers to a broader set of tests to establish functional equivalence and safety.

However, it does state the following objectives and general outcomes:

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

The document explicitly states: "Non-clinical testing of the Smartinhaler™ has been carried out to cover functional verification, device performance, and usability of the user interface. This included completion of software and device verification procedures, with performance testing of the MDI presence and actuation sensor system to ensure data is logged accurately for usage with each of the compatible MDIs."

It also mentions that the testing "established correct functionality and compatibility of the Smartinhaler™ with the Ventolin® HFA, Advair® HFA, Flovent® HFA, ProAir® HFA, QVAR® HFA according to requirements."

However, the document does not provide specific sample sizes (e.g., number of actuations, number of devices, duration of testing) for the non-clinical tests. It generalizes the testing as encompassing "functional verification, device performance, and usability."

Data Provenance: The testing was described as "Non-clinical testing" and conducted by "external laboratories." The specific country of origin for the data or whether it was retrospective or prospective is not detailed, beyond being verification and performance testing. Given it's pre-market, it would inherently be prospective testing for the device's functionality.

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

The document states that the testing was "non-clinical" and describes it as "functional verification, device performance, and usability." This suggests the ground truth for these tests would likely be established by technical specifications, engineering benchmarks, and instrumental measurements, rather than human expert interpretation of medical images or data. Therefore, the concept of "experts" in the context of clinical ground truth (e.g., radiologists) is not applicable here.

4. Adjudication Method for the Test Set

As the testing was non-clinical and focused on device functionality and engineering performance, there's no mention or indication of a human-based adjudication method (like 2+1 or 3+1 consensus) for the test set. The results would be based on instrument readings and meeting defined performance specifications.

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

No. The document explicitly states: "Clinical testing was not required for a determination of substantial equivalence of the Smartinhaler™. The product functionality has been adequately assessed by bench testing as above." Therefore, an MRMC study comparing human readers with and without AI assistance was not conducted. The device is an accessory for recording MDI actuations, not an AI for image interpretation that would typically require an MRMC study for clinical effectiveness.

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

The device itself is a standalone electronic device that records MDI actuations. The "performance testing of the MDI presence and actuation sensor system to ensure data is logged accurately" effectively acts as a standalone performance evaluation of the device's core function. It doesn't rely on human input for its primary function of detection and logging.

7. The Type of Ground Truth Used

The ground truth for the non-clinical tests would have been established through defined engineering specifications, simulated actuation events (e.g., automated MDI actuations), and comparison against known correct values or behaviors. For instance, knowing when an MDI was actuated (based on a test rig or direct observation by engineers) and comparing that to the device's logged data. The document implies that the ground truth was inherent to the bench testing environment.

8. The Sample Size for the Training Set

The concept of a "training set" is typically associated with machine learning or AI models. The Smartinhaler™ is described as using optical and pressure sensors to detect MDI presence and actuation. While there might be internal algorithms for processing sensor data, the document does not suggest a deep learning or complex AI model that would require a large, distinct "training set" in the conventional sense. The "software verification procedures" mentioned would relate to traditional software engineering and testing, not AI model training. Therefore, no specific training set sample size is mentioned or implied.

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

As no "training set" for an AI or machine learning model is indicated, this question is not directly applicable. If there were any internal algorithms that required calibration or parameter tuning, their "ground truth" would likely have been established through controlled bench testing and validation against known physical events (e.g., verified MDI actuations in a laboratory setting).

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