基于mu节律能量的运动意识分类研究

基于脑电(EEG)的脑机接口(BCI)是在人脑和计算机或其它电子设备之间建立不依赖于常规大脑信息输出通路(外周神经和肌肉组织)的全新对外信息交流和控制技术。文中提出了基于mu节律能量为脑电特征的意识任务分类思想,对被测试者想象左右手运动的脑电mu节律能量(二阶矩)及其动态变化情况进行研究。实验结果表明,基于mu节律能量的想象左右手运动意识识别和分类的正确识别率可达85%。二阶矩计算简单,而且可在线计算,故可以认为,基于mu节律能量为脑电特征的意识任务分类在脑机接口的应用中有较高的实用价值。

Study of Classification of Motor Imageries Based on Energy of mu Rhythm of EEG

The EEG-based brain-computer interface(BCI) is a novel technology,which provides a wholly new channel between the computer and electronic equipments instead of the normal output pathways of peripheral nerves and muscles.In this paper,the classification of mental activities based on energy of mu rhythm was proposed.The EEG signals were recorded during imagination of left or right hand movement.The energy of mu rhythm(2nd order moment) and its dynamic properties with respect to time were analyzed.According to the analysis and experiment results,the classification of left or right hand movement imagination based on energy of mu rhythm is designed.The correct rate of classification can achieve 85%.Since the computation of 2nd order moment is very simple and can also be estimated in on-line way,the new method has the practicability in the application of brain-computer interface technique.