Jose Maria Perez-Macias

EEG Trends Analysis in Intensive Care Patients Project

snoring-project-image

Overview

This project involves creating software to analyze EEG trends in intensive care patients, assisting in better patient monitoring and care.

Background

Continuous EEG monitoring in ICU settings helps detect subtle changes in brain activity which can be critical for conditions like delayed cerebral ischemia post-subarachnoid hemorrhage.

Aim

To develop algorithms that can automatically detect and classify EEG trends indicative of neurological deterioration, thereby enhancing patient outcomes through timely intervention.

Methods

We employ two primary methods for EEG analysis:

Both methods use moving windows with overlapping to ensure continuous monitoring and alarm triggering for critical changes.

Results

Preliminary results indicate that these methods can effectively identify early signs of brain ischemia or other neurological disturbances, potentially improving patient management in ICU settings.

Resources

The project is supported by the following publications: