Bacteria Hunt: A multimodal, multiparadigm BCI game

Brain-Computer Interfaces (BCIs) allow users to control applications by brain activity. Among their possible applications for non-disabled people, games are promising candidates. BCIs can enrich game play by the mental and affective state information they contain. During the eNTERFACE’09 workshop we developed the Bacteria Hunt game which can be played by keyboard and BCI, using SSVEP and relative alpha power. We conducted experiments in order to investigate what difference positive vs. negative neurofeedback would have on subjects’ relaxation states and how well the different BCI paradigms can be used together. We observed no significant difference in mean alpha band power, thus relaxation, and in user experience between the games applying positive and negative feedback. We also found that alpha power before SSVEP stimulation was significantly higher than alpha power during SSVEP stimulation indicating that there is some interference between the two BCI paradigms

Programming Robots With Events

International audienceWe introduce how to use event-based style to program robots through the INI programming language. INI features both built-in and user-defined events, a mechanism to handle various kinds of changes happening in the environment. Event handlers run in parallel either synchronously or asynchronously, and events can be reconfigured at runtime to modify their behavior when needed. We apply INI to the humanoid robot called Nao, for which we develop an object tracking program

Employing electro-mechanical analogies for co-resonantly coupled cantilever sensors

Understanding the behaviour of mechanical systems can be facilitated and improved by employing electro-mechanical analogies. These analogies enable the use of network analysis tools as well as purely analytical treatment of the mechanical system translated into an electric circuit. Recently, we developed a novel kind of sensor set-up based on two coupled cantilever beams with matched resonance frequencies (co-resonant coupling) and possible applications in magnetic force microscopy and cantilever magnetometry. In order to analyse the sensor's behaviour in detail, we describe it as an electric circuit model. Starting from a simplified coupled harmonic oscillator model with neglected damping, we gradually increase the complexity of the system by adding damping and interaction elements. For each stage, various features of the coupled system are discussed and compared to measured data obtained with a co-resonant sensor. Furthermore, we show that the circuit model can be used to derive sensor parameters which are essential for the evaluation of measured data. Finally, the much more complex circuit representation of a bending beam is discussed, revealing that the simplified circuit model of a coupled harmonic oscillator is a very good representation of the sensor system

Brain-Computer Interface Games: Towards a Framework

The brain-computer interface (BCI) community started to consider games as potential applications while the games community started to consider BCI as a game controller. However, there is a discrepancy between the BCI games developed by the two communities. In this paper, we propose a preliminary BCI games framework that we constructed with respect to the research conducted in both the BCI and the games communities. Developers can situate their BCI games within this framework and benefit from the guidelines we provide and also extend the framework further

Are super-face-recognisers also super-voice-recognisers? Evidence from cross-modal identification tasks

Individual differences in face identification ability range from prosopagnosia to super-recognition. The current study examined whether face identification ability predicts voice identification ability (participants: N = 529). Superior-face-identifiers (exceptional at face memory and matching), superior-face-recognisers (exceptional at face memory only), superior-face-matchers (exceptional face matchers only), and controls completed the Bangor Voice Matching Test, Glasgow Voice Memory Test, and a Famous Voice Recognition Test. Meeting predictions, those possessing exceptional face memory and matching skills outperformed typical-range face groups at voice memory and voice matching respectively. Proportionally more super-face-identifiers also achieved our super-voice-recogniser criteria on two or more tests. Underlying cross-modality (voices vs. faces) and cross-task (memory vs. perception) mechanisms may therefore drive superior performances. Dissociations between Glasgow Voice Memory Test voice and bell recognition also suggest voice-specific effects to match those found with faces. These findings have applied implications for policing, particularly in cases when only suspect voice clips are available

BNCI Horizon 2020 - Towards a Roadmap for Brain/Neural Computer Interaction

In this paper, we present BNCI Horizon 2020, an EU Coordination and Support Action (CSA) that will provide a roadmap for brain-computer interaction research for the next years, starting in 2013, and aiming at research efforts until 2020 and beyond. The project is a successor of the earlier EU-funded Future BNCI CSA that started in 2010 and produced a roadmap for a shorter time period. We present how we, a consortium of the main European BCI research groups as well as companies and end user representatives, expect to tackle the problem of designing a roadmap for BCI research. In this paper, we define the field with its recent developments, in particular by considering publications and EU-funded research projects, and we discuss how we plan to involve research groups, companies, and user groups in our effort to pave the way for useful and fruitful EU-funded BCI research for the next ten years