發(fā)布時(shí)間：2018-06-15 21:33

  本文選題：模擬放大器 + ADC��； 參考：《北京理工大學(xué)》2015年碩士論文

【摘要】：神經(jīng)科學(xué)和電子科學(xué)的學(xué)科交叉是目前的前沿課題，科學(xué)家們?cè)噲D通過電子與信息的技術(shù)來重構(gòu)神經(jīng)網(wǎng)路，通過微電極將電子設(shè)備植入大腦，從而直接探測(cè)單獨(dú)或者群體神經(jīng)元細(xì)胞的電活動(dòng)。對(duì)人類大腦和神經(jīng)系統(tǒng)的研究是人類目前科技發(fā)展的一個(gè)重要突破方向，通過電子科學(xué)技術(shù)去發(fā)現(xiàn)其工作規(guī)律并通過電信號(hào)去激勵(lì)甚至取代神經(jīng)信號(hào)傳輸，為人類運(yùn)動(dòng)和感官功能的神經(jīng)修復(fù)開辟了一條道路。 然而，實(shí)現(xiàn)以上目標(biāo)，一個(gè)基本前提是能夠很準(zhǔn)確、實(shí)時(shí)、高校的得到神經(jīng)元細(xì)胞的電信號(hào)，尤其是安全可以保證的前提下。本文的研究目標(biāo)是以植入式腦機(jī)接口神經(jīng)信號(hào)采集和修復(fù)系統(tǒng)為應(yīng)用背景，采用CMOS集成電路工藝技術(shù)實(shí)現(xiàn)神經(jīng)信號(hào)模擬前端的信號(hào)采集、放大和模數(shù)轉(zhuǎn)換，為后續(xù)數(shù)字處理做基礎(chǔ)。 盡管國際上，對(duì)于神經(jīng)信號(hào)采集芯片的研究已經(jīng)有一定的技術(shù)和歷史，，且有眾多成果。但真正用于人類日常生活的還基本沒有。對(duì)于神經(jīng)電信號(hào)的采集中的等效輸入噪聲、直流偏執(zhí)抑制范圍、信號(hào)的失真度等性能參數(shù)的優(yōu)化研究仍然需要學(xué)者投入大量的研究精力，最終實(shí)現(xiàn)高效、有效、實(shí)時(shí)的神經(jīng)信號(hào)采集。 本文對(duì)植入式神經(jīng)信號(hào)采集系統(tǒng)的神經(jīng)電極接口模塊和信號(hào)采集處理模塊進(jìn)行了重點(diǎn)闡述。且對(duì)于神經(jīng)電路接口模塊做了詳盡的討論，尤其是對(duì)神經(jīng)信號(hào)及其特征、電極以及組織接口電學(xué)模型做了綜述，為模擬前端設(shè)計(jì)提供理論支撐。 此外，本文的核心內(nèi)容就是介紹模擬前端的設(shè)計(jì)。具體分析和介紹了模擬低噪聲放大器的設(shè)計(jì)要點(diǎn)，分別從結(jié)構(gòu)級(jí)和器件級(jí)分析了放大器的噪聲和功耗性能，給出了基于理論分析進(jìn)行的折衷優(yōu)化設(shè)計(jì)。介紹了模數(shù)轉(zhuǎn)換器的結(jié)構(gòu)選擇，基于選擇的結(jié)構(gòu)進(jìn)行了原理分析和行為級(jí)建模，根據(jù)行為級(jí)建模的掃描仿真結(jié)果進(jìn)行了電路結(jié)構(gòu)選取和設(shè)計(jì)，給出了模數(shù)轉(zhuǎn)換器的前后仿真結(jié)果。最后，給出整體四通道模擬前端設(shè)計(jì)的流片測(cè)試結(jié)果，以及結(jié)果分析。
[Abstract]:The intersection of neuroscience and electronics is the frontier of the day, with scientists trying to reconstruct neural networks using electronic and information technology, and microelectrodes to implant electronic devices into the brain. This directly detects the electrical activity of individual or colony neuron cells. The study of human brain and nervous system is an important breakthrough direction in the development of human science and technology at present. Through electronic science and technology to discover its working rules and electrical signals to stimulate or even replace neural signal transmission. It opens the way for nerve repair of human motor and sensory functions. However, to achieve the above goal, one of the basic prerequisites is to be able to be very accurate, real-time, college to get neuronal cell electrical signals, especially under the premise that security can be guaranteed. The research goal of this paper is to realize the signal acquisition, amplification and analog-to-digital conversion of the neural signal analogue front end using CMOS integrated circuit technology based on the neural signal acquisition and repair system of the implanted brain-computer interface. To provide the basis for subsequent digital processing. Although the research of neural signal acquisition chip has a certain technology and history in the world, and has a lot of achievements. But the real use of human daily life is basically not. The optimization of the performance parameters such as equivalent input noise, DC paranoid suppression range, signal distortion and so on in the acquisition of neural signals still needs a lot of research effort from scholars to achieve high efficiency and effectiveness. Real-time neural signal acquisition. In this paper, the neural electrode interface module and signal acquisition and processing module of implanted neural signal acquisition system are described. The interface module of neural circuit is discussed in detail, especially the electrical model of neural signal and its characteristics, electrode and tissue interface, which provides theoretical support for the design of analog front-end. In addition, the core of this paper is to introduce the design of analog front-end. The design points of analog low noise amplifier are analyzed and introduced in detail. The noise and power performance of the amplifier are analyzed from the structure level and the device level, and the tradeoff optimization design based on the theoretical analysis is given. The structure selection of A / D converter is introduced. The principle analysis and behavior level modeling are carried out based on the selected structure, and the circuit structure is selected and designed according to the scan simulation results of behavioral modeling. The simulation results before and after the analog-to-digital converter are given. Finally, the test results of the whole four-channel simulation front end are given and the results are analyzed.
【學(xué)位授予單位】：北京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TN911.7

【共引文獻(xiàn)】

相關(guān)期刊論文 前10條

1 范壽年,蔣晨曦,劉志琴,趙寧,蔡運(yùn)昌,范園園;系列實(shí)時(shí)手持式心律失常監(jiān)護(hù)儀研究和臨床應(yīng)用[J];貴州醫(yī)藥;2004年02期

2 臧國華;周宗潭;李明;;腦機(jī)接口系統(tǒng)設(shè)計(jì)中工頻干擾分析與抑制問題研究[J];計(jì)算機(jī)測(cè)量與控制;2006年05期

3 蔡瓊;陳鵬慧;魏武;;采用小波變換的腦電圖信號(hào)分析及其應(yīng)用[J];華僑大學(xué)學(xué)報(bào)(自然科學(xué)版);2015年02期

4 裘嘉恒;李雅堂;許坤涵;楊卓;張濤;;癲癇發(fā)作間期alpha波的窄帶相位同步分析[J];生物物理學(xué)報(bào);2008年03期

5 段瑩;高和;;標(biāo)準(zhǔn)多導(dǎo)睡眠監(jiān)測(cè)的技術(shù)規(guī)范和應(yīng)用范圍[J];世界睡眠醫(yī)學(xué)雜志;2014年01期

6 李群;程寧;張濤;;基于神經(jīng)網(wǎng)絡(luò)的振蕩模式分析及其應(yīng)用[J];生理學(xué)報(bào);2015年02期

7 張廣武,范壽年,蔣晨曦;便攜式手持式心律失常監(jiān)護(hù)儀研究[J];醫(yī)療裝備;2005年03期

8 余皓;徐良;;運(yùn)動(dòng)神經(jīng)彌補(bǔ)技術(shù)的進(jìn)展[J];醫(yī)療裝備;2006年06期

9 何航程,沈模衛(wèi),陳碩,張鋒;認(rèn)知神經(jīng)科學(xué)領(lǐng)域腦電復(fù)雜性測(cè)度方法的新進(jìn)展[J];應(yīng)用心理學(xué);2002年03期

10 李剛,劉巍,于學(xué)敏,相韶霞,林凌,何宏獻(xiàn),虞啟璉;CIHANG-2000型微型多功能心電圖機(jī)的研制[J];中國醫(yī)療器械雜志;1998年03期

相關(guān)會(huì)議論文 前2條

1 耿麗清;趙麗;元鵬賢;李宏偉;;基于雙層穩(wěn)態(tài)視覺誘發(fā)電位的腦機(jī)接口技術(shù)研究[A];中國自動(dòng)化學(xué)會(huì)控制理論專業(yè)委員會(huì)D卷[C];2011年

2 孫煜;朱貽盛;李穎潔;童善保;;抑郁癥對(duì)大腦皮層功能聯(lián)系的影響[A];中國生物醫(yī)學(xué)工程進(jìn)展——2007中國生物醫(yī)學(xué)工程聯(lián)合學(xué)術(shù)年會(huì)論文集（下冊(cè)）[C];2007年

相關(guān)博士學(xué)位論文 前10條

1 汪春梅;癲癇腦電信號(hào)特征提取與自動(dòng)檢測(cè)方法研究[D];華東理工大學(xué);2011年

2 程龍龍;BCICFES重建運(yùn)動(dòng)神經(jīng)系統(tǒng)的信號(hào)處理與控制關(guān)鍵技術(shù)研究[D];天津大學(xué);2010年

3 孫曉霞;主語關(guān)系從句加工優(yōu)先共性的研究：漢語神經(jīng)電生理學(xué)的證據(jù)[D];東北師范大學(xué);2011年

4 游榮義;腦電信號(hào)非線性分析方法的研究[D];廈門大學(xué);2003年

5 楊幫華;自發(fā)腦電腦機(jī)接口技術(shù)及腦電信號(hào)識(shí)別方法研究[D];上海交通大學(xué);2007年

6 劉永宏;癲癇發(fā)作期及發(fā)作間期同步EEG-fMRI的研究[D];四川大學(xué);2007年

7 李t

本文編號(hào)：2023729