Resting-state electroencephalogram relevance state recognition of Parkinson's disease based on dynamic weighted symbolic mutual information and k-means clustering / 生物医学工程学杂志

At present, the incidence of Parkinson's disease (PD) is gradually increasing. This seriously affects the quality of life of patients, and the burden of diagnosis and treatment is increasing. However, the disease is difficult to intervene in early stage as early monitoring means are limited. Aiming to find an effective biomarker of PD, this work extracted correlation between each pair of electroencephalogram (EEG) channels for each frequency band using weighted symbolic mutual information and k-means clustering. The results showed that State1 of Beta frequency band ( P = 0.034) and State5 of Gamma frequency band ( P = 0.010) could be used to differentiate health controls and off-medication Parkinson's disease patients. These findings indicated that there were significant differences in the resting channel-wise correlation states between PD patients and healthy subjects. However, no significant differences were found between PD-on and PD-off patients, and between PD-on patients and healthy controls. This may provide a clinical diagnosis reference for Parkinson's disease.

A study of brain inner tissue water molecule self-diffusion model based on Monte Carlo simulation / 生物医学工程学杂志

The study of water molecule self-diffusion process is of importance not only for getting anatomical information of brain inner tissue, but also for shedding light on the diffusion process of some medicine in brain tissue. In this paper, we summarized the self-diffusion model of water molecule in brain inner tissue, and calculated the self-diffusion coefficient based on Monte Carlo simulation under different conditions. The comparison between this result and that of Latour model showed that the two self-diffusion coefficients were getting closer when the diffusion time became longer, and that the Latour model was a long time-depended self-diffusion model.

Effects of Brain White Matter Anisotropic Conductivity on Distribution of EEG Calculated with Finite Element Method Based on Diffusion Tensor Image (DTI) of Nuclear Magnetic Resonance / 航天医学与医学工程

Objective To study the influence of white matter anisotropic conductivity on scalp electric potential distribution.Methods According to the volume constraint water diffusion tensor was converted to conductivity tensor,and the five-layer(white matter,grey matter,CSF,skull,scalp)finite element model(FEM)was constructed based on the DTI data.Based on this model first-order FEM algorithm was implemented.And the scalp electric potential distribution was calculated by using current dipole modal.Results Anisotropic conductivity of white matter has influence in EEG problem,and more influence when the ratio of radius and tangential of volume constraint is greater.The right-left dipoles have more influence than superior-inferior ones.Conclusion In the study of EEG,the anisotropic conductivity of brain tissue cannot be neglected.