REMI-AI Rapid Detection Module (REMI-AI RDM)

K240408

Epitel, Inc · cleared 2024-10-17 · product code OMB · Neurology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“REMI-AI RDM conducts automated analysis of EEG data collected by the REMI System in near real-time.”
AlgorithmThe algorithm is trained to recognize seizure characteristics in EEG data.
source quote (p.5)
“REMI-AI RDM notifications identify when a section of EEG is consistent with seizure characteristics it has been trained to recognize. When a notification is presented, clinical context and facility procedures should inform next steps in patient evaluation and management. REMI-AI RDM does not make any treatment or management recommendations.”
Adaptive (vs locked)Yes
source quote (p.12)
“The REMI-AI RDM Authorized PCCP outlines authorized modifications intended to improve algorithm performance through expansion of the training data and/or through optimizations of the algorithm.”
PCCPYes
source quote (p.1)
“FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP).”
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

n=44 patients

endpoints: Sensitivity > 70%; False Alarm Rate (FAR) < 0.446 False Positives (FP)/hr

Reported performance (4 observations)

sensitivityas written: “Event-level Sensitivity (Pediatric)”91.2CI 80.0, 100.0
source quote (p.12)
“Event-level Sensitivity 91.2% 95% Confidence Interval 80.0, 100.0”
sensitivityas written: “Event-level Sensitivity (Adult)”85CI 68.0, 100.0
source quote (p.12)
“Event-level Sensitivity 85.0% 95% Confidence Interval 68.0, 100.0”
sensitivityas written: “Subject-level Sensitivity (Pediatric)”94.1CI 85.5, 100.0
source quote (p.12)
“Subject-level Sensitivity 94.1% 95% Confidence Interval 85.5, 100.0”
sensitivityas written: “Subject-level Sensitivity (Adult)”90.9CI 78.8 100.0
source quote (p.12)
“Subject-level Sensitivity 90.9% 95% Confidence Interval 78.8 100.0”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
-100%
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Neurology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K240408