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The ARTAIRA Arterial Compression Device's is an intermittent pneumatic compression device intended for treatment of patients with the following conditions:

• · Intermittent claudication
• · Rest pain
• Diabetic Foot
• · Ischemic neuritis
• · Arterial ulcers
• · Gangrene
• Poor runoff.

The AIROS ARTAIRA Arterial Compression Device is an intermittent pneumatic compression device intended to increase blood flow and increase circulation in the lower extremities by providing timed compression to the foot/ankle and calf. The device consists of a hard casing with an air pump, a set of air valves, an air reservoir controlled by the device software to deliver a rapid burst of pneumatic pressure to the treatment area. The device connects through air tubing to a pair of compression garments (left and right leg), each with two air chambers: one on the underfoot (Foot/Ankle chamber) and one on the calf area (Calf Chamber). The device can either be used with one garment or two garments. The system is intended to be used primarily at home settings according to a physician-prescribed therapy.

The provided document is a 510(k) Premarket Notification from the FDA for a medical device called the ARTAIRA Arterial Compression Device. This document does not contain information about the acceptance criteria and study proving device performance as typically understood for AI/ML-driven medical devices.

The listed device, the "ARTAIRA Arterial Compression Device (AACD01)", is an intermittent pneumatic compression device. The document primarily focuses on demonstrating substantial equivalence to a predicate device (ArtAssist Device) based on technological characteristics, functional performance testing of the device hardware (e.g., pressure accuracy, timing accuracy, integrity testing), and adherence to various medical device standards (e.g., ISO, IEC).

There is no mention of an AI/ML component in the device description or the testing conducted. Therefore, the specific questions regarding acceptance criteria for AI/ML performance, sample sizes for test/training sets, expert ground truth establishment, MRMC studies, or standalone algorithm performance are not applicable to the information provided in this FDA clearance letter.

The functional performance testing described in the document (User Interface & Error Indicator Testing, Noise Testing, Compression Sequence Timing Accuracy Testing, Pressure Accuracy Testing, Therapy Time Accuracy Testing, Garment Integrity Testing, Air Leakage Testing) relates to the mechanical and software control aspects of a traditional medical device, not an AI/ML algorithm's diagnostic or predictive capabilities.

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The AIROS 6P Sequential Compression Device utilizes gradient pneumatic compression, which is intended for treatment of patients with the following conditions:

• Lymphedema
• Venous stasis ulcers
• Venous insufficiency
• Peripheral edema
  The device is safe for both home and hospital use.

AIROS 6P Sequential Compression Device is a pneumatic compression device used for treatment and management of venous or lymphatic disorders. The application of compression is effective by increasing blood flow and encouraging extracellular fluid clearance. The device consists of the mechanical device that is used to set the treatment options and supplies cycles of air to the compression garments. There are two primary treatment modes, Gradient Mode and Peristaltic Mode. The air is supplied at adjustable pressures and sequences and inflates the compression garments from the distal to proximal areas of the body. The compression garments are supplied in various sizes for the upper and lower extremity areas of the body.

The AIROS 6P Sequential Compression Device is a pneumatic compression device used for the treatment and management of venous or lymphatic disorders. The study provided in the 510(k) summary focuses on functional performance testing to demonstrate substantial equivalence to predicate devices, rather than a clinical study involving human patients or complex AI algorithms requiring expert adjudication of ground truth.

Here's an breakdown of the information requested, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list "acceptance criteria" with numerical targets and "reported device performance" in a comparative table for specific clinical outcomes. Instead, it lists functional performance tests conducted to ensure the device meets its specifications and is substantially equivalent to predicate devices.

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

The document does not mention a "test set" in the context of patient data or clinical outcomes. The testing described is functional performance testing of the device itself. Therefore, concepts like sample size of patients, data provenance (country of origin), or retrospective/prospective data collection are not applicable to the tests reported.

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

There is no mention of experts being used to establish a "ground truth" for a test set in the provided text. The testing described is engineering/functional testing.

4. Adjudication Method for the Test Set

Not applicable, as no test set requiring adjudication by experts is described.

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

Not applicable. The AIROS 6P is a pneumatic compression device, not an AI-assisted diagnostic or therapeutic tool that would involve "human readers" or "AI assistance" in the sense of image interpretation or similar cognitive tasks.

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

Not applicable. The AIROS 6P is a physical medical device, not a standalone algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The "ground truth" for the functional performance testing would be the device's design specifications and established engineering standards. For example, "cycle time accuracy" would be compared against the designed cycle times. There is no biological or clinical "ground truth" like pathology or outcomes data involved in the described testing.

8. The Sample Size for the Training Set

Not applicable. The AIROS 6P is not a machine learning or AI device that requires a training set.

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

Not applicable, as there is no training set for this device.

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The AIROS 8P Sequential Compression Device utilizes gradient pneumatic compression, which is intended for treatment of patients with the following conditions:

• Lymphedema
• Venous stasis ulcers
• Venous insufficiency
• Peripheral edema

The device is safe for both home and hospital use.

AIROS 8P Sequential Compression Device is a pneumatic compression device used for treatment and management of venous or lymphatic disorders. The application of compression is effective by increasing blood flow and encouraging extracellular fluid clearance. The device consists of the mechanical device that is used to set the treatment options and supplies cycles of air to the compression garments. There are three primary treatment modes, Gradient Mode, Pressure Mode, and Peristaltic Mode. The air is supplied at adjustable pressures and sequences and inflates the compression garments from the distal to proximal areas of the body. The compression garments are supplied in various sizes for the upper and lower extremity areas of the body.

The provided text is a 510(k) premarket notification for the AIROS 8P Sequential Compression Device. This document focuses on demonstrating substantial equivalence to existing predicate devices, rather than proving that a device meets specific performance acceptance criteria for a novel AI/ML algorithm.

Therefore, the requested information regarding acceptance criteria for an AI/ML device, its performance, sample sizes for test and training sets, expert adjudication, MRMC studies, standalone performance, and ground truth establishment cannot be found in this document.

This document describes a medical device (a pneumatic compression device) and its functional performance testing (e.g., Error Indicator Testing, Noise Testing, Cycle Time Accuracy, Pressure Time Accuracy, Therapeutic Performance, Therapy Time Accuracy, Garment Integrity). These tests ensure the hardware and software functionality, and compliance with electrical and safety standards, but do not involve an AI/ML algorithm that requires a dedicated clinical or imaging study with a ground truth established by experts.

Here's why the specific questions cannot be answered from the provided text:

• No AI/ML Component: The AIROS 8P Sequential Compression Device is a physical medical device that applies pneumatic compression. The "AIROS" in the name refers to the company, not Artificial Intelligence. The description of the device's operation ("digitally controlled device consists of an electrically generated source of compressed air, tubing to convey the pressurized air to the sleeve") confirms it's a mechanical device with digital controls, not an AI/ML algorithm that interprets data or images.
• Substantial Equivalence Focus: The entire premise of this 510(k) submission is to demonstrate that the AIROS 8P is "substantially equivalent" to already legally marketed predicate devices (AIROS 8 Sequential Compression Device and Mego Afek Lympha Press Optimal). This type of submission does not typically involve clinical trials or performance studies that would establish acceptance criteria for a novel AI/ML algorithm's accuracy, sensitivity, or specificity.
• Functional Performance Testing: The "Functional Performance Testing" listed (Error Indicator Testing, Noise Testing, Cycle Time Accuracy, etc.) pertains to the engineering and operational parameters of the physical device, not an AI algorithm's diagnostic or predictive performance.

In summary, the provided document does not contain information about acceptance criteria or a study for an AI/ML device because the AIROS 8P Sequential Compression Device is not described as an AI/ML device.

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The AIROS 6 Sequential Compression Device utilizes gradient pneumatic compression, which is intended for treatment of patients with the following conditions:

• Lymphedema
• Venous stasis ulcers
• Venous insufficiency
• Peripheral edema

The device is safe for both home and hospital use.

The AIROS 6 Sequential Compression Device is a gradient pneumatic compression device. The device is used for treatment and management of venous or lymphatic disorders. The application of gradient sequential compression increases blood flow and encourages extracellular fluid clearance.

The AIROS 6 system consists of the device and 6-chambered garments. The device provides cycles of compressed air and sequentially inflates the garments from distal to proximal.

The provided FDA 510(k) summary for the AIROS 6 Sequential Compression Device does not include a study proving device performance against detailed acceptance criteria in the manner typically seen for AI/ML-based diagnostic devices. This document is for a Class II medical device (compressible limb sleeve), which is a mechanical device, not an AI or imaging diagnostic tool. Therefore, the questions related to AI/ML specific aspects (such as AI assistance, human-in-the-loop, training/test set details, expert ground truth, effect size, etc.) are not applicable to this submission.

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (AIROS 6 Sequential Compression Device K172770 from the same manufacturer) through functional performance testing and adherence to relevant standards.

Here's an analysis based on the provided text, primarily addressing the "functional performance testing" section:

1. Table of Acceptance Criteria and Reported Device Performance

The document lists "functional performance testing" categories but does not provide specific numerical acceptance criteria or detailed reported performance values. It states: "Testing was performed and to ensure that the system meets its specifications." This implies that the device did meet its internal specifications, but these specs are not detailed in the public 510(k) summary.

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

This is not applicable as the testing involves the physical device and garments, not a dataset in the context of AI/ML. The "test set" would be the manufactured devices and accompanying garments. The provenance would be the manufacturing site of AIROS Medical, Inc.

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

This is not applicable. "Ground truth" in this context refers to the device's functional specifications, which are established by the manufacturer through engineering design and regulatory requirements, not by external experts adjudicating data.

4. Adjudication Method for the Test Set

Not applicable. The testing appears to be functional and engineering validation, not consensus-based adjudication of interpretations of clinical data.

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

Not applicable. This device is a mechanical sequential compression device, not an AI-assisted diagnostic tool.

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

Not applicable. There is no AI algorithm in this device.

7. The Type of Ground Truth Used

The ground truth is the device's design specifications and functional requirements as established by the manufacturer and validated through engineering tests.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device.

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

Not applicable. This is not an AI/ML device.

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The AIROS 8 Sequential Compression Device utilizes gradient pneumatic compression, which is intended for treatment of patients with the following conditions:

• Lymphedema
• Venous stasis ulcers
• Venous insufficiency
• Peripheral edema

The device is safe for both home and hospital use.

The AIROS 8 Sequential Compression Device is a gradient pneumatic compression device. The device is used for treatment and management of venous or lymphatic disorders. The application of gradient sequential compression increases blood flow and encourages extracellular fluid clearance.

The AIROS 8 system consists of the device and 8-chambered garments. The device provides cycles of compressed air and sequentially inflates the garments from distal to proximal.

The digitally-controlled device consists of an electrically generated source of compressed air, tubing to convey the pressurized air to the sleeve, and like the predicate, pressure is applied cyclically for a specified period of time, according to the physician's prescription.

The provided text is a 510(k) Premarket Notification from AIROS Medical, Inc. for their AIROS 8 Sequential Compression Device. This document primarily focuses on establishing substantial equivalence to a predicate device (also the AIROS 8, K172779) and discusses the device's indications for use, technological characteristics, and conformity to certain standards.

The document does not describe:

• Acceptance criteria for a specific performance metric of an AI/ML algorithm.
• A study proving the device meets such acceptance criteria.
• Sample sizes for test sets or training sets in the context of AI/ML.
• Data provenance, expert involvement for ground truth, or adjudication methods.
• MRMC comparative effectiveness studies or standalone AI performance.
• Specific types of ground truth used (e.g., pathology, outcomes data).

Instead, the document details "Functional Performance Testing" which includes items like Alarm Testing, LED/LCD Testing, Cycle Time Testing, Pressure Accuracy Testing, etc. These are tests typical for a physical medical device (a sequential compression device), confirming its mechanical and electrical specifications, not the performance of an AI/ML algorithm.

Therefore, I cannot fulfill the request as the provided text does not contain information related to AI/ML acceptance criteria or the study that proves an AI/ML device meets those criteria. The AIROS 8 Sequential Compression Device is a hardware device, not an AI/ML powered one, based on the provided document.

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The AIROS 6 Sequential Compression Device utilizes gradient pneumatic compression, which is intended for treatment of patients with the following conditions:

• · Lymphedema
• Venous stasis ulcers
• · Venous insufficiency
• · Peripheral edema

The device is safe for both home and hospital use.

The AIROS 6 Sequential Compression Device is a gradient pneumatic compression device. The device is used for treatment and management of venous or lymphatic disorders. The application of gradient sequential compression increases blood flow and encourages extracellular fluid clearance.

The AIROS 6 system consists of the device and 6-chambered garments. The device provides cycles of compressed air and sequentially inflates the garments from distal to proximal.

The provided text is a 510(k) summary for the AIROS 6 Sequential Compression Device. This type of FDA submission is for demonstrating substantial equivalence to a predicate device, primarily through performance testing and adherence to standards, rather than clinical efficacy studies often associated with AI/ML-based devices.

Therefore, the document does not contain specific details regarding:

• Acceptance criteria and reported device performance related to a diagnostic or AI/ML-based task. The performance tests listed are functional and safety tests for a pneumatic compression device, not accuracy metrics for a diagnostic algorithm.
• Sample sizes for a test set or data provenance (e.g., country of origin, retrospective/prospective). The testing described is for engineering validation of the physical device.
• Number of experts and their qualifications for ground truth establishment. Ground truth as defined for diagnostic AI/ML models is not applicable here.
• Adjudication method for a test set. Not applicable.
• Multi-Reader Multi-Case (MRMC) comparative effectiveness study. This type of study is for evaluating human performance with and without AI assistance, which is not relevant to this device.
• Standalone (algorithm-only) performance. The device is a physical pneumatic compression system, not an algorithm.
• Type of ground truth used (expert consensus, pathology, outcomes data, etc.). Not applicable.
• Sample size for the training set or how ground truth for the training set was established. This device does not involve machine learning or a "training set" in the context of AI.

Based on the provided text, here is what can be extracted regarding the "acceptance criteria" and "study that proves the device meets the acceptance criteria" in the context of this 510(k) submission:

The "acceptance criteria" in this context are the successful completion of various functional and safety performance tests, and compliance with recognized medical device standards, to demonstrate that the AIROS 6 Sequential Compression Device operates as intended and is safe. The "study" refers to the conducted functional performance testing.

1. A table of acceptance criteria and the reported device performance:

The document lists "Functional Performance Testing" that was performed to "ensure that the system meets its specifications." While the specific numerical acceptance criteria (e.g., "pressure accuracy within +/- X mmHg") are not detailed, the implication is that the device met these criteria for each test.

Notes:

• The phrase "Testing was performed and to ensure that the system meets its specifications" and the conclusion "AIROS Medical, Inc., believes that the AIROS 6 is substantially equivalent to the predicate device" implicitly state that the device met the acceptance criteria for these tests. The specific quantitative results are not in this summary but would be in the more detailed submission.
• Additionally, compliance with the listed consensus standards (IEC 60601-1, ISO 10993, IEC 61000, ANSI/AAMI ES60601-1, CAN/CSA-C22.2 No. 60601-1) also represents a set of acceptance criteria regarding safety and essential performance.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• This information is not provided in the 510(k) summary. These details would typically be found in the full test reports submitted to the FDA, not in the public summary. For functional performance tests, a "sample size" often refers to the number of devices or components tested. Data provenance (country, retrospective/prospective) is not relevant for this type of mechanical device testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• This concept is not applicable to the testing described for this device. Ground truth in the context of diagnostic performance (e.g., image interpretation) is not relevant here. The "ground truth" for these functional tests would be the established engineering specifications and physical measurements.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• This concept is not applicable to the testing described for this device. Adjudication methods are used in diagnostic studies to resolve reader discrepancies.

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. This type of study is for evaluating AI-assisted diagnostic performance, which is not relevant to this pneumatic compression device.

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

• No. This device is a physical medical device, not an algorithm, so a "standalone" algorithmic performance evaluation is not applicable.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• This concept is not applicable in the context of this device's functional and safety testing. The "ground truth" for the performance characteristics (e.g., pressure output, cycle time) is based on engineering specifications and direct physical measurement calibrated against known standards.

8. The sample size for the training set:

• Not applicable. This device does not involve machine learning or a "training set."

9. How the ground truth for the training set was established:

• Not applicable. As there is no training set, there is no ground truth to establish for it in this context.

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The AIROS 8 Sequential Compression Device utilizes gradient pneumatic compression, which is intended for treatment of patients with the following conditions:

• · Lymphedema
• Venous stasis ulcers
• · Venous insufficiency
• · Peripheral edema
  The device is safe for both home and hospital use,

The AIROS 8 Sequential Compression Device is a gradient pneumatic compression device. The device is used for treatment and management of venous or lymphatic disorders. The application of gradient sequential compression increases blood flow and encourages extracellular fluid clearance.
The AIROS 8 system consists of the device and 8-chambered garments. The device provides cycles of compressed air at certain adjustable pressures, and sequentially inflates the garments from distal to proximal. The pressure at each chamber can be individually adjusted to accommodate different therapy needs.

Here's an analysis of the provided text regarding the AIROS 8 Sequential Compression Device, focusing on acceptance criteria and study data:

Based on the provided 510(k) summary for the AIROS 8 Sequential Compression Device, the document does not contain the detailed information typically found in an AI/ML-based medical device submission regarding acceptance criteria, performance metrics, and study details (like sample size for test/training sets, expert qualifications, ground truth establishment, or clinical outcome studies).

The AIROS 8 device is a physical medical device (a sequential compression device) and its 510(k) submission focuses on demonstrating substantial equivalence to a predicate device (CircuFlow 5208) based on technological characteristics and functional performance testing, rather than AI/ML algorithm performance.

Therefore, I cannot populate the requested table and answer many of the specific questions as they are designed for AI/ML device assessment. The provided text describes a traditional medical device submission.

However, I can extract the acceptance criteria and performance testing described for this type of physical device:

Acceptance Criteria and Reported Device Performance (for a physical medical device)

1. A table of acceptance criteria and the reported device performance

The document does not present quantitative acceptance criteria or specific numerical performance results in a table format. Instead, it states that "Testing was performed and to ensure that the system meets its specifications" and lists the types of functional performance tests conducted. The conclusion is that the device is "substantially equivalent" to the predicate.

Interpretation for a physical device: The acceptance criteria for these tests would likely be "passes" or "meets specification" for each functional test, implying the device performed as intended and comparably to the predicate. Specific numerical targets for pressure accuracy, cycle time, noise, etc., would be in the full submission, but are not in this summary.

Study Details (as inferable for a physical medical device)

The following points are mostly not applicable (N/A) in the context of this 510(k) summary for a physical compression device, as they are typically relevant to AI/ML or diagnostic device studies. The "study" here is primarily functional performance and electrical safety testing.

2. Sample size used for the test set and the data provenance

• Sample Size: Not specified. For functional testing of a physical device, this would typically involve testing a representative sample of manufactured units (e.g., a few devices from a production batch).
• Data Provenance: Not specified, but generally refers to in-house laboratory testing of the manufactured device.
• Retrospective/Prospective: N/A. This is functional testing, not a clinical data collection.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• N/A. Ground truth as understood in AI/ML (e.g., disease presence/absence determined by experts) is not relevant for the functional testing of a pneumatic compression device. Testing relies on engineering specifications and measurement equipment.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• N/A. Adjudication is not applicable for functional engineering tests.

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

• N/A. This device is not an AI/ML diagnostic or assistive tool for human readers.

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

• N/A. This device does not have an AI algorithm. Its "performance" is its mechanical and electrical function.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• N/A. The "ground truth" for the listed functional tests would be engineering specifications, direct measurements, and established quality control protocols for pressure, time, electrical safety, etc.

8. The sample size for the training set

• N/A. This concept is for AI/ML models. No training set is mentioned as this is not an AI/ML device.

9. How the ground truth for the training set was established

• N/A. Not applicable, as there is no training set for an AI/ML model for this device.

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