Monitoring the Brain in the Adult Icu

The electroencephalogram (EEG) is well-suited for continuous brain monitoring in neurological patients in the ICU, since the EEG is very sensitive for potential risks like ischemia and (non-convulsive) seizures [1]. However, to allow real-time computer assisted interpretation of the EEG, quantitative EEG (qEEG) and an adequate presentation of the data are required. This paper describes the implementation and initial evaluation of a system for real-time classification of EEG patterns based on a combination of qEEG features. The system must be able to classify the most common EEG patterns that are observed in adult neurological patients in the ICU: normal EEGs, iso-electric EEGs, low voltage EEGs, burst suppression patterns, hypofunctional EEGs (with focal or diffuse slowing), EEGs with generalized periodic discharges (GPDs) and EEGs with seizure activity. Creating such a system is a first step towards real-time, computer-assisted detection of seizure activity and ischemia in critically ill patients.