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Brain Injury Adjunctive Interpretive Electroencephalograph Assessment Aid
- Page Type
- Product Code
- A prescription device that uses a patient¿s electroencephalograph (EEG) to provide an interpretation of the structural condition of the patient¿s brain in the setting of trauma. The Brain Injury Adjunctive Interpretive EEG Assessment Aid is for use as an adjunct to standard clinical practice only as an assessment aid for a medical condition for which there exists other valid methods of diagnosis.
- Physical State
- Handheld EEG recording device, electrodes, and data analysis software
- Technical Method
- Software analysis of EEG signals
- Target Area
- Forehead, scalp
- Regulation Medical Specialty
- Review Panel
- Submission Type
- Device Classification
- Class 2
- Regulation Number
- GMP Exempt?
- Summary Malfunction Reporting
- Implanted Device
- Life-Sustain/Support Device
- Third Party Review
- Not Third Party Eligible
- MAUDE Alerts
- View and Sign Up For MAUDE Alerts
CFR § 882.1450 Brain injury adjunctive interpretive electroencephalograph assessment aid
§ 882.1450 Brain injury adjunctive interpretive electroencephalograph assessment aid.
(a) Identification. A brain injury adjunctive interpretive electroencephalograph assessment aid is a prescription device that uses a patient's electroencephalograph (EEG) to provide an interpretation of the structural condition of the patient's brain in the setting of trauma. A brain injury adjunctive interpretive EEG assessment aid is for use as an adjunct to standard clinical practice only as an assessment aid for a medical condition for which there exists other valid methods of diagnosis.
(b) Classification. Class II (special controls). The special controls for this device are:
(1) The technical parameters of the device, hardware and software, must be fully characterized and include the following information:
(i) Hardware specifications must be provided. Appropriate verification, validation, and hazard analysis must be performed.
(ii) Software, including any proprietary algorithm(s) used by the device to arrive at its interpretation of the patient's condition, must be described in detail in the software requirements specification (SRS) and software design specification (SDS). Appropriate software verification, validation, and hazard analysis must be performed.
(2) The device parts that contact the patient must be demonstrated to be biocompatible.
(3) The device must be designed and tested for electrical safety, electromagnetic compatibility (EMC), thermal, and mechanical safety.
(4) Clinical performance testing must demonstrate the accuracy, precision-repeatability and reproducibility, of determining the EEG-based interpretation, including any specified equivocal zones (cutoffs).
(5) Clinical performance testing must demonstrate the ability of the device to function as an assessment aid for the medical condition for which the device is indicated. Performance measures must demonstrate device performance characteristics per the intended use in the intended use environment. Performance measurements must include sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with respect to the study prevalence per the device intended use.
(6) The device design must include safeguards to ensure appropriate clinical interpretation of the device output (e.g., use in appropriate patient population, or for appropriate clinical decision).
(7) The labeling and training information must include:
(i) A warning that the device is not to be used as a stand-alone diagnostic.
(ii) A detailed summary of the clinical performance testing, including any adverse events and complications.
(iii) The intended use population and the intended use environment.
(iv) Any instructions technicians should convey to patients regarding the collection of EEG data.
(v) Information allowing clinicians to gauge clinical risk associated with integrating the EEG interpretive assessment aid into their diagnostic pathway.
(vi) Information allowing clinicians to understand how to integrate the device output into their diagnostic pathway when the device is unable to provide a classification or final result.
[80 FR 16268, Mar. 27, 2015]