(30 days)
The SignalNED Device is intended to record and display Quantitative EEG (qEEG) (relative band power, e.g., alpha, beta, delta, theta), which is intended to help the user analyze the EEG. The SignalNED does not provide any diagnostic conclusion about the patient's condition. The device is intended to be used on adults by qualified medical and clinical professionals.
The SignalNED is intended to be used in a professional healthcare environment.
The SignalNED Model RE machine uses 10 patient electrodes (4 left, 4 right, 2 midh are used to form the 8 channels. The SignalNED machine requires the use of the SignalNED Sensor Cap, and the system includes the following components:
- Portable EEG machine (Device)
- I Battery & External Battery Charger
- I SignalNED Sensor Cap
- I SignalNED Sensor Cap Cable
The primary function of the SignalNED Model RE is to rapidly record EEG and derive the Quantitative EEG (qEEG) measurement of Relative Band Power for multiple bands (e.g., alpha, beta, theta) at each electrode. These measurements are intended to help the user analyze the underlying EEG. The SignalNED Model RE (client) achieves its intended without relying on wireless comectivity. The SignalNED RE does not provide any diagnostic conclusion about the patient's condition.
This summary describes the acceptance criteria and the study that proves the SignalNED System (Model RE) meets those criteria, based on the provided FDA 510(k) summary.
1. Table of Acceptance Criteria and Reported Device Performance
| Test | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Lead Off Detection | Ability to detect disconnected electrodes. | All testing passed acceptance criteria. |
| Signal Acquisition Noise Levels | Acceptable noise levels in signal acquisition. | All testing passed acceptance criteria. |
| Software ADC Conversion Accuracy | Accuracy of software in Analog-to-Digital Converter (ADC) conversion. | All testing passed acceptance criteria. |
| Quantitative Electroencephalogram (QEEG) | Accuracy of the QEEG Relative Band Power calculation. | All testing passed acceptance criteria. |
| EC12:2020 Electrical Performance | Compliance with EC12:2020 electrical standards. | All testing passed acceptance criteria. |
| Essential Performance Tests (IEC 80601-2-26) | Compliance with IEC 80601-2-26 essential performance requirements. | All testing passed acceptance criteria. |
| Electrical Performance (IEC 60601-1, IEC 60601-1-2) | Compliance with IEC 60601-1 and IEC 60601-1-2. | All testing passed. |
| Biocompatibility (ISO 10993-1, -5, -10, -23) | Compliance with ISO 10993 for Cytotoxicity, Sensitization, and Irritation (for limited contact, intact skin). | All testing passed. |
2. Sample Size Used for the Test Set and Data Provenance
The provided document does not specify the sample sizes (e.g., number of subjects, number of EEG recordings) used for the non-clinical performance testing. It only states that "All testing passed acceptance criteria and details are contained in the test report." The data provenance (e.g., country of origin, retrospective or prospective) is also not detailed in this summary.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
The provided document describes non-clinical performance testing (lead-off detection, noise levels, ADC accuracy, QEEG calculation accuracy, electrical performance, biocompatibility). These tests do not typically involve human experts establishing ground truth in the way a clinical study for diagnostic accuracy would. The ground truth for these tests would be established through defined technical specifications, measurement standards, and validated testing protocols. Therefore, information about the number and qualifications of experts for establishing ground truth is not applicable in this context.
4. Adjudication Method for the Test Set
As the performance testing described is non-clinical and based on technical specifications and standards, an adjudication method (like 2+1 or 3+1) used in clinical studies for discrepancies in expert readings is not applicable here. The acceptance criteria for each test inherently define the "ground truth" to which the device's performance is compared.
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
A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned or described in the provided document. The SignalNED System is intended to record and display QEEG, which "is intended to help the user analyze the EEG." It explicitly states, "The SignalNED does not provide any diagnostic conclusion about the patient's condition." This indicates that the device is a tool for professional analysis rather than an AI-driven diagnostic aid for human readers. Therefore, an MRMC study comparing human readers with and without AI assistance is not described.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
The document describes several standalone performance tests for the device's components and calculations (e.g., Lead Off Detection, Signal Acquisition Noise Levels, Software ADC Conversion Accuracy, Quantitative Electroencephalogram (QEEG) accuracy). These tests are conducted on the algorithm and hardware without human interpretation as part of the primary outcome assessment. For instance, the "Software ADC Conversion Accuracy" and "Quantitative Electroencephalogram (QEEG)" accuracy tests evaluate the algorithm's performance in generating calculated EEG measures.
7. The Type of Ground Truth Used
The ground truth used for the reported performance tests is based on:
- Defined Technical Specifications and Engineering Standards: For tests like Lead Off Detection, Signal Acquisition Noise Levels, Software ADC Conversion Accuracy, EC12:2020 Electrical Performance, and Essential Performance Tests (IEC 80601-2-26).
- Validated Calculation Methods: For the Quantitative Electroencephalogram (QEEG) Relative Band Power calculation, the ground truth would be based on established mathematical and signal processing principles for deriving these metrics from raw EEG data.
- International Biocompatibility Standards: For ISO 10993 series tests (Cytotoxicity, Sensitization, Irritation).
8. The Sample Size for the Training Set
The provided document describes performance testing for substantial equivalence, not the development or validation of a machine learning model with distinct training and test sets in the typical sense. While the device calculates QEEG, the details on how the underlying algorithms were developed or "trained" (if machine learning is involved beyond standard signal processing) are not provided. Therefore, a specific sample size for a "training set" is not mentioned.
9. How the Ground Truth for the Training Set Was Established
As information about a distinct "training set" for machine learning algorithms is not provided, the method for establishing ground truth for such a set is also not described. The document focuses on performance testing against established engineering, electrical, and biocompatibility standards.
§ 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).