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The Erbe Electrosurgical Unit (ESU/Generator) model VIO 3n with instruments and accessories is intended to deliver high frequency (HF) electrical current for the cutting and/or coagulation of tissue.

The Erbe ESU Model VIO® 3n is an electrosurgical unit (ESU) that delivers high-frequency (HF) electrical current for cutting and/or coagulation of tissue. The unit can be mounted/secured to a cart/system carrier or on a ceiling mount. Different footswitches are available for activating the ESU. The ESU VIO® 3n has several clearly defined monopolar and bipolar cutting and coagulation modes with different electrical waveforms and electrical parameters that are programmed with defined effect levels. Each effect level corresponds to a defined maximum power output and a voltage limitation. In combination with the compatible argon plasma coagulation unit APC 3 (K191234), it offers monopolar modes for argon plasma coagulation and argon-supported modes. The ESU has a touchscreen monitor that provides the user with an onscreen tutorial as well as settings and operational information. It also provides a small number of physical controls, such as the power switch, instrument sockets and a neutral electrode receptacle. Connections for the central power supply, for footswitches, for potential equalization of the operating theatre and Erbe Communication Bus (ECB) connections to other Erbe modules are located at the rear. The ESU emits sounds when instruments are activated, and messages are signaled. The actual application is carried out using compatible electrosurgical instruments that are connected to the generator. The VIO® 3n can be combined with matching Erbe devices and modules, instruments, and accessories.

To address various clinical needs, the ESU is available in 5 different configurations which are called "Fire", "Metal", "Stone", "Water" and "Timber". Whereas the configuration "Fire" includes all available modes and functionalities, the other configurations only offer a reduced number of modes and functionalities.

The provided FDA 510(k) clearance letter and summary for the Erbe ESU Model VIO® 3n with Accessories do not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and a specific study proving the device meets those criteria, particularly for an AI/software as a medical device (SaMD).

This document pertains to an electrosurgical unit, which is a hardware device for cutting and coagulating tissue using high-frequency electrical current. The "software" mentioned in the document refers to the operating software of the ESU itself, not an AI or diagnostic algorithm, and thus the type of performance metrics, ground truth, and study designs you're asking about (e.g., MRMC, standalone performance, expert consensus on diagnostic images) are not applicable to this type of device submission.

Therefore, I cannot provide a table of acceptance criteria and device performance in the context of an AI/SaMD, nor detailed information on test set sample sizes, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, or specific training set details, because this document describes a hardware device.

However, I can extract the information that is present about the non-clinical performance testing and what it aims to demonstrate:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a hardware electrosurgical unit, the "acceptance criteria" are generally related to compliance with electrical safety, EMC, and functional performance standards for tissue cutting/coagulation. The document does not provide specific quantitative acceptance criteria values or detailed performance metrics in a table. It states that the device "performs as intended per the product specifications and requirements."

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

• Test Set Sample Size: Not specified for any of the non-clinical tests.
• Data Provenance: Not specified, but the tests were performed "non-clinical," implying laboratory or bench testing rather than clinical patient data. The manufacturer is Erbe Elektromedizin GmbH (Germany).

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

• This question is not applicable to the non-clinical testing of an electrosurgical hardware device. Ground truth, in the context of AI/SaMD, usually refers to labeled diagnostic data. For this device, "ground truth" would be the measurable physical parameters and effects on tissue.

4. Adjudication method for the test set

• This question is not applicable. Adjudication methods like 2+1 or 3+1 are used for expert consensus on ambiguous diagnostic cases in AI/SaMD studies. For an ESU, performance is measured against engineering specifications and observed physical effects.

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, an MRMC study was not done. This type of study is relevant for diagnostic AI tools that assist human readers (e.g., radiologists interpreting images). The Erbe ESU Model VIO® 3n is an interventional hardware device, not a diagnostic AI.

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

• The term "standalone performance" for an AI algorithm is not directly applicable here. However, the non-clinical performance testing (functional, EMC, electrical safety) can be considered "standalone" in the sense that the device's technical capabilities were tested independently against specifications without a human operator's diagnostic interpretation loop. The device directly performs an action (cutting/coagulation) rather than providing information for human interpretation.

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

• For the functional testing, the "ground truth" would be the observable physical effects on tissue (e.g., degree of cutting, coagulation depth, eschar formation) and measured electrical parameters (power output, voltage, current) compared to established engineering specifications and the performance of predicate devices.
• For safety and EMC, the "ground truth" is compliance with international standards (e.g., IEC 60601 series).

8. The sample size for the training set

• This question is not applicable. The Erbe ESU Model VIO® 3n is an electrosurgical hardware device. It does not use a "training set" in the machine learning sense to learn and develop an algorithm. Its operating software is developed through traditional software engineering processes, not machine learning model training.

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

• This question is not applicable as there is no machine learning training set for this device.

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The flexible FiAPC probes are intended for argon plasma coagulation and ablation of tissue.

The FiAPC® plus probes are sterile, single-use flexible probes intended for argon plasma coagulation (APC) and ablation of tissue. The probes have a plug on the proximal end that enables the connection to the compatible electrosurgical unit (ESU) and APC unit. The plug is ergonomically designed and contains a filter that isolates the device side from the patient side. The plug also contains an instrument recognition which ensures that the instrument can only be operated with the compatible parent devices. The connector is followed by a long tube so that the probe can be inserted into the working channel of an endoscope. At the distal end there is an opening through which the argon plasma is released. The flexible FiAPC® plus probes are available in different variants. All variants have the same outer diameter but differ in their length and distal opening, i.e. axial opening (straight fire) or lateral opening (side fire).

This document describes the Erbe Elektromedizin GmbH FiAPC plus probes, an electrosurgical device accessory. The provided text is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device, rather than defining novel acceptance criteria for a new type of device or an AI/software-based system.

Therefore, the information requested in your prompt regarding acceptance criteria and studies that prove a device meets those criteria, particularly for AI/software, is not fully applicable or present in this document. This document describes a medical device accessory and its comparison to an already marketed predicate device, primarily focusing on physical and functional characteristics, and safety and effectiveness relative to that predicate.

However, I can extract the information that is relevant to your prompt based on the provided text, and explicitly state where information is not available or not applicable.

Here's a breakdown of the available information:

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

The document doesn't explicitly list "acceptance criteria" in the way a software/AI device might, with specific metrics to hit. Instead, it focuses on demonstrating comparable performance and meeting design specifications through various tests.

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

• Test Set Description: The "test set" for this device primarily refers to the physical units of the FiAPC plus probes and the predicate device used in bench and tissue testing.
• Sample Size:
  • For tissue testing: Not explicitly stated beyond "side-by-side tissue testing."
  • For other bench tests (EMC, electrical safety, sterilization, packaging): Not explicitly stated for each test, but it is implied that sufficient samples were tested to demonstrate compliance and validate performance.
• Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). The tests were conducted internally or by contracted labs as part of the manufacturer's (Erbe Elektromedizin GmbH, Germany) verification and validation activities.

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 and not provided in the document. The "ground truth" for this type of medical device (argon plasma coagulation probes) is established through biophysical principles, engineering standards, and medical consensus on desired tissue effects, rather than expert annotation of data like in an AI/software context. Tissue effects are measured directly.

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

• This information is not applicable and not provided. Adjudication methods like 2+1 or 3+1 are typically used for establishing ground truth from expert opinions in studies involving subjective assessment (e.g., image interpretation for AI). For physical device performance, direct measurements and compliance with objective standards are used.

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:

• This information is not applicable and not provided. MRMC studies are specific to evaluating diagnostic accuracy, particularly for imaging devices or AI tools where human interpretation is involved. This device is an electrosurgical accessory, not a diagnostic or AI-assisted system for human readers.

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

• This information is not applicable and not provided. This device is a physical electrosurgical probe, not an algorithm or a software-only device.

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

• The "ground truth" for this device's performance, as demonstrated in the document, is based on:
  • Direct Physical Measurements/Bench Testing: E.g., electrical load capacity, gas flow rate, probe dimensions.
  • Compliance with Industry Standards: E.g., ISO 10993-1 for biocompatibility, IEC 60601 series for electrical safety, ISO 11135 for sterilization.
  • Observed Tissue Effects: "Comparable tissue effects and comparable ignition distances" to the predicate device. This is a direct physical result rather than an expert consensus or pathology report in the typical sense, though assessment of these effects would involve trained personnel.
  • Comparison to Predicate Device: The overarching "ground truth" for substantial equivalence is the safety and effectiveness of the legally marketed predicate device.

8. The sample size for the training set:

• This information is not applicable and not provided. This device is not an AI/machine learning system, so there is no "training set" in the context of AI.

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

• This information is not applicable and not provided for the reasons stated in point 8.

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