Wheelchair simulator game for training people with severe disabilities

Abstract

People with motor and neurological impairments have little control over parts of their bodies, so they have great difficulty in walking. The development of solutions based on assistive technology dedicated to people with severe motor disabilities can provide accessibility and mobility, the intelligent wheelchair is an example of this type of technology. However, its use without proper training can be dangerous, a wheelchair simulator games can be a good tool for training people with severe disabilities. The EEG signals can be used as a source of information that allows communication between the brain and an intelligent wheelchair. This research aimed to develop a computer model to categorize electroencephalogram signals and control a virtual wheelchair using motor imagery of the left and right wrists, both wrists and both feet. Signs of electroencephalogram were acquired through the eegmmidb database — EEG Motor Movement/Imagery Dataset, captured by the BCI2000 system, and electroencephalogram signal samples from 10 individuals were used to validate the model. The techniques used are promising, making possible its use in three-dimensional simulation environments for intelligent wheelchair controlled by a brain-computer interface.