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. An RF Generator to provide the heating energy. The Generator incorporates the Cooling Module to supply coolant which provides the cooling energy.
. A hand piece that couples the cooling and heating energy to the tissue through the treatment tip.
A footswitch that allows the user to turn the RF Energy on or off.
. 5cm or 8cm Sterile Disposable Treatment Tips.

Accessories include:

Coupling Fluid
Cryogen ●
Return Cable ●
Return Pad ●
. Power Cord

AI/ML Overview

The provided document describes the Viveve 2.0 System, an electrosurgical device that delivers radiofrequency energy. The primary change in this 510(k) submission (K193611) compared to its predicate device (K190422) is the addition of Contact Quality Monitoring (CQM) software and a modified user interface. The study focuses on demonstrating the safety and effectiveness of this added feature.

Here's a breakdown of the requested information based on the document:

1. Table of Acceptance Criteria and Reported Device Performance

Feature/Test	Acceptance Criteria	Reported Device Performance
CQM Contact Resistance Measurement	0 to 200 Ω with ±10% (100 Ω - 200 Ω range) and ± 10 Ω accuracy (< 100 Ω)	The CQM reading was as expected between 50 Ω ± 10 Ω with the RF Activated.
CQM Circuit Response Time Constant	< 20 ms	The voltage on channel 1 of the oscilloscope transitioned 63% of the way from low to high in <= 20 ms.
RF Output Disable on Loss of Patient Contact	The RF Generator hardware shall support detection and provide means to disable the RF output for the following operating condition error: Loss of patient contact.	The RF Generator did fault when the CQM circuit was not complete, resulting in radiofrequency interruption to the patient.
CONTACT MAP Graphic Illumination (GUI)	Not illuminated when the Return Pad is not connected to the phantom tissue; illuminated green when the Return Pad is connected to the phantom tissue.	The CONTACT MAP graphic within the Graphic User Interface was not illuminated when the Return Pad was not connected and was illuminated green when connected.
Error Message on Inadequate Return Pad Contact	When the Return Pad is not adequately connected to the phantom tissue, the RF Generator will fault and result in an E63 - Check Tip Contact error. Acknowledge the error by selecting OK. Place the Return Pad securely on the phantom tissue so that the CONTACT MAP is illuminated and ensure a pulse is delivered.	An E63 - Check Tip Contact error was generated when the Return Pad was not adequately connected. A pulse was delivered after the Return Pad was securely placed and the CONTACT MAP illuminated.
Overall Software Performance (CQM Updates)	Meet the impacted customer requirements identified within ENG-017 Impact Analysis for CQM Updates.	All tested functions performed as expected, and the CQM updates met the identified customer requirements.
Electrical Safety / EMC Testing	Conformance to various IEC and EMC standards (detailed in Section 5.9).	All parameters in applicable standards were met and recorded as PASS results.

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

The document does not specify a specific "test set" in terms of patient data. The testing described for the CQM and software validation was performed on the device itself, likely using phantom tissue (pork belly) for functional tests of the return pad contact. The data provenance is internal testing performed by Viveve and by contract manufacturer Sparton Medical, as well as third-party testing by Intertek. There is no information about country of origin of data or whether it was retrospective or prospective, as it's not a clinical study on human subjects but rather device verification and validation.

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

Not applicable. The ground truth for this device modification is based on engineering specifications and compliance with established electrical safety and software validation standards, not expert clinical interpretation of data. The "ground truth" is that the device correctly identifies and reports contact quality and disables RF output when necessary.

4. Adjudication method for the test set

Not applicable. This was device verification and validation against engineering specifications and international standards, not a clinical study requiring adjudication of expert interpretations.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

No. This document does not describe an MRMC comparative effectiveness study. The submission is for a modification to an electrosurgical device, specifically related to a safety feature (Contact Quality Monitoring). It does not involve human readers interpreting medical images or data from an AI system.

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

Yes, in a sense. The testing described for the CQM feature and software verification is a standalone evaluation of the algorithm's performance in monitoring contact and issuing alerts or disabling RF output. There is no mention of a "human-in-the-loop performance" study described in this document for the specific change being cleared. The device's safety mechanisms (like CQM) are designed to operate automatically.

7. The type of ground truth used

The ground truth used for this submission is based on:

Engineering specifications and design requirements: The device's expected behavior and performance characteristics (e.g., resistance range, response time for CQM).
International standards conformance: Compliance with established electrical safety and electromagnetic compatibility standards (e.g., AAMI ES60601-1, IEC 60601-1-6, IEC 60601-2-2, IEC 60601-1-2).
Functional validation against known states: Demonstrating that the system responds correctly to scenarios like adequate vs. inadequate return pad contact using phantom tissue.

8. The sample size for the training set

Not applicable. This is not an AI/ML device that requires a training set of data. The "software" in question is for Contact Quality Monitoring, a rules-based or algorithmic safety feature, not a learning algorithm.

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

Not applicable, as there is no training set for an AI/ML algorithm in this context.

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