DTMS-EEG检测系统的设计与分析

发布时间：2018-10-31 09:06

【摘要】：精神疾病现已成为我国严重的公共健康和社会问题,但其诊断尚缺乏量化标准。将深部经颅磁刺激(DTMS)作为引起大脑特异性的输入,EEG信号作为输出获得脑功能的状态,是检测和诊断精神疾病的有效方法之一。其中脑电检测分析是诊断精神疾病的核心技术。本文提出实现了一种多路DTMS-EEG无线传输检测方法。首先,利用CPLD同步控制多路AD转换器,实现了多路同步传输的系统结构;其次,通过硬件三级放大、有源、无源、高阶滤波处理,实现了对EEG信号调理;然后,根据DTMS刺激特点,加入可编程放大及模拟开关,利用外部触发同步控制DTMS刺激信号,可编程放大及模拟开关,实现了DTMS刺激下EEG信号在线检测的特殊控制;最后,通过自动比特位选择数据压缩等方法,实现了多通道下信号的无线传输,并在传输接收端将数据上传至上位机,进行显示、控制。根据脑电信号的特点,将互信息方法与Lempel-Ziv复杂度方法的优点相结合,提出一种MILZC新方法,以针刺EEG数据为对象,分析不同脑区间信息交流的复杂度。通过对8位受试者手针六种状态下的分析(针刺前,针刺50次/分钟,针刺100次/分钟,针刺150次/分钟,针刺200次/分钟,针刺后),结果表明(1)MILZC值在针刺过程中增加;(2)100次/分钟和针刺150次/分钟针刺频率时比50次/分钟和针刺200次/分钟更加有效;(3)异侧脑半球的响应要明显高于同侧半球。以上结果证明,MILZC方法能有效地反映针刺下脑区间信息交流复杂度的变化。方法可以直接应用于其他EEG数据的分析。本文设计的DTMS-EEG无线传输检测系统,具有多路同步,多路传输,DTMS刺激下EEG在线检测的特点,为精神疾病的诊疗提供一种新思路。提出的MILZC-EEG分析方法从脑功能网络角度进行分析,适用于DTMS-EEG研究精神疾病的思路。
[Abstract]:Mental illness has become a serious public health and social problem in China, but its diagnosis is still lack of quantitative standard. Using deep transcranial magnetic stimulation (DTMS) as a specific input to the brain and EEG signal as an output to obtain brain function is one of the effective methods for the detection and diagnosis of mental illness. EEG detection and analysis is the core technology in the diagnosis of mental illness. A multichannel DTMS-EEG wireless transmission detection method is proposed in this paper. Firstly, the multiplex AD converter is controlled by CPLD synchronously, and the system structure of multichannel synchronous transmission is realized. Secondly, through the three-stage hardware amplification, active, passive, high-order filter processing, the EEG signal is adjusted. Then, according to the characteristics of DTMS stimulation, the programmable amplifier and analog switch are added to control the DTMS stimulus signal by external trigger synchronously, and the programmable amplifier and analog switch are used to realize the special control of EEG signal on-line detection under the DTMS stimulation. Finally, the wireless transmission of multi-channel signals is realized by means of automatic bit selection data compression, and the data is uploaded to the host computer at the transmission receiving end for display and control. According to the characteristics of EEG signals, this paper combines the advantages of mutual information method and Lempel-Ziv complexity method, and proposes a new MILZC method, which takes acupuncture EEG data as an object to analyze the complexity of information exchange in different brain regions. By analyzing the six states of hand acupuncture in 8 subjects (before acupuncture, 50 times per minute, 100 times per minute, 150 times per minute, 200 times per minute, after acupuncture), The results showed that (1) MILZC increased during acupuncture. (2) the frequency of 100 times / minute and 150 times / min of acupuncture is more effective than that of 50 times / minute and 200 times / minute, (3) the response of the heterolateral hemisphere is obviously higher than that of the ipsilateral hemisphere. The above results show that the MILZC method can effectively reflect the change of the complexity of information exchange between the acupuncture and brain regions. The method can be directly applied to the analysis of other EEG data. The DTMS-EEG wireless transmission detection system designed in this paper has the characteristics of multi-channel synchronization, multi-channel transmission and EEG on-line detection under the stimulation of DTMS, which provides a new way of thinking for the diagnosis and treatment of mental illness. The proposed MILZC-EEG analysis method can be applied to the study of mental illness by DTMS-EEG from the point of view of brain functional network.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TN911.3;R318.6

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