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The QUEX ED and QUEX S device is indicated for use as an Electrophysiological System. The Electrophysiological System is made up of the following Items which are functions of the QUEX ED and S device:

1. Two channel EEG:

The QUEX ED and S Device is intended to record and store EEG signals, and to present the EEG signals in visual formats in real time. The visual signals assist trained medical staff to make neurological diagnoses. The EEG device does not provide any diagnoses conclusion about the subject's condition and does not provide any automated alerts of an adverse clinical event. The QUEX ED AND S Device is intended to be used in a professional healthcare facility environment.
2. GSR [galvanic skin response measuring]

The QUEX ED and S device is intended for use by trained healthcare professionals, to detect and monitor electrical signals produced by the body skin conductance by using electrodes placed on the skin.

QUEX ED or QUEX S devices are contains the following components:

• QUEX ED or QUEX S hardware.
• I QUEX Monitor software
• . USB - USB cable for data communication and power supply.
• EEG electrodes (head electrodes)
• Electrodes for GSR measurements (limbs)
• I Cable harnesses for head and limbs.

The QUEX Monitor software is exclusively used for QUEX ED or QUEX S as part of the system.

The EEG electrodes and the electrodes used for GSR measurements are connected to the QUEX ED or S devices. The device makes the necessary gain on the analog signals and digitalize the signals. The digitalized information is acquired and displayed by the QUEX Monitor software. The QUEX monitor software can run on PCs, notebooks with Windows OS.

Electroencephalography (EEG), measures brain wave activity. The system uses the head harness and electrodes to acquire the signals. The QUEX Devices are measures brain activity on two channels. The EEG wave recording electrodes are connected to the forehead with dry electrodes.

The galvanic skin response (GSR, which falls under the umbrella term of electrodermal activity, or EDA) refers to changes in sweat gland activity.

The GSR recording is done via limb electrodes attached to the wrists and ankles.

The provided FDA 510(k) summary (K232779) for the QUEX ED and QUEX S device describes the regulatory submission for an electrophysiological system, specifically for EEG and GSR measurements. While it details acceptance criteria for various technical aspects like electrical safety and electromagnetic compatibility, and states that “All samples passed the acceptance criteria” for these tests, it does not describe a clinical study meeting the criteria of a multi-reader multi-case (MRMC) comparative effectiveness study or a standalone algorithm-only performance study on a test set with an established ground truth assessed by multiple experts.

The submission focuses on establishing substantial equivalence to a predicate device (Neurosteer Inc. Neurosteer EEG Recorder K221563) primarily through technical comparisons and bench testing. The "performance data" mentioned in the conclusion refers to these bench tests, not a clinical study involving human readers or algorithmic performance against a clinical ground truth.

Therefore, many of the requested details about acceptance criteria and study designs are not present in this document because the device's substantial equivalence was established through technical specifications and bench testing, not through a clinical performance study as typically seen with AI/ML-driven diagnostic devices.

Here's an attempt to answer the questions based only on the provided text, highlighting what is present and what is absent:

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

The document provides acceptance criteria and performance for various bench tests, not for a clinical diagnostic performance study.

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

This document describes bench tests on hardware/software samples, not a clinical study with a test set of patient data. The sample size is referred to as "All samples." No patient data provenance is applicable given the nature of the tests.

3. 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. No ground truth based on expert consensus for clinical diagnosis was established as this was not a clinical performance study. The tests focused on electrical, EMC, and signal performance according to industry standards.

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

Not applicable. No clinical test set and human readers for adjudication were involved.

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 MRMC study was performed or described. The product is an electrophysiological system for recording and displaying signals to assist trained medical staff in making neurological diagnoses, and it "does not provide any diagnoses conclusion about the subject's condition and does not provide any automated alerts of an adverse clinical event." Therefore, there is no AI component assisting human readers in this context.

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

No standalone algorithm performance study was performed or described. The device is a signal acquisition and display system for human interpretation, not an automated diagnostic algorithm.

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

Not applicable. The "ground truth" for the non-clinical tests was the adherence to specified engineering standards and the device's own technical specifications.

8. The sample size for the training set

Not applicable. This document pertains to the regulatory clearance of a medical device based on its functional and safety performance, not the training of an AI/ML algorithm.

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

Not applicable. No training set or ground truth for such a set is mentioned.

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