Toward a Hybrid Passive BCI for the Modulation of Sustained Attention Using EEG and fNIRS - Karran, Alexander J.; Demazure, Théophile; Leger, Pierre-Majorique; Labonte-LeMoyne, Elise; Senecal, Sylvain; Fredette, Marc; Babin, Gilbert (Frontiers in Human Neuroscience, 2019)
We report results of a study that utilises a BCI to drive an interactive interface countermeasure that allows users to self-regulate sustained attention while performing an ecologically valid, long-duration business logistics task. An engagement index derived from EEG signals was used to drive the BCI while fNIRS measured haemodynamic activity for the duration of the task. Participants (n=30) were split into three groups 1) no countermeasures (NOCM), 2) continuous countermeasures (CCM), and 3) event synchronised, level-dependent countermeasures (ECM). We hypothesised that the ability to self-regulate sustained attention through a neurofeedback mechanism would result in greater task engagement, decreased error rate and improved task performance. Data were analysed by wavelet coherence analysis, statistical analysis, performance metrics and self-assessed cognitive workload via RAW-TLX. We found that when the BCI was used to deliver continuous interface countermeasures (CCM), task performance was moderately enhanced in terms of total 14,785 (σ = 423) and estimated missed sales 7.46% (σ = 1.76) when compared to the NOCM 14,529 (σ = 510), 9.79% (σ = 2.75), and the ECM 14,180 (σ = 875), 9.62% (σ = 4.91) groups. An “actions per minute” (APM) metric was used to determine interface interaction activity which showed that overall the CCM and ECM groups had a higher APM of 3.460 (se =0.140) and 3.317 (se =0.139) respectively when compared with the NOCM group 2.65 (se =0.097). Statistical analysis showed a significant difference between ECM - NOCM and CCM - NOCM (p<0.001) groups, but no significant difference between the ECM - CCM groups. Analysis of the RAW-TLX scores showed that the CCM group had lowest total score 7.27 (σ = 3.1), when compared with the ECM 9.7 (σ = 3.3) and NOCM 9.2 (σ = 3.4) groups. No statistical difference was found between the RAW-TLX or the subscales, except for self-perceived performance (p <0.028) comparing the CCM and ECM groups. The results suggest that providing a means to self-regulate sustained attention has the potential to keep operators engaged over long periods, and moderately increase on-task performance while decreasing on-task error.