ABSTRACT
The spectrum of EEG has been studied to predict the depth of anesthesia using variety of signal processing methods up to date. Those standard models have used the full spectrum of EEG signals together with the systolic-diastolic pressure and pulse values. As it is generally agreed today that the brain is in stable state and the delta-theta bands of the EEG spectrum remain active during anesthesia. Considering this background, two questions that motivates this paper. First, determining the amount of gas to be administered is whether feasable from the spectrum of EEG during the maintenance stage of surgical operations. Second, more specifically, the delta-theta bands of the EEG spectrum are whether sufficient alone for this aim. This research aims to answer these two questions together. Discrete wavelet transformation (DWT) and empirical mode decomposition (EMD) were applied to the EEG signals to extract delta-theta bands. The power density spectrum (PSD) values of target bands were presented as inputs to multi-layer perceptron (MLP) neural network (NN), which predicted the gas level. The present study has practical implications in terms of using less data, in an effective way and also saves time as well.
Subject(s)
Anesthetics, Inhalation/administration & dosage , Electroencephalography/methods , Methyl Ethers/administration & dosage , Neural Networks, Computer , Signal Processing, Computer-Assisted/instrumentation , Aged , Algorithms , Blood Pressure , Dose-Response Relationship, Drug , Female , Heart Rate , Humans , Male , Middle Aged , Pulse , Sevoflurane , Time Factors , Wavelet AnalysisABSTRACT
Computer assisted instruction in education, including biomedical engineering education, has been explored and changed dramatically for more than two decades. The Internet, with its capacity to transmit synchronous and asynchronous audio, text, and graphics, presents educators with tremendous opportunies for distance education and independent learning. In this work, we have developed a new educational hypermedia for medical instrumentation courses. It is designed to be suitable for biomedical and technical curricula where these courses are scheduled. The courseware provides support for the education of medical instrumentation. The work is presented herein to provide multimedia course material with animations to assist learning some key Medical Instrumentation topics on the World Wide Web.
