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The REMI-AI Discrete Detection Module (REMI-AI DDM) is indicated for the analysis of REMI Remote EEG Monitoring System electroencephalogram (EEG) recordings. REMI-AI DDM is intended to be used by physicians qualified to analyze and interpret EEG who will exercise professional judgment in using the information.

As an aide to the qualified physician's REMI EEG review, REMI-AI DDM marks previously acquired sections of REMI EEG that may correspond to neurological events of interest indicative of potential electrographic seizures lasting at least 10 seconds in duration. REMI-AI DDM is indicated for use with adult and pediatric patients (6+ years).

REMI-AI DDM does not mark REMI EEG records in real time and does not provide any diagnostic conclusion about the patient's condition to the user.

REMI-Al Discrete Detection Module (REMI-AI DDM) is a software as a medical device (SaMD) that automatically identifies and annotates discrete seizure-like events in previously acquired electroencephalography (EEG) traces to aid a qualified physician in their review of REMI EEG records. REMI-AI DDM analyzes previously acquired EEG data from 4-channel recordings obtained from bilateral, bipolar scalp EEG recordings at both the frontal and temporoparietal regions, collected and stored by the REMI Remote EEG Monitoring System. REMI-AI DDM analyzes EEG recordings and detects regions of the data that may correspond to electrographic seizures lasting at least 10 seconds in duration. These regions are annotated in the REMI EEG file as discrete events and are provided to assist in REMI EEG review.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

1. Test Set Sample Size and Data Provenance:

   • Sample Size: 50 patient records (31 with consensus-determined electrographic seizures, 19 with no consensus-determined electrographic seizures). This included 87 consensus-determined electrographic seizures lasting at least 10 seconds.
   • Data Provenance: Not explicitly stated (e.g., country of origin). However, the data was collected from patients wearing REMI wireless EEG sensors alongside standard-of-care 19-channel, full-montage, video-EEG in Epilepsy Monitoring Units (EMUs) or during at-home ambulatory EEG monitoring. The study design suggests retrospective use of this collected data for validation.

2. Number of Experts and Qualifications for Ground Truth (Test Set):

   • Number of Experts: 3 independent expert epileptologists for panel review, selected from a panel of 6.
   • Qualifications: Holding certification by the American Board of Psychiatry and Neurology or certification by the American Board of Clinical Neurophysiology with Special Competency in Epilepsy Monitoring.

3. Adjudication Method for the Test Set:

   • Method: Consensus ground truth was established using 2 out of 3 (2+1, if referring to a single round of review among three) members identifying the presence or absence of an electrographic seizure event from the wired EEG records.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No, a MRMC comparative effectiveness study was not explicitly done or reported in the provided text to show the effect size of human readers improving with AI vs. without AI assistance. The clinical validation focuses on the standalone performance of the AI algorithm.

5. Standalone Performance (Algorithm Only):

   • Yes, a standalone (algorithm only without human-in-the-loop) performance study was done. The reported Event-Level Sensitivity and False Alarm Rate (FAR) are direct measures of the REMI-AI DDM algorithm's performance in identifying electrographic seizures.

6. Type of Ground Truth Used:

   • Expert Consensus: The ground truth for both training and validation was established through panel review by independent expert epileptologists based on standard 19+channel wired 10-20 montage EEG records acquired concurrently with the REMI 4-channel EEG.

7. Training Set Sample Size:

   • 108 patient records (73 seizure patients, 35 non-seizure patients).
   • This included a total of 562 electrographic seizures used for training.

8. How Ground Truth for Training Set Was Established:

   • Similar to the validation set, the ground truth for the training set was established by panel review of standard 19+channel wired 10-20 montage EEG records concurrently acquired with REMI 4-channel EEG. The same criteria of consensus (at least 2 of 3 experts) identifying the presence or absence of an electrographic seizure event would apply, as described in the "Clinical Reference" section for generating a reference standard for REMI-AI DDM.

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