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Artif Intell Med. 2013 Oct;59(2):121-32. doi: 10.1016/j.artmed.2013.08.004. Epub 2013 Sep 13.

Transferring brain-computer interfaces beyond the laboratory: successful application control for motor-disabled users.

Author information

1
Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Station 11, CH-1015 Lausanne, Switzerland(1). Electronic address: robert.leeb@epfl.ch.

Abstract

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 naïve 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.

KEYWORDS:

Application control; Brain–computer interface (BCI); Electroencephalogram (EEG); End-user; Motor imagery; Technology transfer

PMID:
24119870
DOI:
10.1016/j.artmed.2013.08.004
[Indexed for MEDLINE]
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