Application of Electroencephalogram Non-linear Analysis (review) / 中国康复理论与实践

@# Electroencephalogram non-linear analysis is one of the methods to study brain electric signal complexity and the mutual connection of signals based on the non-linearity principle and method. It can provide condition such as the neural networks function, contact information, the changing trajectory cerebrum function activity. It can be used for nerve spirit disease studying, the depth anaesthetize monitor ,the sleep studies in modern medicine, it breaks the ice in traditional Chinese medicine just now. The application of electroencephalogram non-linear analysis has open up an exhibition further to cerebrum's research.

Detrended Fluctuation Analysis on Sleep EEG of Healthy Subjects / 수면정신생리

INTRODUCTION: Detrended fluctuation analysis (DFA) is used as a way of studying nonlinearity of EEG. In this study, DFA is applied on sleep EEG of normal subjects to look into its nonlinearity in terms of EEG channels and sleep stages. METHOD: Twelve healthy young subjects (age: 23.8+/-2.5 years old, male:female=7:5) have undergone nocturnal polysomnography (nPSG). EEG from nPSG was classified in terms of its channels and sleep stages and was analyzed by DFA. Scaling exponents (SEs) yielded by DFA were compared using linear mixed model analysis. RESULTS: Scaling exponents (SEs) of sleep EEG were distributed around 1 showing long term temporal correlation and self-similarity. SE of C3 channel was bigger than that of O1 channel. As sleep stage progressed from stage 1 to slow wave sleep, SE increased accordingly. SE of stage REM sleep did not show significant difference when compared with that of stage 1 sleep. CONCLUSION: SEs of Normal sleep EEG showed nonlinear characteristic with scale-free fluctuation, long-range temporal correlation, self-similarity and self-organized criticality. SE from DFA differentiated sleep stages and EEG channels. It can be a useful tool in the research with sleep EEG.

Development of Algorithm for Estimation of Gestational Age using each Variable of Fetal Heart Rate / 대한산부인과학회잡지

OBJECTIVE: The objective of this study is to estimate gestational age by using FHR parameters after linear and nonlinear analysis of FHR data. Linear spectral decomposition has a limit to describe and analyze the nonlinear and complex physiological nature. Random processing and chaotic analysis assist to quantify some patterned energies, interaction of the physiological system in body system, which the constancy is preserved, and complexity of physical cardiovascular system. But there are no great development of new device which notify fetal age. METHODS: From March 1995 to December 2000, 2,548 cases who received NST during antenatal visit were included in this study. Among these cases, 1000 cases were sampled randomly. We divided this cases into a study and a control group, 500 cases for model building set and the other 500 cases for validation set. Each FHR parameters such as baseline FHR, variability (AMP, MMR), acceleration & deceleration (15 bpm-15 seconds), loss of signal, the number of fetal movement were analysed by using our own computerized HYFM-I, II software system. The linear and non-linear analysis of FHR were done after extracting approximate entropy (ApEn) value. Finally, we performed regression analysis and extract an equation for estimation of gestational weeks using bootstrap method. RESULTS: We extract a following equation using above study method: Log(GA)=5.870-0.051(Sloss*)-0.065(Mean FHR*)+0.049(Mean FHR*)2-0.058(FM*)+0.048(AMP*)2+0.121(A1515*)-0.031(A1515*)2+0.036(ApEn*)2. CONCLUSIONS: Accurate dating of pregnancy, namely gestational week is very important for antenatal diagnosis in the field of perinatal medicine. This study will propose scientific research results which are useful for studying normal and morbid generating physiological fetal condition. We extract an appropriate equation for estimation of gestational weeks only using FHR parameters. We hope to compare our result with other authors' results in the near future.

Development of Algorithm for Estimation of Gestational Age using each Variable of Fetal Heart Rate / 대한산부인과학회잡지

OBJECTIVE: The objective of this study is to estimate gestational age by using FHR parameters after linear and nonlinear analysis of FHR data. Linear spectral decomposition has a limit to describe and analyze the nonlinear and complex physiological nature. Random processing and chaotic analysis assist to quantify some patterned energies, interaction of the physiological system in body system, which the constancy is preserved, and complexity of physical cardiovascular system. But there are no great development of new device which notify fetal age. METHODS: From March 1995 to December 2000, 2,548 cases who received NST during antenatal visit were included in this study. Among these cases, 1000 cases were sampled randomly. We divided this cases into a study and a control group, 500 cases for model building set and the other 500 cases for validation set. Each FHR parameters such as baseline FHR, variability (AMP, MMR), acceleration & deceleration (15 bpm-15 seconds), loss of signal, the number of fetal movement were analysed by using our own computerized HYFM-I, II software system. The linear and non-linear analysis of FHR were done after extracting approximate entropy (ApEn) value. Finally, we performed regression analysis and extract an equation for estimation of gestational weeks using bootstrap method. RESULTS: We extract a following equation using above study method: Log(GA)=5.870-0.051(Sloss*)-0.065(Mean FHR*)+0.049(Mean FHR*)2-0.058(FM*)+0.048(AMP*)2+0.121(A1515*)-0.031(A1515*)2+0.036(ApEn*)2. CONCLUSIONS: Accurate dating of pregnancy, namely gestational week is very important for antenatal diagnosis in the field of perinatal medicine. This study will propose scientific research results which are useful for studying normal and morbid generating physiological fetal condition. We extract an appropriate equation for estimation of gestational weeks only using FHR parameters. We hope to compare our result with other authors' results in the near future.

Nonlinear Analysis of Electroencephalogram during the Course of Electroconvulsive Therapy: A Single Case Study / 신경정신의학

OBJECTIVES: In order to search for new parameters for the evaluation of the adequacy of electroconvulsive therapy (ECT) the authors performed a non-linear analysis of electroencepha-logram(EEG)recorded during the course of electroconvulsive therapy(ECT)in a single female patient with depression. METHODS: Digitized EEG recordings from two ECT sessions spaced one week were analyzed at five different stages; pretreatment stable, postanesthetic-preictal, ictal, postictal suppression and posttreatment stable stages. RESULTS: Our analysis showed that 1)EEG signals had low dimensional (below 10 dimensions) deterministic characteristics 2) although EEG was nonstationary signal, non-linear parameters could reliably differentiate between various stages we examined. 3)the deterministic property of ictal EEG increased according to the progression of sessions and 4)the primary Lyapunov exponent(PLE)and correlation dimension of pre- and post-treatment stable stage EEG increased according to the progression of sessions. CONCLUSION: In this single case study, results of various non-linear analyses suggested that non-linear variables extracted from EEG recordings during ECT may have utilities as tools for the quantitative evaluation of ECT.