Cerebro

Motor Imagery based control of a 3-DOF arm with haptic feedback integration

The project proposes an approach towards EEG-driven position control of a robot arm by utilizing motor imagery, P300 waveform and Visually evoked Potential to align the robot arm with desired target position. The user produces motor imagery signals to control the motion of the arm. The P300 waveforms gives us sufficient data to detect whether we are performing any motion or even imagining doing so. This becomes even more accurate with C3, C4, PZ, FZ signals coming into picture. Taking these signals as features gives us appropriate information on the motion imagined by the user. This information can be used to control different parameters that are necessary for controlling the arm.

This Project has a lot of Applications. This will facilitate the living of individuals with upper extremity impairment. The Brain-computer interface can act as a medium for them to use robotic arm for the activities of their daily life. Haptic feedback will give them the sense of touch. This can be achieved by giving neuro-feed back to the brain. The haptic feedback can be very helpful when it comes to invasive surgery using robotic arms.