基于BCI的老年照护系统研究

发布时间：2018-05-08 23:32

本文选题：BCI + 脑电信号　；参考：《河北大学》2017年硕士论文

【摘要】：由于我国养老体系不够完善,老年人高龄化、空巢化及慢性病化趋势加剧,半身不遂、脑血栓等症状普遍存在,使得老年人的长期照护问题变得日益严峻,特别是失能老人的长期照护问题更是亟待解决。如果能将外部设备的控制与失能老人的脑电信号结合起来,失能老人就可以根据自己的需求,按照自己的意愿方便得操控设备。这样不仅能够改善失能老人的长期照护问题,重拾他们对生活的信心和减轻子女的负担,也为脑电的研究和发展在实际生活中的应用、推广进行了有意义的探索和尝试。本文设计了一个基于BCI的老年照护系统。只要是意识清晰的失能老人都可以通过头戴TGAM脑电采集仪进行简单的眨眼动作(短时间闭眼、连续两次有意眨眼)实现家用设备的控制及向子女求助报警,子女们还能通过系统的用户显示界面实时了解到老人的精神状态。针对以上内容,本研究做了如下工作:(1)通过研究脑电信号的采集与处理方案,明确了基于BCI的老年照护系统的开发流程和设计方法。(2)完成了系统的硬件设计,主要包括设备控制模块、蓝牙模块两部分的硬件电路设计和单片机程序编写,其中包括完整的脑电信号控制设备的方法与流程。(3)利用C#语言在Visual Studio 2010开发环境下进行了Windows应用程序的编写,设计了相应的用户显示界面,用于获取TGAM脑电模块输出的脑电数据,进行基于原始脑电信号与眨眼强度的有意眨眼、短时间闭眼识别及基于eSense指数的精神状态识别,进而向单片机发送控制指令实现设备的控制。(4)设计实验验证了硬件部分及系统整体的可操控性与稳定性,其中重点对基于两种不同脑电数据的有意眨眼识别效果进行了测试,测试结果表明每种识别方法下的八位测试者的整体平均识别率均达到了92%,满足系统要求。
[Abstract]:Because the pension system in China is not perfect, the elderly are aging, the tendency of empty-nesting and chronic diseases is increasing, the symptoms of hemiplegia and cerebral thrombosis are widespread, the long-term care problem of the elderly is becoming increasingly serious. In particular, the long-term care of the disabled elderly is urgent to be solved. If the external equipment control can be combined with the EEG signal of the disabled elderly, the disabled can easily control the equipment according to their own needs and their own wishes. This will not only improve the long-term care of the disabled, regain their confidence in life and lighten the burden of their children, but also provide a meaningful exploration and attempt for the research and development of EEG in practical life. In this paper, a BCI-based elderly care system is designed. As long as the elderly with a clear sense of disability can carry out simple blink movements (short eye closure, two consecutive intentional blinks) by wearing a TGAM EEG collector, they can control household equipment and call their children to call the police. Children can also understand the mental state of the elderly in real time through the system's user display interface. In view of the above, this study has done the following work: 1) by studying the collection and processing scheme of EEG signal, the development process and design method of the aged care system based on BCI have been clarified, and the hardware design of the system has been completed. Mainly includes the device control module, Bluetooth module hardware circuit design and MCU programming, It includes the method and flow of the complete EEG control equipment. It uses C # language to write the Windows application program in the Visual Studio 2010 development environment, and designs the corresponding user display interface. It is used to obtain the EEG data from the TGAM EEG module, and to recognize the mental state based on the original EEG signal and the blink intensity, the short-time closed eye recognition and the eSense exponent based mental state recognition. Then the control instruction is sent to the single chip microcomputer to realize the control of the equipment. The experiment verifies the controllability and stability of the hardware part and the system as a whole, in which the effect of intentional blink recognition based on two different EEG data is tested. The test results show that the overall average recognition rate of the eight-bit testers under each recognition method is 92 and meets the requirements of the system.
【学位授予单位】：河北大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911.7;D669.6;TP311.52

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