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
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
To receive the publication files, please send an e-mail request to TNO Repository.