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The Neurosign® V4 Intraoperative Nerve Monitor is intended for locating and identifying cranial and peripheral motor and mixed motor-sensory nerves during surgery, including spinal nerve roots.

Indications for Neurosign® V4 EMG Monitoring Procedures include: Intracranial, Extracranial, Extratemporal, Neck Dissections, Thoracic Surgeries, and Upper and Lower Extremities.

Indications for spinal procedures which may use Neurosign® V4 EMG monitoring include: Degenerative Treatments, Pedicle Screw Procedures, Fusion Cages, Rhizotomy, Orthopedic Surgery and Open and Percutaneous Lumbar Procedures.

The Neurosign® V4 Intraoperative Nerve Monitor (IONM) is a multi-channel nerve monitor designed for use in Ear, Nose and Throat (ENT) surgery and neurosurgery. The subject device differs from its primary predicate due to the introduction of improved Pre-amplifier and Stimulator pod cables, as well the addition of an 8-channel Pre-amplifier variant.

Using needle or surface electrodes connected to the Pre-amplifier, the nerve monitor detects electromyographic (EMG) signals within muscles caused by the contraction of the muscle due to mechanical manipulation or electrical stimulation of the nerve controlling it. The Neurosign® V4 then amplifies the EMG data into an audible signal and displays the data as a waveform on the active monitoring screen.

The Neurosign® V4 Intraoperative Nerve Monitor is used for patient treatment by prescription only under the supervision of a licensed physician.

The Neurosign® V4 is an integrated system consisting of a combination of hardware, software, and accessories.

The provided document is a 510(k) Premarket Notification from the FDA for the Neurosign® V4 Intraoperative Nerve Monitor. This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, not typically a study that establishes performance against discrete clinical acceptance criteria in the same way a PMA (Premarket Approval) submission would.

Therefore, the document does not contain a study with acceptance criteria and reported device performance in the typical sense of a clinical trial for a novel device. Instead, the "acceptance criteria" are compliance with various recognized standards and the "study" is non-clinical bench testing to demonstrate that modifications to an existing predicate device do not alter its safety or effectiveness.

Here's an analysis based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Sizes used for the Test Set and Data Provenance

This submission is based on non-clinical bench testing and does not involve human subjects as a "test set" in the sense of a clinical study.

• Electrical Safety, EMC, Alarm Systems, Biocompatibility: "A sample Neurosign® V4 (4-Channel and 8-Channel Variants)" or "A sample Neurosign® V4 (4-Channel)" or "Samples of these materials" were tested. The exact number of units/samples is not specified beyond "a sample" or "samples."
• Human Factors Testing: Not specified, but "Usability testing was performed to analyze the user experience of the 8-Channel Neurosign® V4." This typically involves a small group of representative users, but the size is not disclosed.
• Data Provenance: All testing appears to be retrospective relative to the design changes, commissioned by Magstim Company Ltd. and conducted by either Magstim or independent test laboratories (Element Materials Technology, Eurofins Hursley). The country of origin for the tests is not explicitly stated for all labs, but Magstim is a UK company.

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

This type of submission does not involve "ground truth" established by clinical experts in the context of diagnostic accuracy or treatment effectiveness. The "ground truth" here is compliance with recognized engineering and safety standards, as verified by independent test laboratories and Magstim's internal testing. The qualifications would be expertise in those specific standards and testing protocols, which are inherent to the testing bodies but not explicitly detailed for individual experts in this document.

4. Adjudication Method for the Test Set

Not applicable. This is not a clinical study requiring adjudication of clinical outcomes. The "adjudication" is essentially the determination of compliance with the specified standards by the testing bodies.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. This document does not describe a MRMC comparative effectiveness study. The device is an intraoperative nerve monitor, and the study focuses on its safety and performance based on engineering and safety standards, and its substantial equivalence to predicate devices, not on human reader performance with or without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Yes, in a way. The testing described (electrical safety, EMC, alarm systems, biocompatibility, and software V&V) assesses the device's technical performance and safety characteristics in isolation, or as an integrated system, without necessarily involving a human-in-the-loop performance assessment of its diagnostic or treatment guidance capability in a clinical setting beyond usability testing for user experience. The "performance" mentioned for cables is also standalone bench testing.

7. Type of Ground Truth Used

The ground truth used in this context is:

• Compliance with recognized international and national standards (e.g., IEC 60601 series, ISO 10993 series for biocompatibility, AAMI/ANSI HE75, IEC 62366-1 for human factors).
• Performance specifications (e.g., isolation parameters, EMC performance, software functions) as tested against predefined engineering requirements.
• Usability metrics defined in the human factors engineering report.

8. Sample Size for the Training Set

Not applicable. This device is not an AI/ML algorithm that requires a "training set" in the computational sense. It is a hardware medical device with embedded software. The software underwent verification and validation, but this refers to traditional software testing, not AI model training.

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

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

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The Neurosign® V4 Intraoperative Nerve Monitor is intended for locating and identifying cranial and peripheral motor and mixed motor-sensory nerves during surgery, including spinal nerve roots.

Indications for Neurosign® V4 EMG Monitoring Procedures include: Intracranial, Extracranial, Extratemporal, Neck Dissections, Thoracic Surgeries, and Upper and Lower Extremities.

Indications for spinal procedures which may use Neurosign® V4 EMG monitoring include: Degenerative Treatments, Pedicle Screw Procedures, Fusion Cages, Rhizotomy, Orthopedic Surgery and Open and Percutaneous Lumbar Procedures.

The Neurosign® V4 Intraoperative Nerve Monitor is a multi-channel nerve monitor designed for use in Ear, Nose and Throat (ENT) surgery and neurosurgery.

Using needle or surface electrodes connected to the Pre-Amplifier Pod, the nerve monitor detects electromyographic (EMG) signals within muscles caused by the contraction of the muscle due to mechanical manipulation or electrical stimulation of the nerve controlling it. The Neurosign® V4 then amplifies the EMG data into an audible signal and displays the data as a waveform on the active monitoring screen.

The Neurosign® V4 is an integrated system consisting of a combination of hardware, software, and accessories.

The Neurosian® V4 is comprised of following four components:

1. Neurosign® V4 Intraoperative Nerve Monitor
2. Neurosign® V4 Pre-Amplifier Pod 4 Channel
3. Neurosign® V4 Stimulator Pod
4. Neurosign® V4 Mute Sensor

The Neurosign® V4 Intraoperative Nerve Monitor (IONM) includes a user interface comprised of an audio output, a color graphics display with a touch screen and dedicated rotary controls for frequently adjusted parameters.

EMG signals are collected from the patient using needle and surface electrodes. The Neurosign® V4 Pre-Amplifier Pod collects, processes and transmits the EMG signals to the IONM for display and for an audio output.

The Neurosign® V4 Stimulator Pod allows the simultaneous connection of two stimulating probes for the mapping and locating of nerves within tissue, and to test the nerve activity at various stages during surgery.

The provided text describes the regulatory clearance of the Neurosign® V4 Intraoperative Nerve Monitor, primarily through demonstrating substantial equivalence to predicate devices, rather than an AI-driven device requiring extensive ground truth establishment and MRMC studies.

Therefore, many of the requested elements for an AI/ML-driven device evaluation, such as sample sizes for training/test sets, expert qualifications for ground truth, adjudication methods, and MRMC study details, are not applicable or detailed in this document. The document focuses on demonstrating that the new device performs similarly and is as safe and effective as existing legally marketed predicate devices through non-clinical testing and comparisons of technological characteristics.

However, I can extract the relevant information regarding acceptance criteria and the study that proves the device meets those criteria based on the provided text, primarily under the "Non-Clinical Testing" section.

Acceptance Criteria and Device Performance Study for Neurosign® V4 Intraoperative Nerve Monitor

This submission focuses on demonstrating substantial equivalence to predicate devices rather than meeting specific performance metrics for an AI/ML algorithm. The "acceptance criteria" are implied by compliance with recognized standards and performance parity with predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Testing: The document refers to "A sample Neurosign® V4" being tested for electrical safety, EMC, and alarm systems. For biocompatibility, "Samples of these materials" were tested. For amplifier and stimulator equivalence, the testing was done by comparing the Neurosign® V4 directly against the predicate device (NIM-Response 3.0) using function generators and oscilloscopes, not patient data. Therefore, the "sample size" is effectively one device model, and samples of materials/components, tested under controlled laboratory conditions against various standard requirements.
• Data Provenance: This is a non-clinical, laboratory-based study. The data is generated from controlled tests of the device's hardware and software components against international standards and in direct comparison with a predicate device. There is no mention of human (patient) data or geographical origin of such data. This is retrospective in the sense that it evaluates the manufactured device against pre-defined performance and safety standards.

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

• N/A. This submission does not involve clinical data or deep learning models requiring "ground truth" established by human experts in the typical sense of AI/ML device evaluations. The ground truth for the non-clinical tests is based on the specifications of the standards (e.g., IEC 60601-1) and the measured performance of the predicate device. The testing was performed by "independent test laboratories" (e.g., Element Materials Technology, Kiwa Blackwood Compliance Laboratories, Harlan Laboratories Ltd, Envigo Research Ltd), implying their expertise in medical device testing and regulatory compliance.

4. Adjudication Method for the Test Set

• N/A. Since there's no qualitative assessment of clinical data by multiple readers, an adjudication method is not applicable. The tests are quantitative measurements against predefined specifications.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No. An MRMC study was not conducted as this device is not an AI/ML diagnostic aid intended to improve human reader performance on medical images. It is an intraoperative nerve monitor, and its safety and effectiveness were demonstrated through engineering (non-clinical) tests and substantial equivalence.

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

• Yes, in spirit. The performance evaluation for the amplifier and stimulator equivalence was a "standalone" evaluation of the device's electrical characteristics. The software verification and validation are also a standalone assessment of the device's algorithmic performance. However, this is not an "algorithm only" study in the context of an AI/ML diagnostic device, but rather the performance of an integrated hardware and software system.

7. The Type of Ground Truth Used

• Engineering Specifications and Predicate Device Performance: The "ground truth" used for testing was primarily:
  • Compliance with specific international standards (e.g., IEC 60601-1, EN 60601-1-2, IEC 60601-1-8, ISO 10993 series).
  • The measured electrical output and signal processing characteristics of the legally marketed predicate device (NIM-Response 3.0). The acceptance criteria for the Neurosign® V4's performance were defined as being "within 5% of the target input and ±1% of each other" when compared to the predicate for EMG acquisition, and "almost identical" for stimulator performance.

8. The Sample Size for the Training Set

• N/A. This device does not employ a machine learning model that requires a training set in the typical sense. Its functionality is based on established electrophysiology principles and pre-programmed algorithms, not data-driven learning.

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

• N/A. As no training set was used, this question is not applicable.

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