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The Bio Compression Systems' Sequential, pneumatic compression devices intended for either primary or adjunctive treatment of lymphedema, peripheral edema, venous insufficiency, and venous stasis ulcers. Sequential Circulators are also intended for the prophylaxis of deep vein thrombosis (DVT). Intended for use in a home or healthcare setting.

Bio Compression Systems' Sequential Circulators are sequential pneumatic compression device which consists of a segmented pneumatic compression sleeve ("qarment") connected to a pneumatic compression pump ("pump"). The pump cyclically inflates the garment's segments ("chambers") in sequence from the distal end toward the trunk of the body. The inflation of the garment compresses the limb on which it is worn, stimulating the movement of interstitial fluid and blood flow.

The core components of the pump are the motor, air compressor, disc valves, and micro switch. The air compressor generates air flow into a stationary disc valve. The motor moves a rotating disc valve. The geometry of the disc valve directs air flow and cyclically triggers the micro switch.

The pump is controlled by softkeys and an LED display (models SC-1004-DL, SC-1008-DL, SC-2004-DL, SC-2008-DL) or by a touch screen LCD (models SC-4004-DL, SC-4008-DL).

The device uses the Predicate Device's garments.

The provided document is a 510(k) premarket notification for a medical device (Sequential Circulators) and does not describe a study that establishes acceptance criteria for a device based on expert performance or to prove a device meets acceptance criteria through a comparison with human readers or a standalone algorithm study.

Instead, this document focuses on demonstrating substantial equivalence to a previously cleared predicate device, as required for 510(k) submissions to the FDA. The "acceptance criteria" discussed are primarily related to general performance, electrical safety, electromagnetic compatibility, and software verification/validation, rather than clinical performance based on ground truth established by experts.

Therefore, many of the requested points related to acceptance criteria and performance studies in the context of AI/ML or expert adjudication in a clinical setting cannot be directly extracted from this document.

However, I can provide the information that is present:

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

The document doesn't present "acceptance criteria" in a typical table format with quantitative performance metrics for a diagnostic or AI device (e.g., sensitivity, specificity). Instead, it lists various tests and validations performed to ensure the device performs as intended and is safe. The "reported device performance" is implied by the satisfactory completion of these tests, leading to the substantial equivalence determination.

Here's an interpretation based on the document's content:

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

The document does not specify sample sizes in terms of a "test set" for clinical evaluation in the way an AI/ML device submission would. The testing described (electrical safety, functional verification, comparative pressure) refers to engineering and bench testing of the devices themselves, not a dataset of patient cases.

• Sample Size: Not applicable in the context of clinical "test sets" for diagnostic performance. The sample size would refer to the number of device units tested.
• Data Provenance: Not applicable. The testing is described as being conducted on the subject device and reference devices, not on patient data.

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

This information is not applicable to this 510(k) submission. The device is a pneumatic compression device, not a diagnostic imaging device or an AI/ML algorithm requiring expert ground truth for clinical performance evaluation. The "ground truth" for this device's performance is its direct physical output (e.g., pressure, cycle time) verified through engineering tests against specifications.

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

Not applicable. There is no expert adjudication mentioned as this is not a diagnostic or AI/ML device relying on interpretation 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 is not an AI-assisted device, and no MRMC study was conducted.

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

Not applicable. This is not an AI algorithm.

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

For this device, the "ground truth" used for testing would be the engineering specifications and established standards for medical devices (e.g., pressure accuracy, cycle time, electrical safety parameters). It is not clinical ground truth derived from expert consensus, pathology, or outcomes data.

8. The sample size for the training set

Not applicable. This device does not involve training of an AI/ML model.

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

Not applicable. No training set for an AI/ML model.

Summary of the Study Proving Device Meets Acceptance Criteria (as described in the 510(k)):

The study to prove the device meets its "acceptance criteria" (understood here as performance specifications and safety standards) consisted of a series of bench testing, engineering verification, and validation activities. These included:

• Electrical Safety and Electromagnetic Compatibility (EMC) Testing: Adherence to recognized national and international standards (e.g., ANSI/AAMI ES60601-1, IEC 60601-1-2, etc.).
• Predicate Device Routine Acceptance Tests Conducted on Subject Device: This implies the new device underwent the same internal quality control and performance tests as the predicate, including continuous and timed operation observation, pressure testing, and HiPot testing.
• Functional Verification and Validation Testing: Specific tests were conducted to verify and validate cycle time, treatment time, pressure setting endpoints, and overall functionality of all modes and settings.
• Comparative Pressure Testing: Specific tests were done to compare the pressure performance of the Subject Device and Predicate Device, particularly regarding individual chamber adjustment and pressure gradients. This was crucial for demonstrating substantial equivalence for critical performance parameters.
• Software Verification and Validation Testing: Conducted in accordance with FDA guidance for medical device software, confirming its functionality and safety (classified as "minor" level of concern).

The conclusion states: "The data included in this submission demonstrates that the Subject Device is substantially equivalent to the legally marketed Predicate Device and performs comparably to the Predicate Device that is currently marketed for the same intended use." This statement serves as the justification that the device meets the implied "acceptance criteria" for demonstrating substantial equivalence.

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