Abstract
In a Mental Imagery Brain-Computer Interface the user has to perform a specific mental task that generates electroencephalography (EEG) components, which can be translated in commands to control a BCI system. The development of a high-performance MI-BCI requires a long training, lasting several weeks or months, in order to improve the ability of the user to manage his/her mental tasks. This works aims to present the design of a MI-BCI combining mental imaginary and cognitive tasks for a severely motor impaired user, involved in the BCI race of the Cybathlon event, a competition of people with severe motor disability. In the BCI-race, the user becomes a pilot in a virtual race game against up to three other pilots, in which each pilot has to control his/her virtual car by his/her mental tasks. We present all the procedures followed to realize an effective MI-BCI, from the user's first contact with a BCI technology to actually controlling a video-game through her EEG. We defined a multi-stage user-centered training protocol in order to successfully control a BCI, even in a stressful situation, such as that of a competition. We put a specific focus on the human aspects that influenced the long training phase of the system and the participation to the competition.
Highlights
Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) control an external device by specific EEG components generated by mental imagery tasks performed by the user (Pfurtscheller and Neuper, 2001)
We present the sequence of procedures we followed to realize an effective MI-BCI, from the selection of the pilot to the actual control of the video-game in the BCI Cybathlon series, with a particular focus on the long training phase
Pilot selection started by asking Dr Mariane Bruno of the Pasteur University Hospital in Nice, France, to present to us some of her patients with the disabilities listed by the Cybathlon competition, who would be both motivated and physically able to sustain the competition and its constraints
Summary
Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) control an external device by specific EEG components generated by mental imagery tasks performed by the user (Pfurtscheller and Neuper, 2001). Sensorimotor rhythms (SMRs) modulate the power of the ongoing EEG signal over sensorimotor areas (i.e., mu-rhythm and beta-rhythm) (Yuan and He, 2014) They occur during mental imagery tasks, such as mental arithmetic or mental rotation (Faradji et al, 2009) and motor imagery (Neuper et al, 2006) (Wang et al, 2020). Long Multi-Stage Training for BCI Competition vary over time and across subjects, affecting the performance of MI-BCI systems. Another important parameter impacted by this variability is the design of a MI-BCI for an impaired subject. We defined a multi-stage user-centered training protocol in order to successfully control a BCI, even in a stressful situation, such as that of a competition
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