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Non-Invasive Detection and Preservation of Neurocognitive Signals in the Peri-Death Period Using Brain-Computer Interface and Artificial Intelligence
Sponsor: Noah Tech, Corp.
Summary
Background: Recent electroencephalography (EEG) data indicate that the transition from clinical death to cellular death is marked by highly organized neurophysiological events, including significant surges in gamma-band power, cross-frequency coupling, and distinct spreading depolarization waves. This prospective, observational feasibility study utilizes rapid-deployment, high-density, noninvasive BCI hardware paired with proprietary AI analytics to detect, classify, and securely archive these terminal neurocognitive signals. Objectives: (1) Quantify transient gamma-band activity and cross-frequency connectivity post-clinical death; (2) Validate the efficacy of machine learning models for real-time signal classification in high-noise clinical environments; (3) Establish a highly secure, encrypted bio-informational archive of peri-life EEG data. Design: Prospective, open-label, multicenter, observational cohort (n\>20).
Official title: Feasibility of Non-Invasive Detection and Preservation of Neurocognitive Signals in the Peri-Death Period Using Brain-Computer Interface and Artificial Intelligence: A Prospective Observational Study (NeuroCogPresv)
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
20
Start Date
2026-09-01
Completion Date
2035-09-30
Last Updated
2026-03-17
Healthy Volunteers
No