A brain-computer interface (BCI) directly uses brain-activity signals to allow users to operate the environment without any muscular activation. Thanks to this feature, BCI systems can be employed not only as assistive devices, but also as neurorehabilitation tools in clinical settings. However, several critical issues need to be addressed before using BCI in neurorehabilitation, issues ranging...

The notion of semi-BCI algebras is introduced and some of its properties are investigated. This algebra is another generalization for BCI-algebras. It arises from the “intervalization” of BCI algebras. Semi-BCI have a similar structure to Pseudo-BCI algebras however they are not the same. In this paper we also provide an investigation on the similarity between these classes of algebras by showi...

In summary, the incidence of BCI following blunt thoracic trauma patients has been reported between 20% and 76%, and no gold standard exists to diagnose BCI. Diagnostic tests should be limited to identify those patients who are at risk of developing cardiac complications as a result of BCI. Therapeutic interventions should be directed to treat the complications of BCI. Finally, the prognosis an...

OBJECTIVES We study the applicability of a visual P3-based and a Steady State Visually Evoked Potentials (SSVEP)-based Brain-Computer Interfaces (BCIs) for mental text spelling on a cohort of patients with incomplete Locked-In Syndrome (LIS). METHODS Seven patients performed repeated sessions with each BCI. We assessed BCI performance, mental workload and overall satisfaction for both systems...

Purpose: Previous results from the TransATAC study demonstrated that both the Breast Cancer Index (BCI) and the OncotypeDX Recurrence Score (RS) added significant prognostic information to clinicopathologic factors over a 10-year period. Here, we examined cross-stratification between BCI and RS to directly compare their prognostic accuracy at the individual patient level. Experimental Design: A...

While recent research on Brain-Computer Interfaces (BCI) has highlighted their potential for many applications, they remain barely used outside laboratories. The main reason is their lack of robustness. Indeed, with current BCI, mental state recognition is usually slow and often incorrect. Spontaneous BCI (i.e., mental imagery-based BCI) often rely on mutual learning efforts by the user and the...

Co-adaptive training paradigms for event-related desynchronization (ERD) based brain-computer interfaces (BCI) have proven effective for healthy users. As of yet, it is not clear whether co-adaptive training paradigms can also benefit users with severe motor impairment. The primary goal of our paper was to evaluate a novel cue-guided, co-adaptive BCI training paradigm with severely impaired vol...

Brain-Computer Interface (BCI) research and (future) applications raise important ethical issues that need to be addressed to promote societal acceptance and adequate policies. Here we report on a survey we conducted among 145 BCI researchers at the 4th International BCI conference, which took place in May-June 2010 in Asilomar, California. We assessed respondents' opinions about a number of to...

Due to the non-stationarity of EEG signals, online training and adaptation is essential to EEG based brain-computer interface (BCI) systems. Asynchronous BCI offers more natural human-machine interaction, but it is a great challenge to train and adapt an asynchronous BCI online because the user’s control intention and timing are usually unknown. This paper proposes a novel motor imagery based a...