An adaptive Fourier estimation for automatic monitoring and analysis of EEG signal characters during anesthesia is described.The characteristic of evoked potential signals can be represented and traced with the Fourier coefficients,and the coefficients are classified with a neural network for estimating anesthetic depth.Computer simulation results show the validity of the method.
Key words
EEG analysis /
anesthetic depth /
Fourier estimation /
neural network
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] 吕国义,等.临床麻醉学[M].天津:天津科学技术出版社,1995.
[2] 杨福生,等编.生物医学信号处理[M].北京:高等教育出版社,1995
[3] 张海波,等.诱发脑电与麻醉深度[J].《国外医学》麻醉学与复苏分册.1993,14(2):68-69.
[4] Dierk Schwender,et al.Midlatency auditory evoked potentials predict movements during anesthesia with isoflurane or propofol [J].Anesth Analg.1997,85:164-173.
[5] C A Vaz,I N Bankman,N V Thakor.Evoked potential estimation using a Fourier series model [A].In proc.IX Ann.Conf.IEEE Eng.Med.Biol.Soc.[C],Boston.MA.1997:600-601.
[6] C A Vaz,N V Thakor.Adaptive fourier estimation of time-varying evoked potentials [J].IEEE Trans.On Biomedical Engineering.1989,36(4):448-455.
{{custom_fnGroup.title_en}}
Footnotes
{{custom_fn.content}}
PDF(695 KB)
