• Nadine Tupaika, Montserrat Vallverdu, Mathieu Jospin, Erik W Jensen, Michel M F Struys, Hugo E M Vereecke, Andreas Voss, and Pere Caminal.
• Dept. ESAII, Centre for Biomedical Engineering Research, Universitat Politècnica de Catalunya, CIBER of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain.
• Conf Proc IEEE Eng Med Biol Soc. 2010 Jan 1; 2010: 5971-4.

AbstractMethodologies based on symbolic dynamics have successfully demonstrated to reflect the nonlinear behavior of biological signals. In the present study, symbolic dynamics was applied to the electroencephalogram (EEG) in order to describe the level of depth of anesthesia. The EEG was transformed to symbol sequences. Words of three symbols were built from this symbolic series. The results obtained from the EEGs of 36 patients undergoing anesthesia showed that the probabilities of the word types were able to reflect the depth of anesthesia in a similar way to the auditory evoked potential index AAI, a commercial index.

15 keywords...

hide…