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The Olympus SEPS System is designed for subcutaneous endoscopy -- more specifically, for endoscopically gaining access to vessels (arteries veins, ducts, nerves) in subcutaneous and subfascial surgical planes in the lower extremities for endoscopic observation, diagnosis, and treatment.

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The provided text describes a 510(k) submission for the Olympus SEPS System but does not contain information about acceptance criteria or a study proving the device meets those criteria.

The document is a 510(k) summary, specifically the FDA's clearance letter and the manufacturer's statement of intended use. It focuses on the regulatory classification and the determination of substantial equivalence to predicate devices, rather than performance or efficacy studies.

Therefore, I cannot provide the requested information based on the given text.

If this were a typical device submission with performance data, the following would be the expected information:

1. Table of Acceptance Criteria and Reported Device Performance: This would typically be a table comparing pre-defined thresholds for performance metrics (e.g., accuracy, sensitivity, specificity for a diagnostic device; or specific functional requirements for a surgical device) against the results achieved in a study.

   • Example for an imaging device:

     Metric	Acceptance Criteria	Reported Performance
     Sensitivity	> 90%	92.5%
     Specificity	> 80%	85.1%
     Accuracy	> 85%	88.0%

2. Sample size used for the test set and the data provenance: This would state how many cases were used to evaluate the device's performance and where that data came from (e.g., 200 patient cases from a multi-center retrospective study in the USA and Europe).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: This would detail the number of clinicians who provided the reference standard for the test data and their relevant experience (e.g., 3 board-certified radiologists, each with 10+ years of experience in thoracic imaging).

4. Adjudication method for the test set: How disagreements among experts were resolved (e.g., 2+1 means two experts agree, or a third expert adjudicates if the first two disagree; 3+1 means three experts agree, or a fourth adjudicates).

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Yes/No, and if yes, the effect size for human readers with/without AI assistance.

6. If a standalone (algorithm only without human-in-the-loop performance) was done: Yes/No, and the results if applicable.

7. The type of ground truth used: What the reference standard was based on (e.g., histopathology, clinical follow-up, consensus of multiple experts, outcome data).

8. The sample size for the training set: How many cases/data points were used to train the algorithm (for AI/ML devices).

9. How the ground truth for the training set was established: Similar to point 7, but specifically for the data used to teach the algorithm.

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