The Research On Characteristics Analysis And Propagation Law Of Low Frequency Oscillation Signals In Patients With Ischemic Stroke

Stroke has become the leading cause of death among Chinese residents.The prevalence rate has increased year by year.Among them,ischemic stroke accounts for 60% to 80% of the proportion obstacle.Various susceptibility factors cause cerebral artery stenosis or occlusion,resulting in acute cerebral circulation disorder.Early identification and prevention are urgent.Low frequency oscillation signal,the frequency range is 0.01~0.15 Hz,It is a spontaneous slow-changing signal in hemodynamic parameters that is independent of heartbeat and respiratory signals and can be used as a biomarker for monitoring circulatory dysfunction.Researchers have explored the law of low frequency oscillation signal transmission in healthy human body.However,it is unclear how the LFO signal is transmitted in patients with blood circulation disorder in ischemic stroke.In view of this problem,this paper conducts an in-depth study on the characteristics of peripheral LFO signal transmission in ischemic stroke patients.Firstly,based on the near-infrared spectroscopy technique,a data acquisition experiment under resting state was designed for the acquisition of peripheral low-frequency oscillation signals in ischemic stroke patients.For the noise generated during the acquisition process,according to the nonlinear and non-steady-state characteristics of the low-frequency oscillation signal,a new method for removing physiological noise and motion artifact noise is proposed.The algorithm based on spline interpolation and wavelet kurtosis filter is combined.And compared with the empirical modal decomposition algorithm.Secondly,for the problem of how low-frequency oscillating signals are propagation in patients with ischemic stroke,time-frequency analysis,correlation and time delay analysis methods were used to calculate the time delay and correlation coefficient of low-frequency oscillation signals between peripheral regions(ear,finger and toe).By analyzing the time delay between each position,the difference of low-frequency oscillation signal propagation characteristics between healthy people and ischemic stroke patients was compared.According to the characteristics of ischemic stroke and healthy people,four typical machine learning algorithms were used for classification.Finally,based on the physiological basis of ischemic stroke blood circulation.Timefrequency analysis,correlation and time delay characteristics were used to explore different causes(lower extremity arterial stenosis,internal carotid artery stenosis,external carotid artery stenosis)and different infarction sites(The propagation of low frequency oscillating signals under the left and right sides).Combined with patient pathology,the reasons for this rule were analyzed.