Analysis Of The EEG Of The MCS Patients Based On The Nonlinear Methods

Nowadays,the recovery of the consciousness of the patients with disorder of consciousness is a concern in the whole world.Because of the low requirements of the Electroencephalography(EEG)on the basic nerve function of the subjects,it is very suitable for the examination of the cerebral cortex function and the assessment of the consciousness state of the patients.In this paper,nonlinear EEG analysis was used to evaluate the consciousness of patients with disorder of consciousness and the effects of the spinal cord stimulation(SCS).Firstly,we introduced the acquisition and the pre-process of EEG signals of the patients with disorder of consciousness,and we compared the EEG signals of the patients with minimally conscious state(MCS)to normal state and vegetable state(VS).From the analysis of the neural oscillation and the energy distribution of the patients with MCS,we found that the EEG amplitude of the MCS was larger than VS but smaller than the normal state,and the density of the delta band in the signals was high but the high frequency energy was missing.Secondly,6 entropy methods were introduced in this paper and we proposed minRPE which is more simple and fast based on RPE.From the correlation analysis of the 7 entropy index with the coma recovery scale-revised points,we found that SampEn,minRPE and RPE had higher ability to evaluate the consciousness of patients with disorder of consciousness.In order to assist the selection of the clinical optimal parameter for SCS,the changes of the 7 entropy indicators between before and after the stimulation were statistically analyzed,and the statistical results were linked to the clinical situation to conclude that the optimal stimulation frequency was 70 Hz.In order to search the consciousness of the patients with MCS and the mechanism of SCS based on EEG,we used the fractal theory and the multifractal theory.To describe the fractal characteristics of the EEG signals of the patients,we proposed using DFA combined with surrogate data test to evaluate the long range temporal correlations of the EEG signals of patients with MCS.The results showed that the long-term memory was retained in the EEG of MCS,and this kind of memory was enhanced after SCS.The results of the multifractal spectrum and the multiple DFA showed that the low frequency components in the EEG of the patients were multifractal,and the multifractal features were more obvious after the surgical.Finally,three kinds of two-channel nonlinear algorithms(PCMI,xSample and PS)were used to analyze the EEG and construct the brain network for the MCS patients.The statistical results of the two-channel nonlinear algorithms showed that the communication between the adjacent channels of MCS patients was stronger and the communication between the distant channels was weaker;after receiving the SCS,the complexity of the interaction in the high-frequency signals between the channels was improved;the synchronization between the frontal,the parietal and the occipital regions was enhanced.The statistical results of the network parameters of the patient’s brain network indicated that the network of the patients developed to a more complex direction after SCS.