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The AE-120A EEG Head Set is intended to amplify, capture, and wirelessly transmit electrical activity of the brain for review by a trained medical professional using the previously cleared and validated Nihon Kohden electroencephalograph systems (EEG-1200A series and EEG-9100) to assist in the diagnosis of neurological disorders. The AE-120A EEG Head Set and its associated EEG Software do not provide any diagnostic conclusion or automated alerts of an adverse clinical event about a patient's condition.

The device is intended for use by trained medical professionals in a medical facility such as a physician's office, laboratory, or clinic. The device is intended for use on adults (ages 18 and above). (Rx Only)

The Nihon Kohden AE-120A EEG Head Set is a battery powered (2 AA, LR6 alkaline disposable) wireless EEG head set which facilitates the placement of disposable EEG electrodes on the patient's scalp. The AE-120A EEG Head Set with the electrodes is then attached to the patient's head using the head set's chin, top, and rear straps.

With the head set turned on and secured in place, the head set acquires and amplifies electrical activity via EEG electrodes placed in contact with the patient's scalp. The captured waveforms from these signals are transmitted wirelessly via Bluetooth to a Nihon Kohden specified electroencephalograph through the AE-120A EEG Head Set and receiver.

The head set outputs the collected brain electrical activity to the computer component of the electroencephalograph system where a medical professional can review and interpret the information.

The AE-120A EEG Head Set has 8 channels for measurement along with one reference and one Z electrode. The electrodes are fixed into position with the head set to approximate the 10-20 electrode positions.

The AE-120A EEG Head Set is designed to work with the Nihon Kohden EEG-1200A series and EEG-9100, cleared in K080546 and K011204, respectively. The associated system software is used to facilitate the communication and display of the information from the head set.

The provided text describes a 510(k) premarket notification for the Nihon Kohden AE-120A EEG Head Set. This submission focuses on demonstrating substantial equivalence to a predicate device, primarily through performance testing and comparison of technological characteristics, rather than a clinical study evaluating diagnostic accuracy or human-in-the-loop improvement. Therefore, many aspects of a traditional clinical study (e.g., sample size for test set, adjudication methods, MRMC studies, effect size of human readers, ground truth establishment) are not relevant or described in this type of submission.

The document details performance testing related to electrical safety, biocompatibility, and electrode performance, but not a study to prove improved diagnostic accuracy for neurological disorders.

Here's an analysis of the provided information, focusing on what is described in the 510(k) summary:

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

The document describes several performance tests and their outcomes, which can be interpreted as demonstrating the device meets implicit acceptance criteria for safety and performance in its intended function. Explicit acceptance criteria values are stated for electrode performance testing.

2. Sample sized used for the test set and the data provenance

• Electrode Performance Test: "Twelve (12) electrode pairs were tested." The data provenance is not specified (e.g., country of origin, retrospective/prospective).
• Other tests (Software, Electrical Safety, Biocompatibility): These refer to verification and validation activities against standards and internal requirements, not studies on patient data. Thus, there isn't a "test set sample size" in the clinical sense.

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 because the submission describes device performance testing (e.g., electrical, mechanical, software functionality) rather than a clinical study requiring expert-established ground truth for diagnostic accuracy. The device "assists in the diagnosis of neurological disorders" for "review by a trained medical professional" but does not provide diagnostic conclusions or automated alerts itself.

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

Not applicable. There was no clinical test set requiring adjudication of diagnostic outcomes.

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 such study was conducted or described. This device is an EEG headset that amplifies, captures, and transmits raw electrical brain activity. It does not incorporate AI for interpretation or diagnostic assistance, nor does it claim to improve human reader performance.

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

Not applicable. The device's function is to acquire and transmit data for human review. It does not have a standalone diagnostic algorithm.

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

For the performance tests described:

• Electrode Performance: Ground truth was based on measurements against the specified criteria of the ANSI AAMI EC12:2000 standard, as measured by testing equipment.
• Biocompatibility: Ground truth was established by adherence to ISO 10993 series standards, verified through laboratory testing.
• Software, Electrical Safety & EMC: Ground truth was established by adherence to recognized national and international standards (e.g., IEC 60601 series, FDA guidances) through testing and verification/validation processes.

No clinical ground truth (e.g., expert consensus on neurological disorders, pathology, patient outcomes) was necessary for this 510(k) submission, as the device doesn't provide a diagnostic output.

8. The sample size for the training set

Not applicable. This device does not use machine learning or AI that would require a "training set" of data.

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

Not applicable, as there is no training set for this device.

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