(112 days)
The neo monitor is an 8-channel electroencephalograph (EEG) acquisition software. The device is intended to record and display EEG and aEEG signals for monitoring the brain status of neonatal patients (defined as from birth to 28 days postdelivery, and corresponding to a postconceptual age of 24 to 46 weeks). The device is to be used in a hospital environment by qualified clinical practitioners. The device does not provide any diagnostic conclusion about the patient's condition to the user.
The nëo™ system is a reduced montage neonatal electroencephalograph device that acquires, displays, stores, and archives electroencephalographic signals from the brain. By application of electrodes at specific location on the cranium,using up to 10 surface electrodes placed at specific locations the system functions to measure and record electrical activity of the brain by acquisition of electroencephalograph data and amplitude-integrated electroencephalograph (electroencephalograph signals that have been filtered and displayed in a specific manner).
The neo System is an electromedical device incorporating software. The device itself has no patient contact, but is intended for use with FDA-cleared ECG electrodes. nëo™ Monitor software, which, when installed into a compatible touchscreen PC and paired with a physiological signal amplifier (eego model EE-411) forms the nëo™ Monitor System. The system is a compact and easy-to-use and can be set on a bedside table, pole-mounted, or on a cart in the neonatal care areas.
The system, as-delivered to the customer, is comprised of:
- nëo Monitor software (pre-installed)
- 15" Panel PC
- eego EE-411 model amplifier
- Mounting plate
- nëo User Manual .
Here's a breakdown of the acceptance criteria and study information for the nëo Monitor System, based on the provided FDA 510(k) summary:
1. Table of Acceptance Criteria and Reported Device Performance
The provided document primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting specific performance metrics against pre-defined acceptance criteria for the entire device. Instead, it compares the technological characteristics of the nëo Monitor System to its predicate, the Olympic Brainz Monitor.
The table below summarizes the technical specifications compared, which implicitly serve as acceptance criteria for functionality. It also includes the performance for the burst suppression detection software, which is a key differentiating feature with its own implicit performance.
| Feature | Acceptance Criteria (based on Predicate/Standard) | nëo™ Monitor System Reported Performance |
|---|---|---|
| Reduced montage EEG | Yes (comparable to predicate) | Yes |
| Amplitude integrated electroencephalograph | Yes (comparable to predicate) | Yes |
| Burst suppression detection software | Indication of burst suppression detection capability (compared to another predicate, Background Pattern Classification software (BPc) by Natus Medical (K152301), and the Olympic Brainz Monitor which does not have this feature) | Burst suppression ratio (BSR) |
| Inter burst Interval (IBI) | ||
| Target population | Neonates | Neonates |
| Use environment | Neonatal care areas / NICU/research | neonatal care areas |
| Number of channels | 3 max (Predicate) | 8 max |
| Sampling rate | 2000 Hz (Predicate) | 512 Hz |
| Sampling resolution | 16 bits @2000 Hz (Predicate) | 24 bit |
| Input impedance | >50MΩ (Predicate) | >1 GΩ |
| Bandwidth | 0.5Hz ~ 450Hz (Predicate) | 0Hz -128Hz |
| Noise in bandwidth | 100kOhm) and non-physiological data (saturated channel, strong drift, and strong hum noise) | |
| Basic Safety & Essential Performance | Compliance with IEC 60601-1, IEC 60601-2-26 | Device has been developed and tested to IEC 60601-1, IEC 60601-2-26, IEC 60601-1-2, IEC 62304, ISO 14971. (This implies performance meets the requirements of these standards, though specific data is not detailed in this summary). |
2. Sample Size Used for the Test Set and Data Provenance
The provided 510(k) summary does not detail a clinical study with a specific test set, sample size, or data provenance (e.g., country of origin, retrospective/prospective data for clinical validation). The submission relies on non-clinical testing against recognized standards and a comparison of technological characteristics to a predicate device.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
Since a clinical test set for performance validation (beyond technical specifications) is not described, there is no information on:
- The number of experts used.
- The qualifications of those experts.
4. Adjudication Method for the Test Set
As no specific clinical test set for performance evaluation is described, there is no information on any adjudication method.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No MRMC comparative effectiveness study is mentioned in the provided document. The focus is on demonstrating substantial equivalence based on technical specifications and non-clinical testing, not on human reader performance with or without AI assistance.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
For the specific functions like aEEG signal processing and burst suppression detection, the document describes the algorithms and their technical specifications (e.g., aEEG filter specification, presence of BSR/IBI). The fact that these are listed as device features implies standalone algorithm functionality. However, a formal "standalone performance study" with specific metrics (e.g., sensitivity, specificity for burst detection against a human-annotated ground truth) is not detailed in this document. The comparison is largely at a functional and technical specification level.
7. The Type of Ground Truth Used
For the technical specifications, the ground truth is implicitly defined by:
- Engineering specifications and test methodologies for electrical performance (e.g., sampling rate, resolution, noise, impedance).
- Standardized test signals (e.g., sine wave inputs for aEEG filter specification).
- Reference standards like IEC 60601-1, IEC 60601-2-26, etc. for safety and essential performance.
There is no mention of expert consensus, pathology, or outcomes data being used as ground truth for a clinical validation study in this summary.
8. The Sample Size for the Training Set
The document does not mention any training set size as it concerns hardware/software specifications and regulatory compliance rather than an AI/machine learning model whose performance on classification/detection tasks is being clinically validated against a dataset. While the burst suppression detection software might involve algorithms, the document doesn't delve into its development data.
9. How the Ground Truth for the Training Set Was Established
Since no training set is described, no information is provided on how its ground truth might have been established.
§ 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).