TY - JOUR
T1 - COVID-BEHAVE dataset
T2 - measuring human behaviour during the COVID-19 pandemic
AU - Konsolakis, Kostas
AU - Banos, Oresti
AU - Cabrita, Miriam
AU - Hermens, Hermie
N1 - Funding Information:
This work has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement #769553. This result only reflects the author’s view and the EU is not responsible for any use that may be made of the information it contains. This work has also been supported by the Dutch UT-CTIT project HoliBehave.
Funding Information:
This work has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement #769553. This result only reflects the author’s view and the EU is not responsible for any use that may be made of the information it contains. This work has also been supported by the Dutch UT-CTIT project HoliBehave.
Publisher Copyright:
© 2022, The Author(s).
Financial transaction number:
2500039093
PY - 2022/12/6
Y1 - 2022/12/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85143423353&partnerID=8YFLogxK
U2 - 10.1038/s41597-022-01856-8
DO - 10.1038/s41597-022-01856-8
M3 - Article
C2 - 36473876
AN - SCOPUS:85143423353
SN - 2052-4463
VL - 9
JO - Scientific Data
JF - Scientific Data
IS - 1
M1 - 754
ER -
