EEG in Dual-Task Human-Machine Interaction: Target Recognition and Prospective Memory
Elsa Andrea Kirchner, Su-Kyoung Kim
In Proceedings of the 18th Annual Meeting of the Organization for Human Brain Mapping, (OHBM-12), 10.6.-14.6.2012, Beijing, o.A., Jun/2012.

Abstract :

Studies investigating dual-task performance [Isreal et al., 1980] or retrieval of prospective memory (PM) [West 2011] gave insight into the capabilities of the brain to perform tasks in parallel and to switch between tasks [Bisiacchi et al., 2009]. However, most experiments are conducted under controlled conditions. Here, we investigate electroencephalographic (EEG) activity recorded under natural conditions during human-machine interaction (HMI) that can be used to passively support the human [George & Lécuyer 2010] in multi-task situations, e.g. telemanipulation of robotic systems and mission control [Kirchner et al., 2010]. For this passive support, the success of information processing can be predicted with the help of single-trial EEG analysis and classification [Metzen et al., 2011]. A successful execution of multiple tasks requires an efficient strategy of attention division, the detection and evaluation of important, task-relevant information, retrieval of intended action from long-term memory, post-retrieval monitoring, and task-coordination processes characterized by several overlapping event related potentials (ERPs) [West 2011]. The goal of the study was to investigate the effect of multi-task conditions on positive parietal ERP components evoked by infrequent task-relevant and task-irrelevant stimuli.



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