title: A wavelet transform based method to determine depth of anesthesia to prevent awareness during general anesthesia.
abstract: Awareness during general anesthesia for its serious psychological effects on patients and some juristically problems for anesthetists has been an important challenge during past decades. Monitoring depth of anesthesia is a fundamental solution to this problem. The induction of anesthesia alters frequency and mean of amplitudes of the electroencephalogram (EEG), and its phase couplings. We analyzed EEG changes for phase coupling between delta and alpha subbands using a new algorithm for depth of general anesthesia measurement based on complex wavelet transform (CWT) in patients anesthetized by Propofol. Entropy and histogram of modulated signals were calculated by taking bispectral index (BIS) values as reference. Entropies corresponding to different BIS intervals using Mann-Whitney U test showed that they had different continuous distributions. The results demonstrated that there is a phase coupling between 3 and 4 Hz in delta and 8-9 Hz in alpha subbands and these changes are shown better at the channel T 7 of EEG. Moreover, when BIS values increase, the entropy value of modulated signal also increases and vice versa. In addition, measuring phase coupling between delta and alpha subbands of EEG signals through continuous CWT analysis reveals the depth of anesthesia level. As a result, awareness during anesthesia can be prevented.
authors.affiliation: Department of Biomedical Engineering, Urmia Medical Sciences University, Urmia, Iran.
authors.forename: Seyed Mortaza
authors.initials: SM
authors.lastname: Mousavi
authors.affiliation: Biomedical Engineering Department, Boğazici University, Istanbul, Turkey.
authors.forename: Ahmet
authors.initials: A
authors.lastname: Adamoğlu
authors.affiliation: Physiology Department, Faculty of Medicine, Istanbul University, Çapa Istanbul, Turkey.
authors.forename: Tamer
authors.initials: T
authors.lastname: Demiralp
authors.affiliation: Electrical Department, Faculty of Engineering, Urmia University, Urmia, Iran.
authors.forename: Mahrokh G
authors.initials: MG
authors.lastname: Shayesteh
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000758:Anesthesia / Q000379:methods*; D000768:Anesthesia, General / Q000379:methods*; D001921:Brain / Q000473:pathology; D004569:Electroencephalography / Q000379:methods; D019277:Entropy; D005260:Female; D006801:Humans; D058926:Intraoperative Awareness / Q000517:prevention & control*; D008875:Middle Aged; D016343:Monitoring, Intraoperative / Q000379:methods*; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D058067:Wavelet Analysis