(86 days)
The Neuroscan SynAmps2 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 qualified physicians.
The SynAmps2® Amplifier System is an EEG/ERP/EP amplifier and data acquisition system. The amplifier and data acquisition electronics are housed in a small enclosure (Headbox) placed near the patient, and into which individual electrodes, 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 a USB 2.0 interface. Data flows from the SynAmps2 amplifier over this interface. Multiple System Units may be connected to the host, to obtain systems of up to 512 channels.
This device, the Neuroscan SynAmps2, is an Electroencephalograph (EEG) system and the provided text does not include a study or acceptance criteria in the traditional sense of evaluating an AI model's performance.
The document is a 510(k) summary for a medical device (SynAmps2) that functions as an EEG/ERP/EP amplifier and data acquisition system. The primary goal of a 510(k) submission is to demonstrate substantial equivalence to a legally marketed predicate device, not necessarily to prove specific performance metrics against pre-defined acceptance criteria through a study as would be typical for an AI/ML diagnostic device.
Therefore, many of the requested items (e.g., sample sizes for test/training, number of experts, adjudication methods, MRMC studies, standalone performance, ground truth types) are not applicable or extractable from this document as these relate to the performance evaluation of a diagnostic or AI algorithm, not an EEG hardware system's substantial equivalence.
Here's an analysis of the provided information in the context of the request, highlighting what is (and isn't) present:
1. A table of acceptance criteria and the reported device performance
- Acceptance Criteria: Not explicitly stated in the document in terms of performance metrics for a diagnostic output. The "acceptance criteria" for a 510(k) submission for this type of device is demonstrating substantial equivalence to a predicate device (SynAmps, K001324). This typically involves comparing technical specifications, intended use, and safety aspects.
- Reported Device Performance: The document describes the functionality of the SynAmps2 (EEG/ERP/EP amplifier and data acquisition system, up to 512 channels, USB 2.0 interface) and states its intended use (measuring and recording electrical activity of the brain to aid in monitoring and diagnosis). Specific performance metrics like accuracy, sensitivity, or specificity are not provided as this is a hardware device for data acquisition, not an interpretive or diagnostic AI software.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Not applicable. This is a 510(k) submission for a hardware device, not an AI/ML algorithm requiring a test set for performance evaluation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable. No ground truth establishment for a test set is discussed. The device is for acquiring data that would then be interpreted by qualified physicians.
4. Adjudication method for the test set
- Not applicable.
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
- Not applicable. No MRMC study or AI assistance is mentioned.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable. This is a hardware acquisition system, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable. The device acquires raw EEG data; the "ground truth" for diagnosis would be established by a qualified physician interpreting the acquired data.
8. The sample size for the training set
- Not applicable.
9. How the ground truth for the training set was established
- Not applicable.
Summary relevant to the provided document:
The provided document details a 510(k) premarket notification for the Neuroscan SynAmps2, an Electroencephalograph (EEG) system. The core of this submission is to demonstrate substantial equivalence to an existing predicate device (SynAmps, K001324). This involves comparing the new device's technical characteristics, safety, and intended use against the predicate, rather than conducting a clinical study to prove diagnostic performance against specific acceptance criteria for an AI model.
The "acceptance" by the FDA, as indicated by the letter, means they determined the device is substantially equivalent to the predicate, allowing it to be marketed. This is different from meeting performance acceptance criteria from a study for an AI-powered diagnostic device.
§ 882.1400 Electroencephalograph.
(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).