Brain-computer interface games for hedonic experiences

People enjoy the challenge of controlling computer games using brain signals measured by electrodes in contact with their scalp

User Experience Evaluation in BCI: Filling the Gap

Brain-computer interface (BCI) systems can improve the user experience (UX) when used in entertainment technologies. Improved UX can enhance user acceptance, improve quality of life and also increase the system performance of a BCI system. Therefore, the evaluation of UX is essential in BCI research. However, BCI systems are generally evaluated according to the system aspect only so there is no methodology to evaluate UX in BCI systems. This paper gives an overview of such methods from the human-computer interaction field and discusses their possible uses in BCI research

Evaluating user experience with respect to user expectations in brain-computer interface games

Evaluating user experience (UX) with respect to previous experiences can provide insight into whether a product can positively aect a user's opinion about a technology. If it can, then we can say that the product provides a positive UX. In this paper we propose a method to assess the UX in BCI systems with respect to user expectations. We demonstrate the application of our method in a preliminary study. The study results showed that BCI game control was natural and enjoyable despite the low reliability of the BCI. However SSVEP based selection induced fatigue on participants. The proposed method can extract the right and wrong practices to employ BCI in applications and can suggest interaction paradigms or considerations to follow when developing BCI systems

A graph based approach to estimating lexical cohesion

Traditionally, information retrieval systems rank documents according to the query terms they contain. However, even if a document may contain all query terms, this does not guarantee that it is relevant to the query. The query terms can occur together in the same document, but may have been used in different contexts, expressing separate topics. Lexical cohesion is a characteristic of natural language texts, which can be used to determine whether the query terms are used in the same context in the document. In this paper we make use of a graph-based approach to capture term contexts and estimate the level of lexical cohesion in a document. To evaluate the performance of our system, we compare it against two benchmark systems using three TREC document collections. Copyright 2008 ACM

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

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