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Mariam Hassib, Mohamed Khamis, Susanne Friedl, Stefan Schneegass, Florian Alt
BrainAtWork: Logging Cognitive Engagement and Tasks in the Workplace using Electroencephalography
In MUM '17: Proceedings of the 16th International Conference on Mobile and Ubiquitous Multimedia (bib)

Todayâs workplaces are dynamic and complex. Digital data sources such as email and video conferencing aim to support workers but also add to their burden of multitasking. Psychophysiological sensors such as Electroencephalography (EEG) can provide users with cues about their cognitive state. In this note, we introduce BrainAtWork, a workplace engagement and task logger which shows users their cognitive state while working on different tasks. In a lab study with eleven participants working on their own real-world tasks, we gathered 16 hours of EEG and PC logs which were labeled into three classes of work: central, peripheral and meta work. We evaluated the usability of the different features of BrainAtWork via questionnaires and interviews. We used EEG data and experience sampling probes to investigate the correlations between subjective responses and measured cognitive engagement. Using a random forests classifier, we show the feasibility of automatically labeling work tasks into work classes using EEG in a workplace setting. We discuss how BrainAtWork can support workers on the long term through encouraging reflection and helping in task scheduling.