Error Potential detection during driving operations of a powered wheelchair

Modern technologies allow people with motor impairment (e.g., paraplegia and tetraplegia) to improve their general wealth. Among the modern technologies there is one of particular interest, called brain-computer interface (BCI) that directly connect the brain with a machine for the execution of a specific task. This technology can be used to promote the implementation of a brain-controlled wheelchair, which would significantly increase the independence of people suffering from severe motor disabilities. From the literature regarding the employing of the BCI for the assistance of people emerges a lack of studies of an algorithm that can adjust the wheelchair's trajectory if a problem emerges. In order to improve this aspect, we analysed if a specific brain response generated when an unexpected situation occurs (error-related potential (ErrP)) is reliably detectable; the final goal of this research was to create an offline-algorithm for the classification of the brain responses in order to set a baseline for the implementation of a online-algorithm of trajectory correction. The first chapter will present an overview of the BCI and the error-related potential and the possible applications of this technology. In the following chapters it will be highlighted the motivation and main point of focus of our research, along with the experimental protocol, the results obtained and the discussion of the results.