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CNS Envision is intended for use by qualified personnel in the review, and analysis of patient data collected using external physiological monitors. These data are: raw and quantitative EEG, recorded video data, generic vital signs, electrocardiography, electromyography, intracranial pressures, transcranial Doppler measurements, and Glasgow Coma Score.

CNS Envision includes the calculation and display of a set of quantitative measures intended to monitor and analyze the EEG waveforms. These include, for example, frequency bands, asymmetry, and burst suppression. These quantitative EEG measures should always be interpreted in conjunction with review of the original EEG waveforms.

The aEEG functionality included in CNS Envision is intended to monitor the state of the brain.

CNS Envision is intended for use by a physician or other qualified medical personnel who will exercise professional judgement in using the information. It is intended for use on patients of all ages.

This device does not provide any diagnostic conclusion about the patient's condition to the user.

CNS Envision is a Microsoft Windows-based software application that facilitates the review, annotation and analysis of patient data and physiological measurements. Some of these data, such as ECG, are displayed in raw format whereas other types, such as EEG, are analyzed and quantified by the software. The specific type of input data that are reviewable by CNS Envision software are: Raw electroencephalography (EEG) Quantitative EEG trends; density spectral arrays (DSA) spectral edge frequency (SEF), alpha-delta ratio (ADR), and amplitude EEG (aEEG) Video Generic vital signs which are heart rate (HR), respiration rate (RR), pulse oximetry (SpO2), blood pressure, arterial blood pressure (ABP), mean arterial pressure (MAP), and body temperature Electrocardiography (ECG) Electromyography (EMG) Intracranial pressure (ICP) Transcranial Doppler (TCD) measurements (e.g. spectral envelope, peak velocity, and pulsatility index; TCD measurement is collected by the predicate K080217 device's interface module which interfaces with the Spencer TCD device cleared in K002533, which was a predicate to the predicate K080217 Glasgow Coma Score (GCS); this parameter is manually entered on the CNS Monitor (K080217) with 3 total GCS scores by the user; the CNS software automatically sums the 3 scores and stores the data to provide a trend graph

CNS Envision also has several features to enable ease-of-use. For example, users may select customized layouts that provide data displays that can be tailored to their monitoring needs according to data sources. The subject device also offers customizable EEG montages that present raw EEG data to medical personnel for interpretation.

Unlike the predicate device, Component Neuromonitoring System™, the subject device does not perform direct data acquisition. Instead, it offers the ability to review data remotely or adjust the review speed.

The provided text is a 510(k) summary for the CNS Envision device. It describes the device's intended use, technological characteristics, and comparison to predicate devices, but it does not contain information about specific acceptance criteria, device performance metrics (e.g., sensitivity, specificity, accuracy), sample sizes for test or training sets, ground truth establishment details, or any multi-reader multi-case (MRMC) study results.

The document states that "Software verification and validation testing was conducted and documentation provided as recommended by the Guidance for the Content of Software Contained in Medical Devices, issued May 2005. Traceability has been documented between all system specifications to validation test protocols. Verification and validation testing includes module-level testing, integration-level testing, and system-level testing. In addition, tests according to “IEC 62366-1:2015, Medical Devices Part 1—Application of usability engineering to medical devices” were performed."

This indicates that some testing was done to ensure the software functions as intended and meets usability standards, but the specific performance results in terms of clinical accuracy or equivalent metrics are not present in this summary. The summary focuses on establishing substantial equivalence based on intended use and technological characteristics rather than a detailed performance study like those typically expected for AI/ML-based diagnostic devices.

Therefore, I cannot provide a table of acceptance criteria and reported device performance, or details about the sample sizes, expert ground truth, adjudication methods, MRMC studies, or standalone performance for this specific device based on the provided text. The device "CNS Envision" is described as software that analyzes and quantifies EEG, but "does not provide any diagnostic conclusion about the patient's condition to the user" and "does not contain automated detection algorithms," suggesting it's a tool for experts rather than an automated diagnostic AI.

To illustrate what such an answer would look like if the information were available, here's a template:

Hypothetical Example (based on standard AI/ML medical device studies, NOT from the provided text):

Given the provided document does not contain the requested information regarding specific acceptance criteria, performance metrics, training/test set details, or human reader studies, I cannot fill out the detailed table and answer the questions directly from the text.

However, if this were an AI-powered diagnostic device, the requested information would typically be presented as follows:

1. Table of Acceptance Criteria and Reported Device Performance (Hypothetical Example - Data NOT from provided text)

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