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Abstract
Aiming to illuminate the effects of enforced confinements on people’s lives, this paper presents a novel dataset that measures human behaviour holistically and longitudinally during the COVID-19 outbreak. In particular, we conducted a study during the first wave of the lockdown, where 21 healthy subjects from the Netherlands and Greece participated, collecting multimodal raw and processed data from smartphone sensors, activity trackers, and users’ responses to digital questionnaires. The study lasted more than two months, although the duration of the data collection varies per participant. The data are publicly available and can be used to model human behaviour in a broad sense as the dataset explores physical, social, emotional, and cognitive domains. The dataset offers an exemplary perspective on a given group of people that could be considered to build new models for investigating behaviour changes as a consequence of the lockdown. Importantly, to our knowledge, this is the first dataset combining passive sensing, experience sampling, and virtual assistants to study human behaviour dynamics in a prolonged lockdown situation.
Measurement(s) | ‘human behaviour during the COVID-19 outbreak’, ‘human behaviour’, ‘physical behaviour’, ‘social behaviour’, ‘emotional behaviour’, ‘cognitive behaviour’ |
Technology Type(s) | ‘smartphone device’, ‘activity tracker’, ‘digital questionnaires’ |
Sample Characteristic - Organism | ‘human beings’ |
Sample Characteristic - Location | ‘The Netherlands’, ‘Greece’ |
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Details
1 University of Twente, Biomedical Signals and Systems Research Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Enschede, The Netherlands (GRID:grid.6214.1) (ISNI:0000 0004 0399 8953)
2 University of Granada, Research Center for Information and Communication Technologies, Granada, Spain (GRID:grid.4489.1) (ISNI:0000000121678994)
3 Innovation Sprint, Enschede, The Netherlands (GRID:grid.4489.1)