a Gaussian classifier [10]. Decisions with a confidence on the probability distribution that are below a given rejection threshold are filtered out. Finally, evidence about the executed task is accumulated using an exponential smoothing probability integration framework [11]. This helps to prevent commands from being delivered accidentally. GND 1 Fz Wheelchair Hardware Our brain-controlled wheelchair is based on 2 4 5 6 3 a commercially available mid-wheel drive FC3 FC1 FCz FC2 FC4 model by Invacare Corporation. We have 7 8 9 10 11 made the following modifications, which C3 C1 Cz C2 C4 allow us to control the wheelchair directly 13 14 15 12 16 from a laptop computer. CP2 CPz CP1 CP3 CP4 1) We developed a remote joystick module that acts as an interface between a laptop REF computer and the wheelchair's CANBUSbased control network. 2) We added a pair of wheel-encoders to the central driving wheels to provide the wheelchair with feedback about its own motion. 3) We added an array of ten sonar sensors and two webcams to the wheelchair to provide environmental feedback to the Figure 1. The active electrode placement over the motor cortex for the acquisition of EEG controller. data based on the international 10-20 system. (The triangle at the top represents the nose.) 4) We mounted an adjustable 8-in display to provide visual feedback to the user. 5) We built a power distribution unit to hook up all the two webcams are positioned facing forward directly above sensors, the laptop, and the display to the wheelchair's each of the front castor wheels. batteries. The complete BCI wheelchair platform is shown in Wheel Encoders Figure 2. The positions of the sonars are indicated by the The encoders return 128 ticks per revolution and are geared white dots in the center of the occupancy grid, whereas the up to the rim of the drive wheels, resulting in a resolution of Probability of Free Space User Feedback Sonars Green > 70% Black 30-70% Red < 30% BCI Feedback Bar (Top) Occupancy Grid Camera Streams with Detected Obstacles Highlighted Figure 2. The complete brain-actuated wheelchair. The wheelchair's knowledge of the environment is acquired by the fusion of complementary sensors and is represented as a probabilistic occupancy grid. The user is given feedback about the current status of the BCI and about the wheelchair's knowledge of the environment. March 2013 * IEEE ROBOTICS & AUTOMATION MAGAZINE * 67