Study On Intracranial Pressure Detection Based On EEG Signals

Increased intracranial pressure is a serious pathological syndrome.If patients are not treated in time,there is a high probability of serious consequences such as disability or death.At present,invasive detection methods are commonly used to measure intracranial pressure.In the process of measurement,patients are prone to have a strong sense of pain and risk of bleeding or infection.However,the existing non-invasive detection methods based on flash visual evoked potential have some limitations,such as unreliable detection indicators and need subjective judgment.Therefore,there is an urgent need for a new non-invasive intracranial pressure detection method in clinic.In view of the above problems,this paper explores the feasibility of applying pattern reversal visual evoked potentials,steady state visual evoked potentials and resting EEG signals to intracranial pressure detection.The main work and innovation of this paper are as follows:?1?Data preprocessing.Discrete wavelet transform and bandpass zero phase delay filter are used to preprocess the collected data.A design method of zero phase delay filter for EEG signal based on convolution is proposed.Some details of the design of finite impulse response filter are discussed.?2?Design and validation of experimental paradigm.The experimental paradigms of pattern reversal visual evoked potentials and steady state visual evoked potentials were designed and implemented.Normal subjects were recruited for the experiment,and the validity of the experimental paradigm was verified by the analysis of the experimental results.?3?The validation of visual evoked potential in intracranial pressure detection.The temporal characteristics of pattern reversal visual evoked potentials were extracted by superposition averaging method.The phase characteristics of steady state visual evoked potentials are extracted by using band-pass Hilbert transform,and the influence of band-pass filter parameters on phase extraction is discussed.Patterns reversal visual evoked potentials and steady state visual evoked potentials were tested in patients.Through analysis,it was found that the experimental results were not good,and the two evoked potentials had no significant characteristics for the detection of intracranial pressure.?4?Intracranial pressure detection method based on resting EEG is proposed.Relative power spectra of resting EEG signals in normal group and patient group were analyzed and compared,and the frequency range of significant difference was determined.Brain network is constructed based on coherence coefficient,phase locked value and mutual information for EEG signals in significant difference frequency band.The patients were divided into high intracranial pressure group and low intracranial pressure group based on 180mmH₂O intracranial pressure.The clustering coefficients and global efficiency of the corresponding brain network topological parameters in normal group,high intracranial pressure group and low intracranial pressure group were analyzed.The results showed that compared with the normal group and the low intracranial pressure group,the topological parameters of the high intracranial pressure group decreased significantly.There was no significant difference in topological parameters between normal group and low intracranial pressure group.It is concluded that the significant difference is caused by elevated intracranial pressure rather than brain diseases.The parameters of brain network topology can reflect the level of intracranial pressure to a certain extent.?5?Classified detection of intracranial pressure based on resting EEG network topological parameters.The clustering coefficients and global efficiency calculated by the above-mentioned brain network are used as feature vectors to classify the patients with high and low intracranial pressure.The results show that the parameters of brain network topological characteristics based on resting EEG signal have good effect on the detection of intracranial pressure.This paper explores the feasibility of using EEG signal to detect intracranial pressure.The results show that the pattern reversal visual evoked potentials and steady-state visual evoked potentials based on screen stimulation have no significant effect on the detection of intracranial pressure,while the brain network constructed from resting EEG signals has significant characteristics,which can be used as an effective means for the detection of intracranial pressure and provide theoretical and technical reference for the study of non-destructive detection of intracranial pressure based on EEG signals.