Modern devices such as cell phones, handheld computers, and technical equipment enable professional users to communicate, understand, and act more efficiently and effectively. However, these new systems often increase cognitive workload, and may even introduce performance errors. System analysts can decrease these errors by identifying a users cognitive performance deficits and addressing them through training, improved performance support, and redesigned operational systems. To identify these deficits, neurocognitive measurements of indicators such as cognitive workload and attention can be approximated with high accuracy by using non-invasive sensors to measure brain activity and other physiological indicators. Thus, we are designing and demonstrating the feasibility of a toolkit for system analysts to use neurocognitive measurements to recommend additional training for individual users, performance support for all users of the system, and the redesign of system interfaces or components. This research addresses a clear need for an extensible, general-purpose, stand-alone neurocognitive assessment toolkit that can be incorporated into new and existing technology development with little to no integration effort. © 2011 Springer-Verlag.
CITATION STYLE
Niehaus, J., & Weyhrauch, P. (2011). Towards a software toolkit for neurophysiological data collection and analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6780 LNAI, pp. 199–202). https://doi.org/10.1007/978-3-642-21852-1_25
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