Automatic detection and analysis of the EEG Sharp Wave-Slow Wave patterns evoked by fluorinated inhalation anesthetics

作者：Olejarczyk Elzbieta^*; Jozwik Adam; Zmyslowski Wojciech; Sobieszek Aleksander; Marciniak Radoslaw; Byrczek Tomasz; Jalowiecki Przemyslaw; Bem Tiaza

来源：Clinical Neurophysiology, 2012, 123(8): 1512-1522.

DOI：10.1016/j.clinph.2011.12.017

• EEG
• Fluorinated inhalation anesthetics
• Volatile anesthesia
• Sharp Wave-Slow Wave patterns
• k-NN classifier

Objective: The aim of this study was to develop a method for the automatic detection of Sharp Wave-Slow Wave (SWSW) patterns evoked in EEG by volatile anesthetics and to identify the patterns%26apos; characteristics. %26lt;br%26gt;Methods: The proposed method consisted in the k-NN classification with a reference set obtained using expert knowledge, the morphology of the EEG patterns and the condition for their synchronization. The decision rules were constructed and evaluated using 24 h EEG records in ten patients. %26lt;br%26gt;Results: The sensitivity, specificity and selectivity of the method were 0.88 +/- 0.10, 0.81 +/- 0.13 and 0.42 +/- 0.16, respectively. SWSW patterns%26apos; recruitment was strictly dependent on anesthetic concentration. SWSW patterns evoked by different types of anesthetics expressed different characteristics. %26lt;br%26gt;Conclusions: Synchronization criterion and adequately selected morphological features of %26quot;slow wave%26quot; were sufficient to achieve the high sensitivity and specificity of the method. %26lt;br%26gt;Significance: The monitoring of SWSW patterns is important in view of possible side effects of volatile anesthetics. The analysis of SWSW patterns%26apos; recruitment and morphology could be helpful in the diagnosis of the anesthesia effects on the CNS.

• 出版日期2012-8