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The Deltronix Precision and SEG are a high frequency electrosurgical generators intended for use with monopolar and bipolar accessories for cutting and coagulating tissue.

The electrosurgical generators of Precision and SEG lines are intended to cut and electrosurgical coagulation of living human tissues. This objective is achieved through the power supply at high frequency. The electrosurgical generator of the Precision line may coagulate by using both monopolar technique and bipolar technique.

This is an electrosurgical generator device, not an AI/ML device. Therefore, the questions related to AI/ML device performance are not applicable.

Here's the relevant information extracted from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics and performance, rather than defining explicit acceptance criteria or presenting a standalone performance study with specific metrics. The "Performance" section in Table 5.1 compares output frequencies, waveform, channels, power output, voltage output, and crest factor between the subject devices and predicate devices.

The "acceptance criteria" here implicitly refer to the demonstration of comparable performance within a range considered safe and effective for electrosurgical generators, as evidenced by comparison to predicate devices. The document states: "The documentation submitted in this premarket notification demonstrates that the subject devices have comparable features and performance and, therefore, are substantially equivalent to the identified predicate devices."

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

Not applicable, as this is demonstrating substantial equivalence for an electrosurgical generator, not an AI/ML device that requires a test set of data. The evaluation is based on technical specifications and comparison to existing cleared devices.

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):

Not applicable, as this is an electrosurgical generator, not an AI/ML device relying on expert-established ground truth from a test set.

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

Not applicable.

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, as this is not an AI-assisted device.

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

Not applicable, as this is an electrosurgical generator, not an algorithm.

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

Not applicable. The "ground truth" for this type of device lies in adherence to established performance standards for electrosurgical generators and demonstrating equivalence to legally marketed predicate devices through engineering and functional comparisons.

8. The sample size for the training set:

Not applicable, as this is an electrosurgical generator, not an AI/ML device that undergoes training.

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

Not applicable.

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