EEG Based Smart Wheelchair For Disabled Persons Using Non-Invasive BCI

This paper aims at developing a smart wheelchair that uses EEG signals captured from disabled persons to operate the wheelchair. Interfacing the computer with the brain can be done using Brain-Computer Interface (BCI) technology by connecting the EEG headset to capture the signals from the brain. In this proposed system the non-invasive BCI technology is used for abstracting the EEG signals to perform movement of the wheelchair, it helps the person with a disability to move from one place to another without the help of a caretaker. The EEG device used for this model is a Brainsense headset with a single electrode and Bluetooth enabled to interface with the computer for simulating the brain signals. The artifact signals such as eye blinking and jaw sneezing are used in this system for giving commands required for moving the wheelchair in the desired direction by the user. Arduino is used for assigning input to the Cytron motor driver which is used to drive the motors for wheelchair movement. In MATLAB a code was developed for showing the visual direction setup with a rotating knob to each direction arrow by highlighting in color with some time delay. When the disabled person wants to move his wheelchair in the required direction the EEG signals developed from that person’s brain in terms of artifact signals will be transmitted to a computer device using the UART method and those signals are processed using MATLAB to send commands to Arduino for moving the wheelchair in the desired direction such as forward, backward, left and right. when the user makes an eyeblink it is captured by the headset and transmitted to the computer device for checking the threshold level to confirm that it is in the range specified level previously in the program or not. If the condition is satisfied, then it transmits the command to Arduino for driving the wheelchair in the desired direction.