The Swell knowledge work dataset for stress and user modeling research
conference paper
This paper describes the new multimodal SWELL knowl- edge work (SWELL-KW) dataset for research on stress and user modeling. The dataset was collected in an experiment, in which 25 people performed typical knowledge work (writing reports, making presentations, reading e-mail, searching for information). We manipulated their working conditions with the stressors: Email interruptions and time pressure. A varied set of data was recorded: computer logging, facial expression from camera recordings, body postures from a Kinect 3D sensor and heart rate (variability) and skin conductance from body sensors. The dataset made available not only contains raw data, but also preprocessed data and ex- Tracted features. The participants' subjective experience on task load, mental effort, emotion and perceived stress was assessed with validated questionnaires as a ground truth. The resulting dataset on working behavior and affect is a valuable contribution to several research fields, such as work psychology, user modeling and context aware systems. Copyright 2014 ACM.
TNO Identifier
529702
DOI
https://dx.doi.org/10.1145/2663204.2663257
Publisher
Association for Computing Machinery, Inc
Source title
16th ACM International Conference on Multimodal Interaction, ICMI 2014, 12-16 November 2014, Istanbul, Turkey
Place of publication
New York, NY
Pages
291-298
Files
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