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The intended use of the AESOP System is a robotic computer driven system whose function is to hold and position a laparoscope. It is indicated for use in all forms of laparoscopic surgery. A few examples are cholecystecomy, laparoscopic hemia repair, and laparoscopic appendectomy.

The AESOP System is a robotic computer-driven system whose basic function is to hold and position a laparoscope under the direct control of a surgeon.

This 510(k) summary for the AESOP System primarily describes the device's intended use, its substantial equivalence to a predicate device, and the standards it meets. It does not contain specific acceptance criteria related to device performance in a clinical or image-based diagnostic setting, nor does it detail a study proving the device meets particular performance metrics.

The document focuses on:

• Safety and regulatory compliance: Referencing IEC, UL, AMMI, CSA, and EMC standards.
• Functional equivalence: Stating the new AESOP System uses the same control methods as the original, with the addition of voice control.

Therefore, many of the requested sections regarding performance acceptance criteria and a study proving their achievement cannot be answered from the provided text.

Here's what can be extracted and what cannot:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Not provided: The document does not describe a "test set" in the context of clinical performance data, imaging data, or diagnostic accuracy. The testing mentioned refers to engineering and safety standards compliance.

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

• Not applicable / Not provided: No ground truth establishment for a test set (in a clinical/diagnostic sense) is described.

4. Adjudication method for the test set

• Not applicable / Not provided: No test set (in a clinical/diagnostic sense) or adjudication method 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

• No: This document describes a robotic surgical assistant, not an AI-powered diagnostic tool for human readers. No MRMC study is mentioned.

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

• Not directly applicable / Not provided: The device is a surgical assistant whose function is to hold and position a laparoscope under the direct control of a surgeon. The voice control is an interface for the surgeon, not an autonomous diagnostic algorithm. Its performance is intrinsically human-in-the-loop.

7. The type of ground truth used

• Not applicable / Not provided: No clinical or diagnostic "ground truth" is discussed. The "ground truth" for this device's performance would relate to its mechanical accuracy, response time, and safety as determined by engineering tests and adherence to standards.

8. The sample size for the training set

• Not provided: The document refers to a "speaker dependent speech recognition system" for voice control, which implies a training phase for individual users. However, no details on the sample size or nature of this training (e.g., number of voice commands, speakers) are given. It's likely a relatively small, user-specific training.

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

• Not provided: For the voice control system, the "ground truth" for training would typically be the correct command corresponding to a spoken word. The document states it's "speaker dependent," meaning it's trained to an individual's voice. The method of establishing this training ground truth (e.g., repeating commands, verifying recognition) is not detailed.

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