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The Nicolet Electrocautery Detector is an accessory device supporting muting of external audible outputs when electrocautery interference is detected.

The Nicolet Electrocautery Detector interfaces between the auditory signal output from a nerve monitor and the nerve monitor's external speaker. The Electrocautery Detector automatically mutes the nerve monitor speaker when electrocautery interference is detected.

The Nicolet Electrocautery Detector is an accessory device designed to mute external audible outputs from a nerve monitor when electrocautery interference is detected. The device's performance is compared to a predicate device, the XOMED NIM-2 XL.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

The provided summary does not contain information regarding a specific "test set" in the context of clinical trials or performance testing with human subjects. The comparison is based on device specifications and features, not a study involving a particular sample size of cases or patients. The data provenance is derived from the technical specifications and design of the Nicolet Electrocautery Detector and its predicate device. This is a comparison of product specifications, not a clinical study.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

Since there is no mention of a "test set" for a clinical study or performance evaluation with human data, there is no information on the number of experts or their qualifications used to establish ground truth.

4. Adjudication Method for the Test Set

As there is no mention of a "test set" involving expert review of cases, there is no information on an adjudication method.

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

The document does not describe an MRMC comparative effectiveness study. This device is an accessory for a nerve monitor, designed to automatically mute auditory signals, not an AI-based diagnostic tool requiring human reader interpretation or improvement. Therefore, there is no information on an effect size for human reader improvement with or without AI assistance.

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

The document does not describe a standalone algorithm performance study. The device functions as an accessory that performs an automated action (muting) based on detecting electrocautery interference. The "performance" is implicitly evaluated by comparing its technical specifications (like recovery time and detection method) to those of the predicate device.

7. The Type of Ground Truth Used

The "ground truth" in this context is the technical specifications and functional design of the device and its predicate. The assessment is made by comparing these attributes, particularly the method of electrocautery detection and muting, and key performance parameters like recovery time. There is no mention of ground truth established by expert consensus, pathology, or outcomes data in a clinical trial setting.

8. The Sample Size for the Training Set

The provided document does not mention a "training set". This type of device, an electro-mechanical accessory, is not typically developed using machine learning or AI models that require a training set of data. Its functionality is based on detecting physical RF energy.

9. How the Ground Truth for the Training Set was Established

Since there is no mention of a training set, there is no information on how ground truth for a training set was established.

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The subject monitor detects bioelectrical signals from muscles for the purpose of guiding injections into the muscles identified. Although the monitor is indicated for guidance of any muscle-specific injection, it is typically used for injections into muscles of the head and neck. This includes botulinum toxin injections of facial and laryngeal muscles.

The subject monitor is intended to detect bioelectrical signals from muscles for the subject monitor in intentions into the muscles identified, including botulinum toxin injections of eye muscles.

The proposed EMG monitoring system is composed of a small, handheld monitor, a reusable patient interface cable and a disposable injector needle electrode. Commercially available surface electrodes, to act as references, may elcotrode. Onlinerally aranabitropoposed system as these are readily available or may not be provided with the proposed keys on the front console -- ON/OFF, at the politic of the of Check, Volume Down, and Mute. The software of the proposed EMG monitoring system interprets console key presses from the user and performs the action associated with that key.

The provided text is a 510(k) summary for the XOMED® AccuGuide Muscle Injection Monitor. As a 510(k) submission, the primary goal is to demonstrate substantial equivalence to a predicate device, not necessarily to prove absolute performance against predefined acceptance criteria from novel studies. Therefore, the information provided focuses on comparing the new device to existing, legally marketed devices.

Based on the document, here's a breakdown of the requested information, with specific answers where available and explanations where information is not present in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) submission does not present specific quantitative acceptance criteria or a dedicated performance study with a table of results. Instead, it relies on demonstrating that the proposed device, the AccuGuide, is substantially equivalent to a predicate device (Allergan BOTOX® Injection Amplifier) in terms of intended use, technology, and safety/effectiveness. This means it's assumed to meet the same unstated performance benchmarks as the predicate.

For the purpose of this request, we can infer the "acceptance criteria" and "reported performance" are met if the device is deemed substantially equivalent to the predicate.

2. Sample Size Used for the Test Set and the Data Provenance

The provided 510(k) summary does not describe a specific "test set" or a performance study with a defined sample size for the AccuGuide device. The submission relies on a comparison to a predicate device and existing knowledge of EMG technology. Therefore:

• Sample Size for Test Set: Not applicable / Not provided.
• Data Provenance: Not applicable, as no specific test data set is described for the new device. The comparison is based on the known performance and characteristics of the predicate device (Allergan BOTOX® Injection Amplifier), which is a "currently marketed" device. This implies its performance is established from its prior marketing and regulatory clearance, which would have involved some form of testing, but details are not provided here for the predicate either.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

This information is not provided in the 510(k) summary. Given that no specific test set or performance study is detailed for the AccuGuide, there is no mention of experts establishing a ground truth for such a study. The substantial equivalence argument relies on the established use and safety/effectiveness of the predicate device.

4. Adjudication Method for the Test Set

This information is not provided in the 510(k) summary. As there's no described test set or performance study, there's no mention of an adjudication method.

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

• MRMC Study Done: No, an MRMC comparative effectiveness study was not conducted or reported in this 510(k) submission.
• AI Assistance: The device described is an EMG monitor, a hardware medical device that provides bioelectrical signal detection. It does not incorporate Artificial Intelligence (AI) for interpretation or assistance in the way current AI-driven diagnostic tools do. Therefore, the concept of "human readers improve with AI vs without AI assistance" is not applicable here.

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

• Standalone Performance: Not applicable. The AccuGuide is a hardware device (EMG monitor) designed to provide real-time feedback (audible and visible through LCD bargraph) to a human user (clinician) to guide injections. It does not operate as a standalone "algorithm" generating diagnoses or interpretations without human involvement in the clinical context. Its function is to assist in real-time muscle localization during a procedure.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

Since no specific performance study is detailed, the type of ground truth for the AccuGuide's performance is not explicitly stated. However, the basis for its perceived "truth" or effectiveness stems from the functionality of its predicate device, the Allergan BOTOX® Injection Amplifier. The fundamental "ground truth" for these types of EMG monitors is the accurate detection of muscle electrical activity (bioelectrical signals) in the target muscle, confirmed by clinical observation (e.g., specific muscle movement in conjunction with the EMG response) and the subsequent successful and safe injection into that muscle, leading to the desired therapeutic outcome. This is a clinically established method for guiding precise injections.

8. The Sample Size for the Training Set

The provided 510(k) summary does not describe a "training set" for the AccuGuide. This device is a traditional hardware medical device, not a machine learning model that requires a training set in the conventional sense. The design and validation would have followed standard engineering and quality system processes, rather than machine learning training.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as no training set for a machine learning model is described for this device.

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This device is indicated for use in surgical procedures for patient-connected intraoperative nerve monitoring, i.e. assisting the surgeon in locating and mapping motor nerves through the use of electromyographic (EMG) signals and electrical stimulus of nerves.

The purpose of this 510(k) is to notify the FDA of changes that are intended to be made to the currently marketed NIM-2XL Nerve Integrity Monitor. As previously mentioned, these changes serve to improve the NIM-2XL even further: to make the device more "user friendly" and simplify its use, provide a cleaner, higher quality signal, provide additional options for documentation (printer, disk drive, and video-out) and to lower the overall cost of the system through the use of state-of-the-art componentry. Other than the changes specifically described in this notification, the device remains the same as previously provided in K934426.

Here's an analysis of the provided text regarding the NIM Monitor, focusing on acceptance criteria and study details.

Important Note: The provided document is a 510(k) summary for a premarket notification (K982595) for the NIM Monitor (Nerve Integrity Monitor). This type of document is primarily focused on demonstrating substantial equivalence to a previously cleared device, not typically on presenting full clinical study data for new acceptance criteria. Therefore, many of the requested details about specific acceptance criteria and detailed study performance will likely be absent or only broadly implied.

Acceptance Criteria and Device Performance

Based on the provided K982595 510(k) summary, the device is an updated version of a previously cleared device (NIM-2XL). The primary "acceptance criteria" here are demonstrating substantial equivalence to the predicate device and that the changes do not raise any new safety or effectiveness issues.

Study Information & Ground Truth

The document does not describe a standalone clinical study with new acceptance criteria in the way one might expect for a novel device or a device with significantly altered intended use. Instead, it relies on demonstrating that the modifications made to an already cleared device do not introduce new risks or change the fundamental performance that was previously accepted.

Here's a breakdown of the requested study details:

1. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • Not Applicable / Not Provided. The document does not describe a clinical "test set" in the traditional sense of evaluating new diagnostic accuracy or treatment efficacy. The evaluation performed appears to be a design verification and validation of the changes against the predicate device, including a "Hazard Analysis" and "software validation." This is an internal engineering and risk assessment process, not a clinical study with patients.

2. 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 / Not Provided. Ground truth for a clinical test set is not discussed because a clinical test set, as typically understood, was not used or reported here. The "ground truth" for the device's acceptable performance is implicitly the demonstrated safety and effectiveness of the predicate device, NIM-2XL.

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

   • Not Applicable / Not Provided. Adjudication methods are typically for resolving discrepancies in clinical assessments, which is not relevant to the type of submission presented.

4. 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 device is an intraoperative nerve monitor, not an AI-assisted diagnostic tool for human readers. An MRMC study is completely irrelevant here.

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

   • Not Applicable. This is a medical device that monitors physiological signals; it inherently operates "standalone" in generating its output (EMG signals, electrical stimulation). However, its intended use is "assisting the surgeon," meaning a human (the surgeon) is always "in the loop" for decision-making based on the device's output. The concept of "standalone performance" as typically applied to an AI algorithm making a diagnosis without human input is not relevant here. The device's "performance" is its ability to accurately detect and stimulate nerves and display EMG signals.

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

   • Implicitly, the established safety and effectiveness of the predicate device (NIM-2XL). For the changes themselves, the "ground truth" for the Hazard Analysis would be engineering standards, risk assessment methodologies, and potentially internal verification/validation testing and expert reviews (though not specified in clinical terms).

7. The sample size for the training set:

   • Not Applicable / Not Provided. This is not an AI/machine learning device that requires a "training set."

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

   • Not Applicable. As above, no training set is relevant for this device.

Summary of Approach in K982595:

This 510(k) submission is an example of a "special 510(k)" or "traditional 510(k) for modifications" where the focus is on demonstrating that changes to an existing cleared device do not alter its fundamental safety or effectiveness. The "study" here is primarily a design control process, including a Hazard Analysis and software validation, to confirm that the modifications maintain equivalence to the predicate device and introduce no new risks. It is not a clinical trial establishing new performance metrics.

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