Research On Geriatric Care System Based On Brain-Computer Interface

Because of China's pension system is not perfect,the trend of the elderly aging,empty nest and chronic diseases is intensifying,hemiplegia,cerebral thrombosis and other symptoms are prevalent.They are making the elderly long-term care problems become increasingly serious,and especially the problem of the elderly disabled long-term care is even more urgent.If we can make the external equipment and the disabled elderly EEG signal combine,the elderly can manipulate equipment easily according to their own needs and their own will.This can not only improve the long-term care of disabled elderly to regain their confidence in life and reduce the burden on children,but also it is a meaningful exploration and try for the EEG research and development in real life.This paper designs an elderly care system based on BCI.As long as the elderly with a clear sense can achieve the control of home equipment and ask children for help through the head wearing TGAM EEG acquisition instrument and a simple blink of action(intentional blink and short time to close eyes for successive two times),children can also learn the mental status of the elderly through the system user interface.In view of the above,this study has done the following work:(1)Through the study of EEG signal acquisition and processing program,the development process and design method of the geriatric care system based on BCI is defined.(2)The hardware design of the system is completed.it mainly includes the devices control module,the Bluetooth module two parts hardware circuit design and the single chip program preparation,including complete EEG signal process control equipment flow and control method.(3)Use C# language in Visual Studio 2010 development environment to write Windows applications,and design the corresponding user interface,including acquisition of the EEG data of TGAM EEG module output,recognition of intentional blink,short-term closed eyes based on the original EEG signal and blinkstrength and recognition of mental state based on eSense meters,and then send control instructions to the microcontroller to achieve the controlof the device.(4)Design experiment to verify the controllability and stability of the hardware part and the whole system,which focuses on the intention of blinking recognition results based on two different EEG data were tested,the test results show that the average recognition rate of the eight bit testers under each recognition method is up to 92% as a whole,which meets the requirements of the system.