The Air Force Research Laboratory has implemented and evaluated two brain-computer interfaces (BCI's) that translate the steadystate visual evoked response into a control signal for operating a physical device or computer program. In one approach, operators self-regulate the brain response; the other approach uses multiple evoked responses.

Research indicates that coactors performing cooperative tasks often exhibit spontaneous and unintended similarities in their physiological and behavioral responses--a phenomenon referred to here as physio-behavioral coupling (PBC). The purpose of this research was to identify contributors to PBC; examine relationships between PBC, team performance, and perceived team attributes (e.g., cohesion, trust); and compare a set of time-series measures(cross-correlation [CC], cross-recurrence quantification analysis [CRQA], and cross-fuzzy entropy [CFEn]) in their characterization of PBC across comparisons. To accomplish this, PBC was examined in human postural sway (PS) and cardiac interbeat intervals (IBIs) from dyadic teams performing a fast-paced puzzle task (Quadra--a variant of the video game Tetris). Results indicated that observed levels of PBC were not a chance occurrence, but instead driven by features of the team-task environment, and that PBC was likely influenced by similar individual task demands and interpersonal coordination dynamics that were not "unique" to a particular team. Correlation analysis revealed that PBC exhibited negative relationships with team performance and team attributes, which were interpreted to reflect complementary coordination (as opposed to mimicry) during task performance, potentially due to differentiated team roles. Finally, qualitative comparison of time-series measures used to characterize PBC indicated that CRQA percent recurrence and CFEn (both nonlinear measures) settled on mostly analogous characterizations, whereas linear CC did not. The disparity observed between the linear and nonlinear measures highlights underlying computational and interpretational differences between the two families of statistics and supports the use of multiple metrics for characterizing PBC.

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The increase in performance and decrease in workload associated with augmentation is an important and anticipated finding. This suggests that augmentation should only be provided when it is truly needed, especially if the augmentation requires additional assets and/or resources.Gruenwald CM, Middendorf MS, Hoepf MR, Galster SM. Augmenting human performance in remotely piloted aircraft. Aerosp Med Hum Perform. 2018; 89(2):115-121.

Electroencephalographic(EEG)-based control devices are one of several emerging technologies that will provide operators with a variety of new hands-free control options. In general, EEG-based control translates brain electrical activity into a control signal. The system evaluated in this study uses the steady-state visual evoked response for system control. The luminance of selectable items on a computer display was modulated at different frequencies. The operator's choice between these items was identified by detecting which frequency pattern was dominant in the visual evoked brain activity.One objective of this study was to characterize the performance of this human-machine system. In addition, two candidate control frequencies were evaluated. The results are encouraging. Participants were able to use this form of EEG-based control and performance was stable. Participants averaged over 90 percent correct selections. Future development will focus on increasing the speed and accuracy with which this novel hands-free controller can be utilized.