Walking by thinking: the brainwaves are crucial, not the muscles!
Presence: Teleoperators and Virtual Environments - Special issue: 8th annual international workshop on presence II
Steady-state VEP-based brain-computer interface control in an immersive 3D gaming environment
EURASIP Journal on Applied Signal Processing
Nessi: an EEG-controlled web browser for severely paralyzed patients
Computational Intelligence and Neuroscience - Brain-Computer Interfaces: Towards Practical Implementations and Potential Applications
Brain-computer interfaces for hci and games
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Designing for uncertain, asymmetric control: Interaction design for brain-computer interfaces
International Journal of Human-Computer Studies
Presence: Teleoperators and Virtual Environments
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Objectives: Brain-computer interfaces (BCIs) are no longer only used by healthy participants under controlled conditions in laboratory environments, but also by patients and end-users, controlling applications in their homes or clinics, without the BCI experts around. But are the technology and the field mature enough for this? Especially the successful operation of applications - like text entry systems or assistive mobility devices such as tele-presence robots - requires a good level of BCI control. How much training is needed to achieve such a level? Is it possible to train naive end-users in 10 days to successfully control such applications? Materials and methods: In this work, we report our experiences of training 24 motor-disabled participants at rehabilitation clinics or at the end-users' homes, without BCI experts present. We also share the lessons that we have learned through transferring BCI technologies from the lab to the user's home or clinics. Results: The most important outcome is that 50% of the participants achieved good BCI performance and could successfully control the applications (tele-presence robot and text-entry system). In the case of the tele-presence robot the participants achieved an average performance ratio of 0.87 (max. 0.97) and for the text entry application a mean of 0.93 (max. 1.0). The lessons learned and the gathered user feedback range from pure BCI problems (technical and handling), to common communication issues among the different people involved, and issues encountered while controlling the applications. Conclusion: The points raised in this paper are very widely applicable and we anticipate that they might be faced similarly by other groups, if they move on to bringing the BCI technology to the end-user, to home environments and towards application prototype control.