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)
| Registry | NCT07477028, acronym NeuroCogPresv |
|---|---|
| Status | Not yet recruiting |
| Study type | Observational |
| Enrollment | 20 (Estimated) |
| Sponsor | Noah Tech, Corp. (Industry); collaborators: Columbia University, Massachusetts Institute of Technology, Stanford University, City of Hope Medical Center |
| Conditions | Terminal Illness, End-of-Life Care, Death, Brain Death, Death Anxiety, Consciousness, Electroencephalography, Gamma Oscillations, Near-Death Phenomena, Cognitive, Cognition, Memory, EEG, Severe Acute Trauma |
| Dates | start 2026-09-01 (estimated), primary completion 2030-09-30 (estimated), completion 2035-09-30 (estimated), first posted 2026-03-17, last updated 2026-03-17 |
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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).
This prospective observational feasibility study will use non-invasive high-density EEG combined with a wireless brain-computer interface (BCI) and artificial intelligence analytics to detect, characterize, and archive neurocognitive signals in adult patients during the peri-death period. The study includes individuals with terminal illness or severe acute trauma who have a do-not-resuscitate (DNR/DNI) order. Building on recent human findings of gamma oscillation surges and cross-frequency coupling (Vicente et al., 2022; Xu et al., 2023), the study aims to quantify these signals, test AI-driven real-time classification, and explore technical feasibility for future signal preservation and continuity research. No therapeutic intervention is performed. All monitoring is conducted with surrogate consent under strict ethical oversight.
| Arm | Type | Interventions | Description |
|---|---|---|---|
| Peri-Death Cohort | Adults (≥18 years) with terminal illness or severe acute trauma who have a do-not-resuscitate (DNR/DNI) order and for whom surrogate informed consent has been obtained. Participants undergo continuous non-invasive high-density EEG monitoring using a wireless brain-computer interface (BCI) headset. Monitoring begins prior to expected clinical death and continues for up to 6 hours after cardiac arrest. This single prospective cohort is followed to characterize neurocognitive signals during the transition from clinical death through brain death to cellular death. No study intervention is administered. |
Sex: All, ages: 18 Years to any
Inclusion Criteria: 1. Adults ≥18 years with terminal illness or severe acute trauma 2. Do-not-resuscitate (DNR/DNI) order in place 3. Surrogate decision-maker available and willing to provide informed consent 4. Expected survival ≤7 days (physician estimate) Exclusion Criteria: 1. Brain death already declared > 24 hours prior to enrollment 2. Contraindication to EEG/BCI headset placement (e.g., severe scalp injury) 3. Patient lacks a legally authorized representative