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510(k) Data Aggregation
(101 days)
NeuroEEG is intended for prescription use to acquire, record, transmit, and display electrical brain activity of patients of all ages.
"NeuroEEG" is a 16-lead electroencephalograph. Electrodes correspond to the international 10-20 standard. It is a portable, non-sterile, non-invasive, non-radiation emitting electroencephalogram (EEG) device that works with a stationary PC with uninterruptible power supply (UPS) or a laptop with an internal battery. Signal transfer occurs between NeuroEEG and PC via wireless Bluetooth channel. The accompanying MemoryMD software runs on the Windows operating system (OS) Windows 8.1 and later. This device will be used "By Prescription" pursuant to 21 CFR 801 Subpart D. The medical use of data acquired by "NeuroEEG" is to be performed under the direction and interpretation of a licensed medical professional. This device does not provide any diagnostic conclusion about a subject's condition. The generated data serves as an assessment aid at medical practices, rehabilitation institutions, diagnostic centers, neurosurgical clinics, OR, ICU, ER, and clinical research institutes.
This is a 510(k) premarket notification for the NeuroEEG device, not a study report. Therefore, information regarding acceptance criteria and performance studies in the way you've requested is not typically found in this type of document. 510(k) submissions focus on demonstrating substantial equivalence to a predicate device.
However, based on the provided text, I can infer some aspects related to testing and "acceptance" in the context of a 510(k) submission:
1. Table of Acceptance Criteria and Reported Device Performance
The document doesn't provide a typical "acceptance criteria" table with specific quantitative thresholds that the device was tested against for clinical performance. Instead, it demonstrates compliance with recognized standards and successful completion of verification and validation activities.
Feature/Aspect Tested | Acceptance Criteria (Implied) | Reported Device Performance |
---|---|---|
Electrical Safety | Compliance with AAMI / ANSI ES60601-1:2005/(R)2012 And A1:2012, C1:2009/(R)2012 And . A2:2010/(R)2012 (Consolidated Text) | Full compliance |
Electromagnetic Compatibility (EMC) | Compliance with IEC 60601-1-2 Edition 4.0 2014-02 | Full compliance |
Usability | Compliance with IEC 60601-1-6 Edition 3.1 2013-10 | Passed tests |
Home Healthcare Environment | Compliance with IEC 60601-1-11 Edition 2.0 2015-01 | Passed tests |
Electroencephalograph Specific | Compliance with IEC 60601-2-26:2012 (Third Edition) | Passed tests |
FCC Compliance | Compliance with FCC Part 15: 2015 Subpart B | Passed tests |
Software Verification & Validation | Functions work as designed, performance requirements and specifications met, all hazard mitigations fully implemented, all testing met predetermined acceptance values. | Successfully performed; met predetermined acceptance values. |
Software Life Cycle Processes | Compliance with IEC 62304 Edition 1.1 2015-06 | Passed test |
Input Noise | Superior or equivalent to predicate device | Less than 2 uV (Predicate: 1.5uV at input) - Note: "Less than 2 uV" is effectively comparable for a 510(k) |
Common Mode Rejection Ratio | Superior or equivalent to predicate device | >110 dB (Predicate: >120 dB) - Note: "Similar performance" is the claim for 510(k), not necessarily superiority. |
2. Sample Size for Test Set and Data Provenance
The document does not provide information on a specific clinical "test set" for performance evaluation in terms of patient data. The testing mentioned primarily relates to hardware and software validation against technical standards. There is no mention of patient data, retrospective/prospective studies, or country of origin for such data.
3. Number of Experts and Qualifications for Ground Truth
This information is not provided as there is no specific clinical study described where expert ground truth was established for a test set. The submission focuses on technical compliance and substantial equivalence.
4. Adjudication Method
This information is not applicable/provided because no clinical test set requiring expert adjudication is described.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
An MRMC comparative effectiveness study was not conducted or described in this 510(k) submission. MRMC studies are typically done for diagnostic aids where human interpretation is involved, which this basic EEG acquisition device is not intended as a diagnostic tool itself but rather for data acquisition.
6. Standalone Performance Study
A standalone performance study in the sense of an algorithm-only without human-in-the-loop performance test for a diagnostic or interpretive algorithm was not conducted or described. The device, NeuroEEG, is an electroencephalograph—a medical device for acquiring and displaying physiological signals, not an interpretive algorithm. Its "standalone performance" refers to its ability to accurately acquire and transmit EEG signals according to technical specifications, which are addressed by the electrical safety and software verification/validation tests. The 510(k) summary explicitly states: "This device does not provide any diagnostic conclusion about a subject's condition."
7. Type of Ground Truth Used
The ground truth for the technical and software testing would be the specifications and requirements of the relevant industry standards (e.g., IEC, AAMI, FCC) and the device's own design specifications. For "performance" in the context of this 510(k), the "ground truth" demonstrated by testing is that the device correctly performs its intended function of acquiring, recording, transmitting, and displaying electrical brain activity in accordance with engineering and safety standards. There is no mention of pathology, outcomes data, or expert consensus on clinical diagnoses as ground truth.
8. Sample Size for Training Set
This information is not applicable/provided. The NeuroEEG is an EEG acquisition system and does not appear to involve machine learning models that would require a "training set" of data in the typical sense.
9. How Ground Truth for Training Set Was Established
This information is not applicable/provided as there is no mention of a training set for machine learning.
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