Leiden University Scholarly Publications

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Kraaij, W.; Verberne, S.; Koldijk, S.; Korte, E. de; Dantzig, S. van; Sappelli, M.; ... ; Sinderen, M. van (2019)

Personalized support for well-being at work: an overview of the SWELL project

Article / Letter to editor
Recent advances in wearable sensor technology and smartphones enable simple and affordable collection of personal analytics. This paper reflects on the lessons learned in the SWELL project that addressed the design of user-centered ICT applications for self-management of vitality in the domain of knowledge workers. These workers often have a sedentary lifestyle and are susceptible to mental health effects due to a high workload. We present the sense–reason–act framework that is the basis of the SWELL approach and we provide an overview of the individual studies carried out in SWELL. In this paper, we revisit our work on reasoning: interpreting raw heterogeneous sensor data, and acting: providing personalized feedback to support behavioural change. We conclude that simple affordable sensors can be used to classify user behaviour and heath status in a physically non-intrusive way. The interpreted data can be used to inform personalized feedback strategies. Further...Show moreRecent advances in wearable sensor technology and smartphones enable simple and affordable collection of personal analytics. This paper reflects on the lessons learned in the SWELL project that addressed the design of user-centered ICT applications for self-management of vitality in the domain of knowledge workers. These workers often have a sedentary lifestyle and are susceptible to mental health effects due to a high workload. We present the sense–reason–act framework that is the basis of the SWELL approach and we provide an overview of the individual studies carried out in SWELL. In this paper, we revisit our work on reasoning: interpreting raw heterogeneous sensor data, and acting: providing personalized feedback to support behavioural change. We conclude that simple affordable sensors can be used to classify user behaviour and heath status in a physically non-intrusive way. The interpreted data can be used to inform personalized feedback strategies. Further longitudinal studies can now be initiated to assess the effectiveness of m-Health interventions using the SWELL methods.
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All authors
Kraaij, W.; Verberne, S.; Koldijk, S.; Korte, E. de; Dantzig, S. van; Sappelli, M.; Shoaib, M.; Bosems, S.; Achterkamp, R.; Bonomi, A.; Schavemaker, J.; Hulsebosch, B.; Wabeke, T.; Vollenbroek-Hutten, M.; Neerincx, M.; Sinderen, M. van
Date
2019-06-20
Journal
User Modeling and User-Adapted Interaction
Volume
30
Pages
413 - 446
DOI
doi:10.1007/s11257-019-09238-3