New EEG method predicts neurological recovery of cardiac arrest patients

The VTT Technical Research Centre in Finland is Northern Europe's biggest contract research organization and provides high-end technology solutions, often combining different technologies to create new innovations. One new breakthrough that's certain to be watched closely later this week will be that of VTT Research Scientist, Miikka Ermes (M.Sc., Eng.), who will publicly defend his doctoral thesis presenting methods for analysing human biosignals, including innovative methods for the verification of brain damage following cardiac arrest. Up until now, the use of electroencephalography (EEG) in the monitoring of cardiac patients has been limited due to interpretation difficulties.

A study conducted by a multi-disciplinary research team showed that variables derived from EEG traces can be used to predict neurological recovery even within the first 24 hours following cardiac arrest. The researchers derived variables from the EEG trace which simplified the interpretation process. The long-term goal of the team is to develop methods that allow continuous monitoring of neurological recovery at hospitals. This would allow the health care personnel to promptly respond to changes in the patient’s brain status. If blood circulation stops, the tissue in the patient’s body soon begins to suffer from reduced oxygen delivery. Brain cells are particularly sensitive to oxygen deprivation, which explains why even successfully resuscitated patients often sustain neurological damage. In its mildest form this is manifested as transient memory or movement disturbances; in the most serious cases, they can cause permanent unconsciousness. Basically, an electroencephalogram (EEG) records the electrical activity of the brain in the same way as an electrocardiogram (ECG) records heart activity. Interpreting EEG traces is more difficult, however, since unlike the electrical activity of a regularly beating heart, the electrical activity of the brain consists of irregular impulses generated by billions of brain cells. While the applicability of EEG in predicting neurological recovery has long been known, difficulties in interpreting the recordings have limited the routine use of EEG in patient monitoring. Interpretation almost invariably requires consulting a specialist, which may cause a delay in treatment. Miikka Ermes will publicly defend his doctoral thesis “Methods for the Classification of Biosignals Applied to the Detection of Epileptiform Waveforms and to the Recognition of Physical Activity” on Friday, 15 May 2009 starting at 12 noon. The public defence will take place in the Tietotalo Auditorium (room TB219) of the Tampere University of Technology (TUT), address: Korkeakoulunkatu 1, Tampere. Professor Georg Dorffner from the Medical University of Vienna (Austria) will act as the opponent. The doctoral thesis, which belongs to the field of signal processing, is available on the Internet here.