Long-Term Stable Control of Motor-Imagery BCI by a Locked-In User Through Adaptive Assistance

Abstract

Abstract-Performance variation is one of the main challenges that BCIs are confronted with, when being used over extended periods of time. Shared control techniques could partially cope with such a problem. In this paper, we propose a taxonomy of shared control approaches used for BCIs and we review some of the recent studies at the light of these approaches. We posit that the level of assistance provided to the BCI user should be adjusted in real time in order to enhance BCI reliability over time. This approach has not been extensively studied in the recent literature on BCIs.In addition, we investigate the effectiveness of providing online adaptive assistance in a motor-imagery BCI for a tetraplegic enduser with an incomplete locked-in syndrome in a longitudinal study lasting 11 months. First, we report a reliable estimation of the BCI performance (in terms of command delivery time) using only a window of 1 s in the beginning of trials (AUC≈ 0.8). Second, we demonstrate how adaptive shared control can exploit the output of the performance estimator to adjust online the level of assistance in a BCI game by regulating its speed. In particular, online adaptive assistance was superior to a fixed condition in terms of success rate (p < 0.01). Remarkably, the results exhibited a stable performance over several months without recalibration of the BCI classifier or the performance estimator.

Neural mechanisms of training an auditory event‐related potential task in a brain–computer interface context

“…Based on the current study, no conclusions can be drawn concerning the effects of long-term training with BCIs (Saeedi, Chavarriaga, & Millan, 2017), as only three sessions were conducted.…”

“…Aptitude prediction and conjunction analysis of P300 and motor imagery data further highlighted the importance of the SMA for BCI control, thus training and/or stimulation of this region may lead to increased performance. Based on the current study, no conclusions can be drawn concerning the effects of long‐term training with BCIs (Saeedi, Chavarriaga, & Millan, ), as only three sessions were conducted.…”

Heading for new shores! Overcoming pitfalls in BCI design

“…Recent works both with able-bodied subjects and one end-user with locked-in syndrome have proposed methods to assess performance variation within a session and during runtime. They may help to better assess the suitability of a given BCI approach, and to provide user-specific support during the training periods [29,30]. …”

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

“…Given this constraint, an alternative is to privilege long-term studies over these small populations [54]. Such studies, although demanding, give a better assessment of how a BMI will work in its intended operational conditions [55,56]. Nonetheless, care should be taken to choose appropriate experimental protocols and analysis approaches for studies with small N, and results should not be interpreted as generalizable to larger populations.…”