Heading for new shores! Overcoming pitfalls in BCI design

Abstract

Research in brain-computer interfaces has achieved impressive progress towards implementing assistive technologies for restoration or substitution of lost motor capabilities, as well as supporting technologies for able-bodied subjects. Notwithstanding this progress, effective translation of these interfaces from proof-of concept prototypes into reliable applications remains elusive. As a matter of fact, most of the current BCI systems cannot be used independently for long periods of time by their intended end-users. Multiple factors that impair achieving this goal have already been identified. However, it is not clear how do they affect the overall BCI performance or how they should be tackled. This is worsened by the publication bias where only positive results are disseminated, preventing the research community from learning from its errors. This paper is the result of a workshop held at the 6th International BCI meeting in Asilomar. We summarize here the discussion on concrete research avenues and guidelines that may help overcoming common pitfalls and make BCIs become a useful alternative communication device.

Learning 2-in-1: Towards Integrated EEG-fMRI-Neurofeedback

“…NF studies often report a significant proportion of subjects (usually about 30%) that are not able to self-regulate their brain activity (Alkoby et al, 2018). In the brain-computer-interface (BCI) community this phenomenon is known as BCI-deficiency and might originate from non optimal features, flaws from the design (Lotte et al, 2013;Chavarriaga et al, 2017), but also from anatomo-physiological factors that would make some subjects less responsive to certain modalities (Zich et al, 2015). EEG is the most popular NF modality for it is portable, non-invasive and benefits from millisecond temporal resolution.However, its spatial resolution is limited by volume conduction of the head and the number of electrodes.Also, source localization from EEG is inaccurate because of the ill-posed inverse problem (Grech et al, 2008;Baillet et al, 2001).…”

What if I had a third arm? An EEG study of a supernumerary BCI system

“…The learning task should include an intuitive feedback so that the users can easily understand the action to be executed and improve their performance. However, it is currently hard to choose the right feedback presentation, and it should be a motivating and engaging environment [11], besides being natural and realistic. Here, VR can be shown as a real alternative for tackling the feedback presentation issue.…”

“…Despite BCI being a promising and useful application, there are still several challenges to be addressed. Chavarriaga et al [11] discuss concrete research avenues and guidelines to overcome common pitfalls in BCI. Their paper is the outcome of a meeting held at the workshop “What’s wrong with us?…”

The sixth international brain–computer interface meeting: advances in basic and clinical research

“…Both review work in which a BCI aids recovery from disabling conditions, sometimes producing long-term effects that persist after BCI use is discontinued. The third workshop summary considers the barriers to commercial BCI translation and how they can be overcome [8]. …”