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计算机工程 ›› 2010, Vol. 36 ›› Issue (15): 248-249,252. doi: 10.3969/j.issn.1000-3428.2010.15.088

• 开发研究与设计技术 • 上一篇    下一篇

基于大脑神经元放电的脑-机接口技术

贾爱宾1,2,王 敏1,刘法胜1   

  1. (1. 山东科技大学信息与电气工程学院,青岛 266510;2. 青岛理工大学理学院,青岛 266520)
  • 出版日期:2010-08-05 发布日期:2010-08-25
  • 作者简介:贾爱宾(1978-),女,讲师、博士研究生,主研方向: 信号检测及其处理,生物信息处理;王 敏、刘法胜,教授、博士
  • 基金资助:
    山东省自然科学基金资助项目(Y2007C029)

Brain-Computer Interface Technology Based on Brain Neuronal Discharge

JIA Ai-bin1,2, WANG Min1, LIU Fa-sheng1   

  1. (1. College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao 266510; 2. College of Science, Qingdao Technological University, Qingdao 266520)
  • Online:2010-08-05 Published:2010-08-25

摘要: 基于大脑运动皮层神经元放电的脑-机接口通过记录大脑运动皮层神经元的放电信号控制瘫痪肢体或假肢运动,其软硬件核心为神经元群体解码和神经元放电活动的检测。解码方法分为推理算法和分类器方法,检测方法通过在大脑运动皮层区植入长效电极记录单个或群体神经元的放电活动。分析表明,脑-机接口技术应在更多脑区域上植入长效电极达到更好控制设备的目的,各类解码算法应通过联合并加入反馈信号提高对神经元信号的解码效果。

关键词: 神经元放电, 脑机接口, 植入式电极, 神经元解码

Abstract: Brain-Computer Interface(BCI) based on neural firing rates of cerebral motor cortex can control the paralysed body or the motion of the prosthetic device by recording neuronal firing rates of cerebral motor cortex. The core of the software and hardware are the neurons decoding method and the detection technique of the potential of neuronal. The neuronal decoding methods are divided into inferential algorithm and classifiers method, the detection technique is recording the neuronal activity of single or population neuronal using the chronic microelectrodes planted in the cerebral motor cortex. Analysis shows that BCI technology should apply continuously chronic working implanted electrodes on more areas of the brain to control equipment better; different decoding method should unite and add feedback signal to improve the performance of the decoding.

Key words: neuronal discharge, Brain-Computer Interface(BCI), implanted electrode, neuronal decoding

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