BRAIN MACHINE INTERFACE SYSETM WITH ARTIFICIAL INTELLIGENT FOR A PERSON WITH DISABILITY

[ Marghade * , 4.(7 ): Ju ly , 2015] ISSN: 2277 - 9655 (I2OR), Publication Impact Factor: 3.785 http: // www.ijesrt.com © International Journal of Engineering Sciences & Research Technology [ 708 ] IJESRT INTERNATIONAL JOURNA L OF ENGINEERING SCI ENCES & RESEARCH TECHNOLOGY BRAIN MACHINE INTERFACE SYSETM WITH ARTIFICIAL INTELLIGENT FOR A PERSON WITH DISABILITY Ujwala Marghade*, Vinay Keswani * M.Tech ,Electronics Engg(communication), Vidarbha Institute of Techn ology, Nagpur University, India . Assistant Professor (M. Tech ECE),Vidarbha Institute of Technology, Nagpur University, India . ABSTRACT Brain Machine Interface (BMI) system is very useful modus operandi for the disabled or the crippled person to express his emotions and feelings to someone else with the help of EEG signals coming out of the brain. We know that, the human brain is made up of billions of interconnected n eurons about the size of a pinhead. As neurons interact with each other, patterns manifest as singular thoughts such as a math calculation. As a by - product, every interaction between neurons creates a miniscule electrical discharge, measurable by EEG (elec troencephalogram) machines. This system enables people with severe motor disabilities to send command to electronic devices with the help of their brain waves. These signals can be used to control any electronic devices like mouse cursor of the computer, a wheel chair, a robotic arm etc. The research in the area of BMI system uses the sequence of 256 channel EEG data for the analysis of the EEG signals coming out of the brain by using traditional gel based multi sensor system, which is very bulky and not co nvenient to use in real time application. So this particular work proposes a convenient system to analyze the EEG signals, which uses few dry sensors as compared to the traditional gel based multi sensor system with wireless transmission technique for capt uring the brain wave patterns and utilizing them for this application. In this paper, different brain signals are captured by EEG headset that is EMOTIVE EPOC headset. After that this signal is processed and used for various command to application. Here t he EEG signal is used to control the robotic arm, also we introducing artificial intelligence in robotic arm for error proofing of system. The goal of this research is to improve quality of life for those with severe disabilities