本文選題：單通道腦機(jī)接口 + 眨眼腦電信號(hào)��； 參考：《哈爾濱工業(yè)大學(xué)》2017年碩士論文

【摘要】：隨著傷老病殘人群對(duì)生活品質(zhì)需求不斷提高,對(duì)基于腦電控制的人機(jī)交互式智能輪椅研究有很大必要性,然而基于運(yùn)動(dòng)想象腦電信號(hào)的智能輪椅控制系統(tǒng)龐大,信號(hào)采集設(shè)備成本昂貴,輪椅自由運(yùn)動(dòng)受限,致使目前僅限于實(shí)驗(yàn)室研究而無(wú)法大規(guī)模應(yīng)用。為此本課題開(kāi)發(fā)了低成本、較好性能的人機(jī)交互式智能輪椅系統(tǒng),該系統(tǒng)采用便攜式的單通道腦機(jī)接口設(shè)備采集腦電信號(hào),利用腦電信號(hào)眨眼特征和集中度參數(shù)結(jié)合人機(jī)交互界面控制輪椅運(yùn)動(dòng),最終能夠?qū)崿F(xiàn)基本運(yùn)動(dòng),實(shí)時(shí)性和可操控性可較好滿(mǎn)足要求。首先,研究了腦電信號(hào)的產(chǎn)生機(jī)理和特點(diǎn),分析了腦機(jī)接口系統(tǒng)的工作原理及其國(guó)內(nèi)外研究現(xiàn)狀,研究了快速傅里葉變換、小波變換理論和功率譜估計(jì)等腦電信號(hào)粉刺處理算法并分別matlab仿真實(shí)現(xiàn),改進(jìn)基于小波的軟硬閾值收縮算法并評(píng)估改進(jìn)效果。其次,選定了腦電信號(hào)的采集與傳輸方式,接收到原始腦電信號(hào)后采用改進(jìn)的小波閾值收縮算法對(duì)其進(jìn)行了去偽跡處理,通過(guò)特征識(shí)別算法識(shí)別出眨眼特征和精神集中特征并轉(zhuǎn)換為控制信號(hào),在MFC平臺(tái)設(shè)計(jì)了基于眨眼腦電信號(hào)的人機(jī)交互系統(tǒng)。選取一定的樣本量設(shè)計(jì)了眨眼腦電信號(hào)的特征參數(shù)預(yù)標(biāo)定實(shí)驗(yàn)并驗(yàn)證,根據(jù)預(yù)標(biāo)定結(jié)果設(shè)定眨眼信號(hào)的閾值和集中度參數(shù)完成了人機(jī)交互實(shí)驗(yàn)研究。再次,完成了基于單通道腦機(jī)接口的智能輪椅控制與人機(jī)交互系統(tǒng)的軟硬件設(shè)計(jì)。設(shè)計(jì)了STM32處理器核心控制電路和腦電信號(hào)采集傳輸、直流電機(jī)控制、交互顯示界面、輔助避障等系統(tǒng)硬件電路,在STM32上移植了μC/OS-III嵌入式實(shí)時(shí)操作系統(tǒng)和STemWin圖形界面,在系統(tǒng)中進(jìn)行了腦電信號(hào)接收解碼與眨眼特征識(shí)別,編寫(xiě)和調(diào)試智能輪椅運(yùn)動(dòng)狀態(tài)控制和交互界面信息顯示等程序的代碼,實(shí)現(xiàn)了智能輪椅與人機(jī)交互控制的軟件系統(tǒng)。最后,聯(lián)合調(diào)試基于眨眼腦電信號(hào)的智能輪椅控制與人機(jī)交互的軟硬件系統(tǒng),在不同類(lèi)型的路徑下分別利用眨眼腦電信號(hào)特征和其集中度參數(shù)控制輪椅運(yùn)動(dòng),對(duì)系統(tǒng)性能進(jìn)行實(shí)驗(yàn)測(cè)試,給出了相關(guān)的測(cè)試數(shù)據(jù)并分析其結(jié)果。測(cè)試結(jié)果表明,基于單通道腦機(jī)接口的智能輪椅控制與人機(jī)交互系統(tǒng)具有較好的實(shí)時(shí)性和可操控性,為便攜式腦機(jī)接口技術(shù)在實(shí)際應(yīng)用中的探索研究奠定了基礎(chǔ)。
[Abstract]:With the increasing demand for the quality of life among the elderly, the disabled and the injured, it is necessary to study the man-machine interactive intelligent wheelchair based on EEG control. However, the intelligent wheelchair control system based on EEG is huge. Signal acquisition equipment is expensive and wheelchair free movement is limited, so it is limited to laboratory research and can not be applied on a large scale. Therefore, a low cost and better performance man-machine interactive intelligent wheelchair system is developed. The system uses portable single-channel brain-computer interface equipment to collect EEG signals. The basic motion of wheelchair can be realized by using the blinking characteristic and concentration parameter of EEG combined with the man-machine interaction interface. The real-time and maneuverability can meet the requirements well. Firstly, the mechanism and characteristics of EEG signal generation are studied, the working principle of BCI system and its research status at home and abroad are analyzed, and the fast Fourier transform (FFT) is studied. Wavelet transform theory, power spectrum estimation and other EEG signal processing algorithms are implemented by matlab simulation, which improves the soft and hard threshold shrinkage algorithm based on wavelet transform and evaluates the effect of the improved algorithm. Secondly, the acquisition and transmission mode of EEG signal is selected. After receiving the original EEG signal, the improved wavelet threshold shrinkage algorithm is used to deartifact the EEG signal. The blinking feature and the concentration feature are recognized by the feature recognition algorithm and converted into control signals. A human-computer interaction system based on the blinking EEG is designed on the MFC platform. A certain sample size is selected to design the pre-calibration experiment of the characteristic parameters of the blinking EEG signal and verify it. According to the pre-calibration results, the threshold and concentration parameters of the blinking signal are set up to complete the human-computer interaction experiment. Thirdly, the software and hardware design of intelligent wheelchair control and man-machine interaction system based on single channel brain-computer interface is completed. The core control circuit of STM32 processor and the hardware circuits of EEG acquisition and transmission, DC motor control, interactive display interface and auxiliary obstacle avoidance are designed. 渭 C/OS-III embedded real-time operating system and STemWin graphic interface are transplanted on STM32. The software system of intelligent wheelchair and man-machine interactive control is realized by the code of EEG receiving and decoding and blink feature recognition in the system, and the code of intelligent wheelchair motion state control and interactive interface information display are compiled and debugged. Finally, the software and hardware system of intelligent wheelchair control and man-machine interaction based on blinking EEG signal is debugged, and the wheelchair motion is controlled by the characteristics of blinking EEG signal and its concentration parameter under different paths, respectively. The performance of the system is tested, the relevant test data are given and the results are analyzed. The test results show that the intelligent wheelchair control and man-machine interaction system based on single channel Brain-Computer Interface have better real-time and maneuverability, which lays a foundation for the exploration and research of portable Brain-Computer Interface technology in practical application.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R318;TN911.7

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 楊健;張金峰;;殘疾人社會(huì)救助政策效果與完善路徑[J];地方財(cái)政研究;2016年01期

2 高楠;傅俊英;趙蘊(yùn)華;;人機(jī)結(jié)合的研究現(xiàn)狀與進(jìn)展[J];高技術(shù)通訊;2015年02期

3 趙進(jìn)創(chuàng);馬超;潘屏萍;傅文利;;基于單通道腦機(jī)接口的小車(chē)控制系統(tǒng)設(shè)計(jì)[J];電子技術(shù)應(yīng)用;2014年04期

4 陳東偉;李海芳;相潔;陳俊杰;;基于腦-機(jī)接口的智能車(chē)控制算法研究與實(shí)現(xiàn)[J];太原理工大學(xué)學(xué)報(bào);2013年06期

5 張瑞;李遠(yuǎn)清;;多模態(tài)腦機(jī)接口游戲系統(tǒng)的設(shè)計(jì)與應(yīng)用[J];計(jì)算機(jī)工程與應(yīng)用;2012年22期

6 徐寶國(guó);彭思;宋愛(ài)國(guó);;基于運(yùn)動(dòng)想象腦電的上肢康復(fù)機(jī)器人[J];機(jī)器人;2011年03期

7 白雪;;腦電波實(shí)時(shí)控制電動(dòng)輪椅[J];機(jī)器人技術(shù)與應(yīng)用;2010年02期

8 徐寶國(guó);宋愛(ài)國(guó);;基于小波包變換和聚類(lèi)分析的腦電信號(hào)識(shí)別方法[J];儀器儀表學(xué)報(bào);2009年01期

9 魯濤;原魁;朱海兵;;智能輪椅研究現(xiàn)狀及發(fā)展趨勢(shì)[J];機(jī)器人技術(shù)與應(yīng)用;2008年02期

10 萬(wàn)柏坤;綦宏志;趙麗;陳濱津;畢卡詩(shī);陳騫;;基于腦電Alpha波的腦-機(jī)接口控制實(shí)驗(yàn)[J];天津大學(xué)學(xué)報(bào);2006年08期

相關(guān)博士學(xué)位論文 前3條

1 王洪濤;混合腦機(jī)接口實(shí)現(xiàn)及其應(yīng)用研究[D];華南理工大學(xué);2015年

2 申慧敏;基于頭部電磁信息反演的人機(jī)交互系統(tǒng)控制指令提取方法研究[D];浙江大學(xué);2015年

3 吳婷;自發(fā)腦電腦機(jī)接口模式識(shí)別關(guān)鍵技術(shù)與實(shí)驗(yàn)研究[D];上海交通大學(xué);2008年

相關(guān)碩士學(xué)位論文 前10條

1 左超華;便攜式單導(dǎo)腦電信號(hào)采集與處理研究[D];西南交通大學(xué);2016年

2 朱丹;基于便攜式腦電采集設(shè)備的機(jī)械臂控制系統(tǒng)[D];南京郵電大學(xué);2015年

3 宋聞笛;運(yùn)動(dòng)想象BCI的移動(dòng)機(jī)器人導(dǎo)航系統(tǒng)研究[D];北京理工大學(xué);2015年

4 馬超;基于單通道腦機(jī)接口的嵌入式智能輪椅控制系統(tǒng)研究[D];廣西大學(xué);2015年

5 梅意城;基于腦機(jī)接口技術(shù)的手臂康復(fù)研究[D];北京工業(yè)大學(xué);2014年

6 李陽(yáng);單導(dǎo)腦電信號(hào)偽跡去除算法的研究[D];蘭州大學(xué);2014年

7 王喜梅;腦電波控制的智能輪椅控制系統(tǒng)設(shè)計(jì)[D];大連交通大學(xué);2013年

8 張璐琳;基于腦機(jī)接口的控制及虛擬場(chǎng)景應(yīng)用研究[D];哈爾濱工程大學(xué);2013年

9 劉鑫;基于小波分析的強(qiáng)噪聲環(huán)境下弱信號(hào)提取研究[D];南京大學(xué);2012年

10 王宇丁;實(shí)時(shí)腦—機(jī)接口設(shè)計(jì)與研究[D];重慶大學(xué);2012年

，

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