(24 days)
The Datex-Ohmeda S/5™ EEG module , E-EEG and the Datex-Ohmeda S/5™ EEG headbox, N-EEG and accessories are intended to be used with Datex-Ohmeda modular multiparameter monitors for monitoring neurophysiological status of hospitalized patients.
The Datex-Ohmeda S/5™ EEG module , E-EEG and the Datex-Ohmeda S/5™ EEG headbox, N-EEG and accessories are indicated for monitoring of electroencephalograph (EEG), frontal electromyograph (FEMG) and auditory evoked potentials (AEP) of all hospital patients. The device is indicated for use by qualified medical personnel only.
The Datex-Ohmeda S/5M EEG module, E-EEG is a single-width plug-in parameter module for a a Datex-Ohmeda modular monitoring system. The Datex-Ohmeda EEG module, E-EEG is for controlling the EEG, FEMG and AEP measurements in the N-EEG. The Datex-Ohmeda EEG headbox, N-EEG is a separate preamplifier and measurement unit for EEG, FEMG and AEP measurements. N-EEG can measure up to 4 real-time EEG waveform channels and an FEMG measurement from one channel. It can also measure AEP from two channels. The N-EEG can only be used with the Datex-Ohmeda EEG module, E-EEG.
The Datex-Ohmeda EEG module, E-EEG can be used with the following Datex-Ohmeda modular monitors:
S/5TM Anesthesia Monitor (AM) with main software S-ANE99(A) or L-ARK99(A) or newer S/5™ Compact Anesthesia Monitor (CAM) with main software S-ANE99(A) or L-ARK99(A) or newer
S/5TM Critical Care Monitor (CCM) with main software L-ICU99(A) or newer.
S/57M Compact Critical Care Monitor (CCCM) with main software L-ICU99(A) or newer. The raw EEG signal is displayed from all the monitored channels. The waveform size, color and sweep speed can be adjusted. Spectral analysis is performed on all of the measured EEG channels. Total power is calculated, and several parameters are calculated based on the power spectrum of the signal. The burst suppression pattern is detected, and suppression ratio is calculated. All the calculated parameters can be selected on the display, and trended. For auditory evoked potentials, the stimulation intensity and frequency can be set, and the number of averaged responses can be determined. The averaged AEP can be stored and markers can be set manually. Six sets of AEP's can be stored and printed. One of the saved responses can be selected as a reference on screen. Electrode impedance is measured automatically, when the electrodes are attached, and during monitoring at user-defined intervals. There are no alarms associated with the measurement, except for a message and an auditory beep for leads off situations. To simplify the patient connections, a series of preconfigured lead sets for different EEG measurements are available. The lead wires are connected together by a plastic piece, which has labels indicating where to attach which lead. The lead wire goes through the plug so that the connectors of the wire are visible from the other side to be plugged into the headbox. The lead set has an identification pin by which the monitor can automatically select the correct montage. There are 8 different lead sets, of which 3 are preconfigured and 5 are empty ones, for the user's own montages. The length of the leads is 0.60 m. The headphones for AEP monitoring are connected to a standard 3.5 mm stereo female plug in the headbox. The headphones supplied by Datex-Ohmeda generate the sound wave in a speaker, from where the pulse is transmitted to the ear through plastic tubes. Standard safety pin EEG leads and commercial headphones can also be used with the device.
The accessories are the same for the E- EEG module and the predicate device, the M- EEG (K000892).
The provided document is a 510(k) Premarket Notification for the Datex-Ohmeda S/5™ EEG Module, E-EEG and Headbox, N-EEG, and accessories. This submission is for a medical device seeking substantial equivalence to a predicate device, not for a new device requiring extensive clinical trials for performance validation. Therefore, the information typically requested regarding acceptance criteria, clinical study details, sample sizes, expert involvement, and ground truth establishment, as it pertains to AI/ML device performance, is not present in this type of regulatory document.
This document focuses on demonstrating that the new device is "substantially equivalent" to an already legally marketed device (the Datex-Ohmeda M-EEG Module, K000892) in terms of intended use, indications for use, fundamental technology, and safety/effectiveness, despite minor differences in physical appearance and electronic layout. The basis for substantial equivalence is primarily non-clinical testing against recognized standards.
Here's an analysis based on the information provided, highlighting why some requested details are absent:
1. A table of acceptance criteria and the reported device performance
The document does not provide a table of acceptance criteria in the sense of performance metrics (e.g., sensitivity, specificity, accuracy) for a diagnostic output, nor does it report device performance against such metrics. Instead, the "acceptance criteria" are implied by the comprehensive list of national and international standards against which the device was evaluated for safety and effectiveness.
-
Acceptance Criteria (Implied): Compliance with the following standards (among others listed):
- COUNCIL DIRECTIVE 93/42/EEC (Medical Devices)
- FDA/DCRND Reviewer Guidance for Premarket Notification Submissions, November 1993
- IEC 60601-1:1988 + Amdt. 1:1991 + Amdt. 2:1995 (General requirements for safety)
- EN 60601-1:1990+ A1:1993 + A13:1996 + A2:1995 (identical to IEC60601-1)
- CAN/CSA C22.2 No. 601.1-M90 + S1:1994 (Canadian deviations to IEC 60601-1)
- IEC 60601-1-2:2001 (Electromagnetic compatibility Requirements and tests)
- AAMI ESI-1993 (Safe current limits for electromedical apparatus)
- Electroencephalograph Devices Guidance for 510(k) Content, Draft Document Version 1.0, November 3, 1997
- FDA/ODE Guidance for Content of Premarket Submission for Software Contained in Medical Devices. (May 11, 2005)
- IEC 60601-2-26 Medical electrical equipment. Part 2: Particular requirements for the safety of electroencephalographs, 2002.
- ISO 14971 Ed. I: Medical devices Application of risk management to medical devices
- FDA Performance standard, 21 CFR Part 898.12
-
Reported Device Performance: The document states: "The device has been thoroughly tested through validation and verification of specifications." It concludes that the device is "substantially equivalent in safety and effectiveness" to the predicate device and that "there are no new questions of safety and effectiveness." Specific performance metrics are not provided.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
This information is not provided as this submission is based on non-clinical engineering and regulatory compliance testing rather than clinical study data with a "test set" of patient cases for performance evaluation. The testing involved compliance with electrical safety, EMC, software, and general medical device standards.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
This information is not applicable/not provided. The "ground truth" for this type of device, which is an EEG measurement module, would relate to accurate signal acquisition and processing capabilities, not interpretive diagnostic outputs requiring expert consensus. The validation focused on meeting technical specifications and regulatory standards.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not applicable/not provided for the reasons stated above.
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
This information is not applicable/not provided. This device is not an AI-assisted diagnostic tool. It is a measurement module for physiological signals (EEG, FEMG, AEP). Therefore, an MRMC study or AI-related effectiveness metrics are irrelevant to this submission.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not applicable/not provided. This device is hardware and associated software for signal measurement and display. It is used by "qualified medical personnel" for monitoring neurophysiological status. It is not a standalone algorithm performing a diagnostic task.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The concept of "ground truth" as it applies to diagnostic accuracy from expert interpretation is not relevant here. The ground truth for this device's validation would be the accurate measurement of electrical signals and adherence to technical specifications and safety standards. This would be established through engineering verification and validation, calibration, and standardized test procedures comparing device outputs to known inputs or reference standards.
8. The sample size for the training set
This information is not applicable/not provided. As this is not an AI/ML device, there is no "training set" in the context of machine learning model development.
9. How the ground truth for the training set was established
This information is not applicable/not provided for the same reason as point 8.
§ 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).