ABSTRACT
BACKGROUND: Monitoring the "depth of anesthesia" is an ongoing problem. To identify a useful parameter for determining the depth of anesthesia with enflurane, EEG data was obtained using a Physiolab 800. METHODS: Variations in EEG signals were measured and analyzed by the stage of anesthesia. EEG data was obtained from 15 patients during general anesthesia with enflurane. The EEG signal was acquired and analyzed in 5 steps (one day before anesthesia, during induction, during skin incision, at end of anesthesia, and one day after anesthesia). Fp1 electrode and the EEG data mainly from the forehead were used to determine the depth of anesthesia using EEG characteristics during enflurane anesthesia. All data were preprocessed by filtering, baseline correction and using the linear detrend method to reliable analyze of sample data in the surgical environment. Data obtained were transformed to frequency and power spectrum analysis was performed. RESULTS: alpha, beta, delta and theta waves were detected by frequency area separation and the trend of each wave was observed during each anesthesia stage. EEG data was slowed down and the theta wave ratio increased as the depth of anesthesia increased. Accordingly, spectral edge frequency (SEF) and median frequency (MF) were used as parameters to determine the depth of anesthesia. The frequencies of SEF and MF decreased during anesthesia and returned to the preanesthetic level after the cessation of anesthesia. CONCLUSIONS: Our results suggest that SEF and MF can contribute as useful parameters to determine the depth of anesthesia. Anesthetics not only affect the central nervous system, but also affect the autonomic nervous system. If the autonomic nervous system signals such as heart rate variability are taken into account, more reliable evaluations would be possible.