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.

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

Adults (≥18 years) with terminal illness or severe acute trauma who have a do-not-resuscitate (DNR/DNI) order and for whom a legally authorized surrogate has provided informed consent. Participants are recruited from hospice, palliative care units, and intensive care units at three U.S. academic medical centers. The study focuses on individuals with physician-estimated survival of 7 days or less. All participants receive continuous non-invasive EEG/BCI monitoring during the peri-death period.

De-identified raw EEG data, AI-processed neurocognitive signal files, and limited demographic information will be made available to qualified researchers upon reasonable request. Data will be shared via a secure, public repository (e.g., Zenodo or NIH-compliant platform) to support future research on consciousness and neurocognitive activity in the peri-death period.

Data will become available beginning 12 months after the primary completion date and will remain available for a period of 5 years.

Qualified scientific researchers with an IRB-approved research proposal and relevant scientific background. All requests will be reviewed and approved by the study sponsor (NoahTech Corp.) and the responsible IRB. Access will be granted through a secure data-sharing platform after execution of a data use agreement.