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Correlate of Surface Electroencephalogram (EEG) With Implanted EEG Recordings (ECOG)

Correlate of Surface Electroencephalogram (EEG) With Implanted EEG Recordings (ECOG)

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03629743
Enrollment
20
Registered
2018-08-14
Start date
2019-11-11
Completion date
2026-08-09
Last updated
2026-08-11

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Anesthesia

Brief summary

Improve understanding of the correlation between surface EEG and implanted EEG recordings

Interventions

DEVICEEEG

EEG will be collected with Brain Product's VAMP-16 channel EEG Monitor using the accompanying software. (Website with further specifications and product details: https://www.brainproducts.com/productdetails.php?id=15)

DEVICEECOG

ECOG will be collected with Nihon Kohden acquisition System and accompanying software and depth electrodes.

Sponsors

Stanford University
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Male or Female subjects 18 years of age or older. * English or Spanish Speaking * Subjects who have been previously diagnosed with intractable epilepsy and require implantation of invasive electrophysiological recordings as part of their routine clinical presurgical workup.

Exclusion criteria

* Patients with skin abnormalities at the planned application sites that would interfere with sensor or electrode applications. * Patients with pre-existing conditions and/or co-morbidities that would prohibit them from participating in the study due to unacceptable risks to their health and well-being, as determined by the Principal Investigator (PI). * Patients who the PI deems ineligible at the PI's discretion * Pregnant patients

Design outcomes

Primary

MeasureTime frameDescription
Electrocardiogram (EEG) change before, during, and after anesthesia.Up to 48 hours. Specific time points are dependent on patient clinical events.Patient subjective level of consciousness during and after anesthesia administration will be assessed using response to verbal stimuli, response via button press, reported subjective level of consciousness, and/or response to memory tests (i.e. demonstration of explicit memory recall). Around loss and recovery of consciousness time points (e.g. induction or emergence from anesthesia or when patient falls asleep or wakes up during 24 hour postoperative time points) level of consciousness will be assessed in brief intervals (seconds) until patient no longer responds or begins to respond. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared.

Secondary

MeasureTime frameDescription
Electrocardiogram (EEG) change during any changes in consciousness.Up to 48 hours. Specific time points are dependent on patient clinical events.Scalp and cortical electrical activity collected using EEG and ECOG arrays respectively will be analyzed using standard frequency-derived measures (e.g. spectrograms, Fourier analysis), nonlinear dynamical analyses (e.g. correlation dimension, entropy), network dynamics (e.g. connectivity matrices, path length), and/or machine learning. These measures will include all of the data collected from the start of the implant procedure until 24 hours after the implant procedure has ended. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared. Reports will included characterization of electrophysiological activity before, during, and after variations in behavioral and subjectively reported consciousness.
Electrocardiogram (EEG) change during any seizures.Up to 48 hours. Specific time points are dependent on patient clinical events.Scalp and cortical electrical activity collected using EEG and ECOG arrays respectively will be analyzed using standard frequency-derived measures (e.g. spectrograms, Fourier analysis), nonlinear dynamical analyses (e.g. correlation dimension, entropy), network dynamics (e.g. connectivity matrices, path length), and/or machine learning. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared. Reports will include characterization and comparison of EEG and ECOG electrophysiological activity and analyses during consciousness transitions and significant time points.

Countries

United States

Contacts

PRINCIPAL_INVESTIGATORDavid Drover, MD

Stanford University

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Aug 12, 2026