2010 · 36 citations · 10 references
EngineeringIndustrial EngineeringNeuroscienceCognitive NeuroscienceErgonomicsHuman-computer InteractionBrain-computer InterfacesElectroencephalogram AnalysisElectroencephalographyHuman-machine InteractionHuman-machine InterfacesIndustrial AutomationBrain-computer Interface Signal AcquisitionBrain-computer Interface Signal AnalysisBrain-computer Interface Signal ProcessingBrain-machine InterfacesElectroencephalography-based Brain-computer InterfacesMachine-operator InteractionOperator ErgonomicsPsychophysiological Mechanisms
Brain‑computer interface research has evolved over four decades with sophisticated data‑analysis techniques, yet most studies remain laboratory‑based; recent work is expanding BCI applications toward enhanced human‑machine interaction. The study investigates using neurotechnology to optimize psychophysiological working conditions in industrial settings. The authors applied BCI‑related analysis techniques to evaluate operators’ cognitive processing depth in a real‑world industrial environment. Results indicate that BCI analysis can assess operators’ cognitive depth, enabling assistive technologies that adapt workspaces to real‑time mental states to reduce accidents.
Brain Computer Interface (BCI) research advanced for more than forty years, providing a rich variety of sophisticated data analysis methods. Yet, most BCI studies have been restricted to the laboratory with controlled and undisturbed environment. BCI research was aiming at developing tools for communication and control. Recently, BCI research has broadened to explore novel applications for improved man-machine interaction. In the present study, we investigated the option to employ neurotechnology in an industrial environment for the psychophysiological optimization of working conditions in such settings. Our findings suggest that it is possible to use BCI-related analysis techniques to qualify responses of an operator by assessing the depth of cognitive processing on the basis of neuronal correlates of behaviourally relevant measures. This could lead to assistive technologies helping to avoid accidents in working environments by designing a collaborative workspace in which the environment takes into account the actual cognitive mental state of the operator.
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To See or Not to See: Prestimulus α Phase Predicts Visual Awareness
Kyle E. Mathewson, Gabriele Gratton, Monica Fabiani et al. · Journal of Neuroscience · 2009 · 1.1K citations · Full text
Medicine, Neuroscience, Psychology +17