Towards ambulatory brain-computer interfaces

Lotte, Fabien; Fujisawa, Junya; Touyama, Hideaki; Ito, Ryota; Hirose, Michitaka; Lécuyer, Anatole

doi:10.1145/1690388.1690452

Cited by 45 publications

(35 citation statements)

References 11 publications

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“…In particular, when we consider BCI in such social contexts, we hope to have shown the importance of reinstating the social organisation of bodily and mindful behaviour in our understanding and analysis of these technologies. Given the potential for bodily movement to both facilitate and inhibit BCI control [21,24], understanding the circumstances of this action has consequences for thinking about the application of BCI design in these contexts. As Nijholt et al [24] argue, shortcomings and idiosyncratic characteristics of BCI can be incorporated into game challenges by design.…”

Section: Resultsmentioning

confidence: 99%

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Embodiment in brain-computer interaction

O’Hara

Sellen

Harper

2011

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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With emerging opportunities for using Brain-Computer Interaction (BCI) in gaming applications, there is a need to understand the opportunities and constraints of this interaction paradigm. To complement existing laboratorybased studies, there is also a call for the study of BCI in real world contexts. We present such a real world study of a simple BCI game called MindFlex ® , played as a social activity in the home. In particular, drawing on the philosophical traditions of embodied interaction, we highlight the importance of considering the body in BCI and not simply what is going on in the head. The study shows how people use bodily actions to facilitate control of brain activity but also to make their actions and intentions visible to, and interpretable by, others playing and watching the game. It is the public availability of these bodily actions during BCI that allows action to be socially organised, understood and coordinated with others and through which social relationships can be played out. We discuss the implications of this perspective and findings for BCI.

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Section: Resultsmentioning

confidence: 99%

“…For example, from a pragmatic perspective, bodily movements and muscle artefacts can influence EEG signals [e.g. 21]. Within a social context, too, these accompanying actions are of additional significance.…”

Section: Bci and Embodied Interactionmentioning

confidence: 99%

Embodiment in brain-computer interaction

O’Hara

Sellen

Harper

2011

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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“…For instance, many of the limitations mentioned above are currently being addressed by the BCI community and improvements can be expected in the relatively short term. More precisely, some preliminary results suggested that BCI could be used by a mobile user [12], although this makes the recognition performances slightly lower. Some efforts have also be made to reduce or suppress the calibration time with a minimal (but, unfortunately not null) performance loss [10] [5].…”

Section: Hope: Promising Perspectivesmentioning

confidence: 99%

Brain-computer interfaces for 3D games

Lotte

2011

Proceedings of the 6th International Conference on Foundations of Digital Games

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Brain-Computer Interfaces (BCI) are communication systems conveying messages through brain activity only. This paper elaborates on the suitability of BCI for 3D Video Games (VG). Thus, we first review some recent BCI-based 3D VG. We then discuss the limitations of current BCI technology, those being mainly related to usability and performances. Finally, we report on some areas in which BCI could be useful for 3D VG despite their limitations. More precisely, BCI could be useful as an additional control channel, to send commands that cannot be intuitively sent with other devices. BCI could also be used for mental state monitoring either 1) during the game, in order to make adaptive and dynamic video games or 2) during the game creation in order to maximizes some measures of game quality that could be derived from a tester's mental state.

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“…Lotte, et al [6] investigated the feasibility of using an EEG system based on P300 signals with a moving subject. They found that it was possible to detect the P300 signal while sitting, standing or walking.…”

Section: A Realistic Bci Settingsmentioning

confidence: 99%

Classifying motor imagery in presence of speech

Gürkök

Poel

Zwiers

2010

The 2010 International Joint Conference on Neural Networks (IJCNN)

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Abstract-In the near future, brain-computer interface (BCI) applications for non-disabled users will require multimodal interaction and tolerance to dynamic environment. However, this conflicts with the highly sensitive recording techniques used for BCIs, such as electroencephalography (EEG). Advanced machine learning and signal processing techniques are required to decorrelate desired brain signals from the rest. This paper proposes a signal processing pipeline and two classification methods suitable for multiclass EEG analysis. The methods were tested in an experiment on separating left/right hand imagery in presence/absence of speech. The analyses showed that the presence of speech during motor imagery did not affect the classification accuracy significantly and regardless of the presence of speech, the proposed methods were able to separate left and right hand imagery with an accuracy of 60%. The best overall accuracy achieved for the 5-class separation of all the tasks was 47% and both proposed methods performed equally well. In addition, the analysis of event-related spectral power changes revealed characteristics related to motor imagery and speech.

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Towards ambulatory brain-computer interfaces

Cited by 45 publications

References 11 publications

Embodiment in brain-computer interaction

Embodiment in brain-computer interaction

Brain-computer interfaces for 3D games

Classifying motor imagery in presence of speech

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