K-numberK251936
Device nameCeribell Delirium Monitor System
ApplicantCeribell, Inc.
Product codeNCG
Device classClass II
Decision dateDec 8, 2025
DecisionSubstantially Equivalent
Regulation882.1440
AI Summary extracted from FDA summary PDF · never regenerated
Intended use

The Ceribell Delirium Monitor System is an EEG-based software device that analyzes electroencephalogram patterns to aid clinicians in screening and monitoring delirium in adult patients in critical care hospital settings. It provides binary assessments (delirium suspected or not suspected) as an aid to clinical evaluation, not as a standalone diagnostic tool, and notifies clinicians of delirium-positive findings through audible or visible alerts.

Technological characteristics

Both the Ceribell device and its primary predicate (DeltaScan Monitor) use EEG acquisition hardware and software algorithms to extract specific neuropsychiatric features. The Ceribell Delirium Monitor differs in that it uses previously cleared EEG hardware (Pocket EEG Device K191301 and Instant EEG Headband K232052) and employs machine-learning-based algorithms to detect delirium features, whereas DeltaScan calculates a polymorphic delta index for acute encephalopathy. The Ceribell device also includes Wi-Fi connectivity to cloud-based servers for algorithm analysis.

Test standards cited

Not stated in this summary.

Substantial equivalence argument

The Ceribell Delirium Monitor is substantially equivalent to the DeltaScan Monitor predicate because both are prescription-only neuropsychiatric EEG assessment aids under 21 CFR 882.1440, both use EEG to aid diagnosis of a neuropsychiatric condition rather than provide standalone diagnosis, and both serve similar clinical functions despite targeting different conditions. Clinical performance testing demonstrated 81% sensitivity and 81% specificity with high repeatability (Cohen's kappa 0.76), showing the differences in EEG features analyzed and algorithm approach do not raise new safety or effectiveness questions.

Extracted by AI from the official FDA summary PDF →
Source

View the full FDA submission: accessdata.fda.gov

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