基于脑肌电同源性模型的运动意图定向复现方法研究

项目名称： 基于脑肌电同源性模型的运动意图定向复现方法研究

项目编号： No.61503374

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 其他

项目作者： 丁其川

作者单位： 中国科学院沈阳自动化研究所

项目金额： 23万元

中文摘要： 完整复现缺失肢体的运动是康复医学面临的一项难题，研究基于头皮脑电（EEG）或表面肌电（sEMG）的运动辅助技术有助于攻克这一难关。由于EEG信噪比低，空间分辨率差；而sEMG依存于肌肉，且会因肌肉疲劳导致非平稳，因此应用单一EEG/sEMG难以开发稳定、普适且操控自如的运动辅助系统。现有神经科学揭示出，与运动相关的EEG与sEMG都是源自人脑产生的运动意图，具有同源性。本课题从脑肌电同源性机理出发，建立EEG与sEMG的隐层神经活跃度映射模型；通过模型提取出脑肌电信号中蕴含的肢体关节/部位的运动意图，实现针对该运动意图的定向估计；同时，建模过程引入基于疲劳因子的自适应策略，以保证模型及运动估计的稳定性。本课题提出的方法可为运动辅助设备（如假肢）复现人脑的运动意图提供一种可行的技术途径，对于开发智能假肢等运动辅助系统具有重要意义。

中文关键词： 头皮脑电；表面肌电；运动识别；运动辅助；脑机交互

英文摘要： Completely restoring the motion of human’s disabled limb is a challenge in rehabilitation medicine. Studying the movement-assistance technology based on electroencephalogram (EEG) or surface electromyography (sEMG) helps to overcome the difficulty. However, the noise ratio and spatial resolution of EEG signals are low, and sEMG signals depend on muscles and have no-stationary due to muscle fatigue, so it is difficult to develop a stable, universal and easily manipulated movement-assistance system by using the single EEG or sEMG. Current neuroscience reveals that the motion-related EEG and sEMG signals are both derived from the motion intent produced by human brain, so EEG and sEMG have homology. In view of the homology mechanism between EEG and sEMG, this proposal first built a mapping model to relate the nerve activities in hidden layers of EEG and sEMG. Afterwards, the motion intent of human limb/joint can be extracted from EEG and sEMG signals by using the built model, and then the targeted movement can be estimated. Meanwhile, the proposal introduced a fatigue-factor-based adaptive scheme in modeling to ensure the stability of the model and motion estimation. With the proposed methods, this proposal provides a feasible way to reappear the motion intent in human brain by using movement-assistance systems (e.g., artificial limb). The studies in this proposal are meaningful for the development of smart prosthetics and other movement-assistance systems.

英文关键词： Electroencephalography;surface Electromyography;motion recognition;movement-assistance technology;brain-robot interface