Multi-modal synergistic quantitative analysis and rehabilitation assessment of lower limbs for exoskeleton / 生物医学工程学杂志

In response to the problem that the traditional lower limb rehabilitation scale assessment method is time-consuming and difficult to use in exoskeleton rehabilitation training, this paper proposes a quantitative assessment method for lower limb walking ability based on lower limb exoskeleton robot training with multimodal synergistic information fusion. The method significantly improves the efficiency and reliability of the rehabilitation assessment process by introducing quantitative synergistic indicators fusing electrophysiological and kinematic level information. First, electromyographic and kinematic data of the lower extremity were collected from subjects trained to walk wearing an exoskeleton. Then, based on muscle synergy theory, a synergistic quantification algorithm was used to construct synergistic index features of electromyography and kinematics. Finally, the electrophysiological and kinematic level information was fused to build a modal feature fusion model and output the lower limb motor function score. The experimental results showed that the correlation coefficients of the constructed synergistic features of electromyography and kinematics with the clinical scale were 0.799 and 0.825, respectively. The results of the fused synergistic features in the K-nearest neighbor (KNN) model yielded higher correlation coefficients ( r = 0.921, P < 0.01). This method can modify the rehabilitation training mode of the exoskeleton robot according to the assessment results, which provides a basis for the synchronized assessment-training mode of "human in the loop" and provides a potential method for remote rehabilitation training and assessment of the lower extremity.

Application of combination of intraoperative neuroelectrophysiological monitoring and neuronavigation multi-modal fusion technology in the glioma resection / 中国神经精神疾病杂志

Objective To analyze the application of intraoperative neurophysiological monitoring combined with neuronavigation multi-modal fusion technology in the brainstem glioma resection. Methods One hundred twenty patients with brainstem glioma were divided into observation group and control group. The control group was treated by traditional operation, while the observation group was treated by intraoperative nerve electrophysiological monitoring combined with neuronavigation multimodal fusion technology. The general condition, clinical efficacy, KPS score, complications and survival rate of the two groups were compared. Results The effect was significantly better in the observation group(76.66%)than in control group(53.33%)( x2=11.962,P=0.001).KPS scores were significantly higher in the observation group (27.91 ±1.98) than in the control group (12.11 ±2.13)(t=32.669, P<0.001). Conclusions Intraoperative nerve electrophysiological monitoring plus neuronavigation multimodality fusion technology can improve clinical efficacy and quality of life in patients with brainstem glioma.