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Novel Methods for Measuring Depth of Anesthesia by Quantifying Dominant Information Flow in Multichannel EEGs
Kab-Mun Cha1, Byung-Moon Choi2, Gyu-Jeong Noh2
1Department of Electronic Engineering, Soongsil University, Seoul, Republic of Korea.
Computational Intelligence and Neuroscience
|April 15, 2017
Summary
This study introduces new methods to measure depth of anesthesia (DOA) using multichannel electroencephalography (EEG) by analyzing information flow across the entire brain. These novel techniques show high correlation with propofol levels in patients.
Area of Science:
- Neuroscience
- Anesthesiology
- Signal Processing
Background:
- Current depth of anesthesia (DOA) monitoring often relies on limited EEG channels, failing to capture widespread cerebral cortex function.
- Existing multichannel EEG studies for DOA are typically restricted to specific brain regions, limiting comprehensive assessment.
Purpose of the Study:
- To develop and validate novel methods for measuring depth of anesthesia (DOA) by quantifying dominant information flow in multichannel electroencephalograms (EEGs).
- To overcome the limitations of conventional methods by analyzing information flow across the entire cerebral cortex.
Main Methods:
- Proposed novel methods quantify dominant information flow in multichannel EEGs using principle bipartitioning.
- Three distinct bipartitioning techniques were employed to identify dominant information flow across all EEG channels.
- Information entropy was calculated to quantify the detected dominant information flow.
Main Results:
- Experimental results from clinical data of 39 subjects demonstrated a high correlation between the proposed DOA measures and plasma propofol concentration.
- The study successfully illustrated the performance of the novel methods using multichannel EEG data visualized on a 2D brain map.
Conclusions:
- The developed methods provide a more comprehensive approach to DOA measurement by considering information flow across wide brain regions.
- The findings suggest that quantifying dominant information flow in multichannel EEGs is a promising strategy for accurate depth of anesthesia monitoring.
