Brain-Computer Interface Controlled Robotic Arm to Improve Quality of Life

Abstract

Brain-Computer Interface (BCI) systems can be used to perform daily life actions by utilizing brain activity to distinguish between different commands. For example, a robotic arm controlled with BCI. A robotic arm can allow patients diagnosed with Amyotrophic lateral sclerosis (ALS), Locked in syndrome (LIS), or any other neurodegenerative disease to grip objects and move them around the area. This system can potentially be used to perform a variety of useful tasks such as opening doors, picking up objects and to restore a level of everyday function. The presented system utilizes Electroencephalography (EEG) signals to create a BCI which can control a robotic arm. Specifically, Steady State Visual Evoked Potential (SSVEP) based signals are captured from a user's brain to serve as the controller for three servo motors. The user is presented with three sets of LEDs with different frequencies to distinguish between each of the three degrees of freedom (DOF). The frequencies and servos are paired in the following manner: 7 Hz => servo 1, 11 Hz => servo 2, and 15 Hz => servo 3. Servo 1 changes the orientation of the arm, servo 2 changes the angle of the claw, and servo 3 controls the opening and gripping of the claw. The first experiment is intended for the subjects to get familiar with the system by attempting to activate each of the three servos ten times. The subjects were able to complete this experiment with an average accuracy of 85.56%. The final experiment allowed the subjects to perform a more essential task, which is swapping the items at two locations. On average, the subjects were able to complete the swap experiment in 4:31 minutes.