Cognitive State Assessment

Abstract

This effort investigated the ability of a neurophysiological measure to detect changes in workload during a task which is sensitive to cognitive function. A growing collection of research suggests that physiological measures such as EEG can be used to inform the adaptation of systems. However, it has been proposed that such measures often provide a gross interpretation of cognitive workload during complex tasks and are not sensitive to differences in specific cognitive function. To understand the utility of neurophysiological measures for human-machine interaction, we must know if these measures are sensitive to tasks which are sensitive to changes in cognitive function. To begin to answer this question, we investigated the sensitivity of Advanced Brain Monitoring's EEG-based measures to changes in workload experienced during a Stroop task. Results indicated that ABM's workload measure can detect changes associated with the attentional demands and cognitive processes linked to the ability to inhibit word naming during tasks involving semantic interference. This indicates that changes in workload associated with the ability to inhibit competing cognitive processes can be identified using neurophysiological workload measures.

Examining Positivity Effect and Working Memory in Young-Old and Very Old Adults Using EEG-Derived Cognitive State Metrics

“…Since Berka et al’s (2007) study, ABM’s algorithms have been validated with other cognitive tests (Stroop; Sciarini, Grubb, & Fatolitis, 2014), physical and social states (sleep deprivation, Westbrook et al, 2004; team collaboration, Stevens, Galloway, & Berka, 2006), and populations (athletes, Stikic et al, 2014). It thus becomes possible to use metrics of cognitive state to assess the theory of cognitive resource allocation in YOAs versus VOAs within the context of the positivity effect with emotionally valenced stimuli.…”