Development of classifier for anesthesia depth index using power spectrum analysis of EEG

Monitoring of depth of anesthesia is an ongoing problem in anesthesia. In this paper, using SEF, BDR, BTR parameters which is calculated by power spectral density. EEG data were obtained from 7 patients (ASA I, II) during general anesthesia with sevoflurane. The anesthetic depth evaluation index algorism was embodied to obtain a quantified index with the scale of 0~100. Then quantified index could be obtained from the patients under analysis: the average was 86.05, 36.98, 15.33 and 87.72 for the states of pre-operation, induction of anesthesia, operation and post-operation, respectively. The results show that when evaluating the depth of anesthesia, more quantified information can be provided for anesthesia doctors, rather than depending solely on their subjective evaluation, achieving the effect of establishing safer environment for surgery. Key-Words: classifier, anesthesia, depth of anesthesia, BDR, BTR, SEF