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The Compumedics Neuvo System is intended for measuring recording of the electrical activity of a patient's brain and/or through the attachment of multiple electrodes at various locations to aid in monitoring and diagnosis as routinely found in clinical settings for EEG. The system is intended for the EEG and long/middle/short- latency EP registration in the research environment. The system is intended to be used by qualified/trained EEG technologists and/or physicians. The data acquired must be interpreted by a qualified physician.

The Compumedics Neuvo System is intended for measuring of the electrical activity of a patient's brain and/or through the attachment of multiple electrodes at various locations to aid in monitoring and diagnosis as routinely found in clinical settings for EEG. The system is intended for the EEG and long/middle/short-latency EP registration in the research environment. The system is intended to be used by qualified/traincd EEG technologists and/or physicians. The data acquired must be interpreted by a qualified physician.

The Neuvo Amplifier System is an EEG/ERP/EP amplifier and data acquisition system. The amplifier and data acquisition clectronics are housed in a small enclosure (Headbox) placed near the patient, and into which individual clectrodes, collections of electrodes, may be connected. Additionally a high density electrode cap connector is provided on the Headbox. The Headbox also contains a connector for the interconnect cable to the System Unit.

The System Unit is slightly larger than the Headbox and serves as an interface between up to four Headboxes and the host computer.

The system operates under the software control of a host computer over an Ethernet 100BaseT interface. Data flows from the Neuvo amplifier over this interface.

Here's an analysis of the provided text regarding the Neuvo device's acceptance criteria and study, based on the information available in the 510(k) summary:

Unfortunately, the provided 510(k) summary for the Compumedics Neuvo (K081151) does not contain information about acceptance criteria or specific study results demonstrating performance for the device.

This document primarily serves as a submission for substantial equivalence to a predicate device (SynAmps2 510(k) # K023771) and focuses on describing the device, its intended use, and its classification. Performance data with acceptance criteria is typically detailed in separate sections of a 510(k) submission, such as a "Summary of Design Control Documentation" or "Performance Data," which are not present in the given excerpt.

Therefore, I cannot provide the requested information. The document focuses on:

• Administrative details: Contact person, date prepared, proprietary and common names, classification, and predicate device.
• Device description: Explanation of the Neuvo system components (amplifier, headbox, system unit, software control).
• Intended Use/Indications for Use: What the device is designed to do (measure electrical activity of the brain to aid in monitoring and diagnosis for EEG, and for EP registration in research).
• FDA correspondence: The letter confirming substantial equivalence.

Without further documentation from the 510(k) submission, it's impossible to answer the specific questions about acceptance criteria, study design, sample sizes, ground truth, or expert involvement.

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For long term unattended EEG or other electrophysiological signal monitoring and recording.
This device is intended for use by physicians skilled in electroencephalography. These individuals are typically Board Certified Neurologists or Neurophysiologist or the equivalent or Ph.D. level Electroencephalographers.
We recommend placement of electrodes in accordance with the 10.20 International System.

Like the predicate WARATAH® and Cardinal® Digital EEG and Sleep Acquisition Devices (WARATAH® Devices), the PANBUS® Digital EEG and Sleep Acquisition Devices (PANBUS® Devices) are provided to Original Equipment Manufactures (OEM) for creation of an electroencephalography (EEG) recording system. Significant PANBUS® Devices are:
I ) Personal computer (PC) interface board;
2) Electrode interface connection (Jackbox);
3) Communication protocol and port (PANBUS);
4) Amplifier(s);
5) Electrode lead wire sets.

The provided text describes a 510(k) summary for the PANBUS® Digital EEG and Sleep Acquisition Devices. It's important to note that a 510(k) application focuses on demonstrating substantial equivalence to a predicate device, rather than proving the safety and effectiveness from scratch through extensive clinical trials. Therefore, the information typically found in such a document regarding detailed acceptance criteria and a study proving device performance against those criteria is limited.

Here's an analysis based on the provided text:

Acceptance Criteria and Reported Device Performance

Study Details and Ground Truth Establishment

Given that this is a 510(k) summary for an EEG and sleep acquisition device (hardware and interface components, not an AI diagnostic algorithm), the typical elements for evaluating AI-based diagnostic devices (like sample size for test sets, experts for ground truth, MRMC studies) are not applicable or not explicitly detailed in this type of submission.

Here's a breakdown of what can be inferred or is explicitly absent:

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

   • Not Applicable/Not Provided: This document describes a medical device's technical equivalence, not an AI algorithm's performance on a specific dataset. There is no mention of a "test set" in the context of clinical data for performance evaluation of an AI algorithm. The "testing" mentioned refers to engineering verification and validation of the device components.

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

   • Not Applicable/Not Provided: Ground truth in the context of medical image interpretation or AI model training/testing is not relevant here, as this is a hardware device for signal acquisition.

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

   • Not Applicable/Not Provided: See explanation above.

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 is a hardware device for acquiring physiological signals (EEG, PSG). It does not involve human readers interpreting data with or without AI assistance. Therefore, an MRMC study is not relevant to this device.

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

   • Not Applicable/No: This device is a system for acquiring biological signals. It's not an "algorithm only" device in the sense of an AI diagnostic tool. Its function is to facilitate the recording of physiological data for human interpretation.

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

   • Not Applicable/Not Provided: The "ground truth" for this type of device would relate to the accuracy and fidelity of its signal acquisition and processing capabilities, typically verified against known electrical signals or established measurement standards, rather than clinical outcomes or expert consensus on a diagnosis. The document mentions "Hardware verification of design output meeting design input requirements," which implies that the device was tested against its technical specifications.

7. The sample size for the training set:

   • Not Applicable/Not Provided: There is no mention of a "training set" as this is not an AI/ML algorithm that learns from data.

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

   • Not Applicable/Not Provided: See explanation above.

In summary, the provided document describes a 510(k) submission for a hardware device (EEG and sleep acquisition components) that aims to demonstrate substantial equivalence to a predicate device. The "study" referenced is primarily the design control process, including engineering verification and validation against technical specifications and consensus standards, rather than a clinical performance study with human readers or AI algorithms with defined test sets and ground truths.

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