Comparison of Modulations of Motor Brain Activity and SedLine After Median Nerve Stimulation in General Anesthesia

Summary

To this date, no monitoring device can reliably detect episodes of accidental awakening during general anesthesia. One promising approach is the use of electroencephalography (EEG) to detect movement attempts via a brain-computer interface (BCI). Previous work has shown that combining a BCI with painless median nerve stimulation can detect cerebral motor activity under light propofol sedation. However, clinical data are still lacking regarding the persistence or otherwise of a cerebral motor response (neural synchronization, or ERS) induced by this stimulation during general anesthesia.

In this new study, the aim is to simultaneously record the EEG centered on the motor cortex and the signal from the SedLine Patient State Index (PSI) to better characterize the evolution of cerebral motor activity before, during general anesthesia, and up to awakening. This approach will allow us to explore the complementarity of the two signals for future automated detection of residual states of consciousness during surgery.

Preliminary data from a previous protocol (STIM-MOTANA) allowed to develop an EEG classification algorithm based on Riemannian geometry, capable of inferring a patient's state of consciousness from cortical responses induced by median nerve stimulation.

The objective of this new study is also to compare the sensitivity of this algorithm with that of PSI, in order to assess its potential as a complementary - or even alternative - indicator of the level of consciousness under general anesthesia.

Investigators hypothesize that it is possible to detect, using EEG, specific brain signatures related to median nerve stimulation, including during propofol-induced general anesthesia. Specifically, neuronal desynchronization and resynchronization phases (ERD/ERS), well characterized in wakefulness or light sedation, could partially persist at higher propofol concentrations. Parallel PSI recording will allow analyzing to what extent these EEG modulations are related to classically measured levels of consciousness, and to validate the relevance of the new algorithm based on Riemannian geometry as a tool for detecting intra-operative arousals.

Conditions

• Accidental Awareness During General Anesthesia

Interventions

DEVICE

EEG Headset

64-electrode device (including 16 on the motor cortex), placed on the scalp. The EEG measurement is performed using OpenViBE software, in conjunction with an Eego amplifier (64 electrodes, ANT Neuro), both CE certified.

DEVICE

SD LTM STIM (Micromed)

Median nerve stimulation: applied to the right forearm using two ECG electrodes positioned at the wrist (palmar side), allowing painless transcutaneous stimulation (intensity 3 to 14 mA; pulse duration: 0.1 ms; frequency: 5 Hz). The stimulator used is a SD LTM STIM model (Micromed), CE certified.

DEVICE

SedLine®

Anesthetic depth monitoring: Performed using the SedLine® Brain Function Monitoring device (Masimo Corporation, model RDS7A, CE certified), using four forehead electrodes to record EEG activity. The Patient State Index (PSi), calculated in real time, is interpreted within a target range of 25 to 50 to ensure adequate general anesthesia. The device complies with international standards for electrical safety (IEC 60601) and hospital use.

Sponsors & Collaborators

• Brugmann University Hospital

  lead OTHER

Principal Investigators

• Seyed Javad Bidgoli, MD · CHU Brugmann

Study Design

Allocation

NA

Purpose

PREVENTION

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Min Age

18 Years

Max Age

81 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2025-10-27

Primary Completion

2026-12-31

Completion

2026-12-31

Countries

• Belgium

Study Locations