Clinical trials

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 study aims to evaluate the efficacy of community-based early detection and targeted interventions, including stem cell therapy and wearable non-invasive brain-computer interface (BCI) devices, for Mild Cognitive Impairment (MCI) in adults aged 55 years and older residing in U.S. urban and suburban communities. Primary objectives include assessing improvements in MCI detection rates, cognitive outcomes, and progression delay compared to standard care.