便携式脑机接口系统应用研究

发布时间：2018-05-02 06:46

本文选题：便携式 + BCI　；参考：《济南大学》2014年硕士论文

【摘要】：脑机接口(Brain-Computer Interface，简称BCI)是指让人不依靠人自身的输出通路，比如人神经系统和肌肉组织等，只通过脑波就能够与外界进行通信或控制的设备。由于临床医学、心理认知学、PC科学和通信等各个学科的飞速发展，BCI系统的研发探究在脑功能方面越来越成为了热点。本文关于课题的研究主要由以下三大部分构成：第一部分是设计实现便携式脑电信号(electroencephalograph，简称EEG)采集系统，包括相关硬件电路设计和软件设计；第二部分是控制单元对EEG进行处理，包括了EEG数据的预处理、特征提取等；第三部分是分类和鉴别采集的相关EEG，根据相关对应情况转换为控制信号，进而控制外围电路。本文首先设计实现了一种便携式EEG采集系统，大多数的脑电采集系统都是利用多导联的高精度脑电放大器对信号进行记录和分析，，但庞大的输入电路和检测时间是难以应用与便携式设备。本文采用了一个有效的集成模拟前端芯片(ADS1299)来实现了一个八通道的EEG采集系统。与现有系统相比，这种设计极大地简化了前端电路，提高共模抑制比(CMRR)。该EEG采集设备集成密度高，有良好的便携性性和实用性，紧跟了当前便携式EEG采集系统的发展趋势。其次介绍了基于小波和小波包分析的EEG特征提取算法和运用了支持向量机(SVM)的模式分类算法，有效的提取出以系数均值和能量为特征的特征向量，取得较好的分类效果。最后将分类信息转换成控制信号，通过控制小灯有效的识别了左右手运动想象。根据受试者的实验测试结果表明系统可用性强，准确率高。
[Abstract]:Brain-Computer Interface (BCI) is a device that allows people to communicate or control with the outside world without relying on their own output pathways, such as the human nervous system and muscle tissue. With the rapid development of clinical medicine, psychological cognition, PC science and communication, the research and development of BCI system has become more and more popular in the field of brain function. The research of this paper is mainly composed of the following three parts: the first part is the design and implementation of a portable EEG electroencephalography (EEGG) acquisition system, including the related hardware circuit design and software design; The second part is the control unit to process the EEG, including the EEG data preprocessing, feature extraction and so on; the third part is the classification and identification of the collection of EGs, according to the corresponding situation into the control signal, and then control the peripheral circuit. In this paper, a portable EEG acquisition system is designed and implemented. Most EEG acquisition systems use high precision EEG amplifier to record and analyze the signal. But huge input circuits and detection times are difficult to apply with portable devices. In this paper, an effective integrated analog front-end chip ADS1299) is used to realize an eight-channel EEG acquisition system. Compared with the existing system, this design greatly simplifies the front-end circuit and improves the common-mode rejection ratio (CMRR). The EEG acquisition equipment has high integration density, good portability and practicability, and follows the development trend of portable EEG acquisition system. Secondly, the EEG feature extraction algorithm based on wavelet and wavelet packet analysis and the pattern classification algorithm based on support vector machine (SVM) are introduced. The feature vectors with coefficients mean and energy are extracted effectively, and good classification results are obtained. Finally, the classified information is converted into the control signal, and the left and right hand motion imagination is effectively recognized by the control light. The experimental results show that the system is highly available and accurate.
【学位授予单位】：济南大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.7

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