本文選題：便攜式 + BCI�。� 參考：《濟(jì)南大學(xué)》2014年碩士論文

【摘要】：腦機(jī)接口(Brain-Computer Interface，簡稱BCI)是指讓人不依靠人自身的輸出通路，比如人神經(jīng)系統(tǒng)和肌肉組織等，只通過腦波就能夠與外界進(jìn)行通信或控制的設(shè)備。由于臨床醫(yī)學(xué)、心理認(rèn)知學(xué)、PC科學(xué)和通信等各個(gè)學(xué)科的飛速發(fā)展，BCI系統(tǒng)的研發(fā)探究在腦功能方面越來越成為了熱點(diǎn)。 本文關(guān)于課題的研究主要由以下三大部分構(gòu)成：第一部分是設(shè)計(jì)實(shí)現(xiàn)便攜式腦電信號(hào)(electroencephalograph，簡稱EEG)采集系統(tǒng)，包括相關(guān)硬件電路設(shè)計(jì)和軟件設(shè)計(jì)；第二部分是控制單元對EEG進(jìn)行處理，包括了EEG數(shù)據(jù)的預(yù)處理、特征提取等；第三部分是分類和鑒別采集的相關(guān)EEG，根據(jù)相關(guān)對應(yīng)情況轉(zhuǎn)換為控制信號(hào)，進(jìn)而控制外圍電路。 本文首先設(shè)計(jì)實(shí)現(xiàn)了一種便攜式EEG采集系統(tǒng)，大多數(shù)的腦電采集系統(tǒng)都是利用多導(dǎo)聯(lián)的高精度腦電放大器對信號(hào)進(jìn)行記錄和分析，，但龐大的輸入電路和檢測時(shí)間是難以應(yīng)用與便攜式設(shè)備。本文采用了一個(gè)有效的集成模擬前端芯片(ADS1299)來實(shí)現(xiàn)了一個(gè)八通道的EEG采集系統(tǒng)。與現(xiàn)有系統(tǒng)相比，這種設(shè)計(jì)極大地簡化了前端電路，提高共模抑制比(CMRR)。該EEG采集設(shè)備集成密度高，有良好的便攜性性和實(shí)用性，緊跟了當(dāng)前便攜式EEG采集系統(tǒng)的發(fā)展趨勢。 其次介紹了基于小波和小波包分析的EEG特征提取算法和運(yùn)用了支持向量機(jī)(SVM)的模式分類算法，有效的提取出以系數(shù)均值和能量為特征的特征向量，取得較好的分類效果。最后將分類信息轉(zhuǎn)換成控制信號(hào)，通過控制小燈有效的識(shí)別了左右手運(yùn)動(dòng)想象。根據(jù)受試者的實(shí)驗(yàn)測試結(jié)果表明系統(tǒng)可用性強(qiáng)，準(zhǔn)確率高。
[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.
【學(xué)位授予單位】：濟(jì)南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN911.7

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