[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"near-death-phenomena\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:near-death-phenomena":33},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":39,"overallStatus":50,"whyStopped":4,"lastUpdateSubmitDate":51,"lastUpdatePostDateStruct":52,"startDateStruct":55,"completionDateStruct":57,"leadSponsor":59,"locationsCount":4},"100629619","non-invasive-detection-and-preservation-of-neurocognitive-signals-in-the-peri-death-period-using-brain-computer-interface-and-artificial-intelligence-100629619",false,"NCT07477028","Non-Invasive Detection and Preservation of Neurocognitive Signals in the Peri-Death Period Using Brain-Computer Interface and Artificial Intelligence","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)","NeuroCogPresv","Inclusion Criteria:\n\n1. Adults ≥18 years with terminal illness or severe acute trauma\n2. Do-not-resuscitate (DNR\u002FDNI) order in place\n3. Surrogate decision-maker available and willing to provide informed consent\n4. Expected survival ≤7 days (physician estimate)\n\nExclusion Criteria:\n\n1. Brain death already declared \\> 24 hours prior to enrollment\n2. Contraindication to EEG\u002FBCI headset placement (e.g., severe scalp injury)\n3. Patient lacks a legally authorized representative","ALL","18 Years",{"count":20,"type":21},20,"ESTIMATED","OBSERVATIONAL","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.\n\nObjectives: (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.\n\nDesign: Prospective, open-label, multicenter, observational cohort (n\\>20).",[25,26,27,28,29,30,31,32,33,34,35,36,37,38],"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",[40,41,42,27,32,35,30,43,44,45,36,46,47,48,49],"AI","BCI","Brain Computer Interface","Pefi-death","Brain death","Reservation","Life","Life experience","Transfer","Convergence","NOT_YET_RECRUITING","2026-03-12",{"date":53,"type":54},"2026-03-17","ACTUAL",{"date":56,"type":21},"2026-09-01",{"date":58,"type":21},"2035-09-30",{"name":60,"class":61},"Noah Tech, Corp.","INDUSTRY"]