Search Results

Neuronaute is a system intended to acquire, display, store, archive, and periodically transmit EEG signals from the brain using a full montage array to enable review at a physician's office, hospital, or other remote locations. It allows remote access by users via the Neuronaute N-CLOUD which receives EEG signals from Neuronaute Head Module which sends transmissions to the cloud. Neuronaute and its associated software are intended to assist in the diagnosis of neurological disorders. Neuronaute and its components do not provide any diagnostics conclusions or automated alerts of an adverse clinical event about a patient's clinical condition.

The device is for use by trained medical professionals for patients under medical supervision. The device is intended for use on adults (ages 18 and above). Neuronaute is not intended to replace direct communication with healthcare providers. The system data should not be used alone, but should be used along with all other clinical data and exams to come to a diagnosis.

Neuronaute allows up to 24 channels EEG monitoring. It includes the following components: Neuronaute Head Module, Neuronaute High Capacity Battery Module, Neuronaute BioAdapter, Neuronaute Mobile App, Neuronaute N-CLOUD, Neuronaute N-DEO, Neuronaute N-WAY, Neuronaute IceCap.

The provided text describes the Neuronaute device, an electroencephalograph (EEG) system, and its substantial equivalence to a predicate device (AE-120A EEG Head Set, K183529) for FDA clearance. However, it does not contain a specific study demonstrating that the device meets numerically defined acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, accuracy for a particular condition). Instead, the submission focuses on demonstrating substantial equivalence through non-clinical performance testing against recognized standards.

Therefore, many of the requested items (e.g., sample size for test set, number of experts for ground truth, MRMC study, standalone performance) are not applicable or cannot be extracted from this document, as a clinical performance study with such metrics was not submitted.

Here's a breakdown of the information that can be extracted or inferred:

1. Table of Acceptance Criteria and Reported Device Performance

As a clinical performance study with specific diagnostic metrics (like sensitivity, specificity, or accuracy) was not submitted, there isn't a table of acceptance criteria for diagnostic performance against specific disease states. Instead, the acceptance is based on meeting technical and safety standards, and demonstrating signal quality, all of which are considered "performance" in this context.

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

• Sample Size (Test Set): Not applicable. No clinical performance testing with a patient test set was submitted for diagnostic accuracy. The testing performed was non-clinical (bench, software V&V, usability).
• Data Provenance: Not applicable. No clinical patient data was submitted for performance testing.

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

• Number of Experts: Not applicable. No clinical performance testing with expert-established ground truth was submitted.
• Qualifications of Experts: Not applicable.

4. Adjudication method for the test set

• Adjudication Method: Not applicable. No clinical performance testing requiring adjudication was submitted.

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

• MRMC Study: No. The device "Neuronaute" is an EEG data acquisition, display, storage, and transmission system. It is explicitly stated that "Neuronaute and its components do not provide any diagnostics conclusions or automated alerts of an adverse clinical event about a patient's clinical condition." Therefore, it does not include AI for diagnostic assistance, and an MRMC study comparing human readers with and without AI assistance is not relevant to this device's current claims.

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

• Standalone Performance: No. As noted above, the device does not provide diagnostic conclusions or automated alerts, implying no standalone diagnostic algorithm. Its primary function is to collect and transmit EEG signals for review by a physician.

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

• Type of Ground Truth: Not applicable for diagnostic performance. For the technical performance aspects (e.g., signal quality, electrical safety), the "ground truth" would be the specifications and requirements of the referenced industry standards (e.g., IEC 60601-2-26) or "EEG gold standards" referenced in the text.

8. The sample size for the training set

• Sample Size (Training Set): Not applicable. As the device does not provide diagnostic conclusions or automated alerts, it does not appear to involve a machine learning model that would require a patient-based training set for diagnostic classification.

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

• Ground Truth for Training Set: Not applicable. See explanation for #8.

Ask a specific question about this device