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The SmartVest® Airway Clearance System, Model Clearway is designed to deliver high frequency chest wall oscillation to promote airway clearance and improve bronchial drainage. The SmartVest® System is indicated when external chest manipulation is the physician's treatment of choice to enhance mucus transport.

The modified Electromed SmartVest® Airway Clearance System, Model Clearway is an electrically powered percussor device designed to deliver high frequency chest wall oscillation (HFCWO) to aid in freeing mucus deposits in the lungs to improve bronchial drainage and airway clearance under the order of a physician's prescription. The primary components of both the proposed modified and predicate HFCWO Airway Clearance Systems consist of an Air Pulse Generator, an Inflatable Vest, and an Air Hose that connects the Generator to the Inflatable Vest. The Air Pulse Generator produces small volumes of pressurized air pulses that are rapidly delivered to the Inflatable Vest via the Air Hose at a selected oscillatory frequency between 5-20 times per minute (Hz). The Inflatable Vest imparts the oscillatory air pulses to the patient's external chest wall. These pressurized air pulses promote transient increases in airflow within the lungs that loosens mucus sufficiently to facilitate expulsion by the patient when normal respiratory function is not capable.

The provided text is a 510(k) summary for the Electromed SmartVest® Airway Clearance System, Model Clearway. It describes modifications made to a previously cleared device, focusing on changes to the Air Pulse Generator. The primary objective was to reduce size and weight, update the graphic user interface (GUI) to a touchscreen, and refine certain features. The document highlights the testing performed to demonstrate substantial equivalence to the predicate device.

Based on the provided text, the device is the Electromed SmartVest® Airway Clearance System, Model Clearway, which is intended to deliver high-frequency chest wall oscillation for airway clearance and bronchial drainage.

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

Key Takeaway from the Document:
This document is a Special 510(k) Summary, indicating that the manufacturer is demonstrating substantial equivalence of a modified device to a previously cleared predicate device, rather than bringing a completely novel device to market. As such, the performance data presented is primarily focused on demonstrating that the changes do not adversely affect safety or effectiveness, and that the modified device performs comparably to the predicate. This is not a clinical trial designed to establish standalone effectiveness against a control or to show human reader improvement with AI assistance.

Details Regarding Acceptance Criteria and Study:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes performance testing, but it does not provide a specific table with numerical acceptance criteria and a direct comparison to reported device performance in a quantitative, side-by-side format. Instead, it states the type of testing and the statistical method used to demonstrate equivalence.

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

• Sample Size for Comparative Performance Testing: The text states, "Testing was conducted on both the predicate and proposed Generators using multiple Inflatable Vests that included the smallest and the largest sizes using the full range of Generator settings for pressure and frequency." A specific numerical sample size is not provided.
• Data Provenance: The document does not specify the country of origin of the data. Given it's a US FDA submission, it's highly implied the testing was conducted under US regulatory and quality system standards. The testing appears to be prospective as it's part of the design verification and validation for a modified product being submitted for clearance.

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

• This information is not applicable in the context of this 510(k) summary. The testing described is primarily engineering and performance verification of a medical device, not a diagnostic or AI-driven system requiring expert ground truth for interpretation (e.g., radiologists for medical images). The "ground truth" for the performance tests would be the measurement standards themselves (e.g., calibrated sensors for pressure, frequency, time).

4. Adjudication Method for the Test Set:

• Not applicable. This isn't a study involving human interpretation where adjudication is needed. (See point 3).

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:

• No, an MRMC study was not done. This device is an airway clearance system, not an AI diagnostic tool. The "performance" described is the physical output of the device (air pulse pressure, frequency, time), not the diagnostic accuracy of an algorithm or its impact on human readers.

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

• Not Applicable. This is not an algorithm-only device. It is a physical medical device. The "performance" assessment is of the device's physical output and functional safety. The software component mentioned is for control of the device, not for diagnostic interpretation.

7. The Type of Ground Truth Used:

• For the comparative output performance testing: The ground truth is established by physical measurements against calibrated standards, with the predicate device's performance serving as the reference for equivalence.
• For electrical safety, EMC, and shipping testing: The ground truth is adherence to the specified international and industry standards (e.g., IEC 60601 series, ASTM D4169).

8. The Sample Size for the Training Set:

• Not applicable. This document describes the clearance of a physical medical device, not an AI model that requires a "training set" in the machine learning sense. The "design input requirements" mentioned in the context of software testing refer to functional specifications, not data for training an algorithm.

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

• Not applicable. (See point 8).

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