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

被引:5
|
作者
Kraaij, Wessel [1 ,2 ,3 ]
Verberne, Suzan [1 ,3 ]
Koldijk, Saskia [2 ,3 ]
de Korte, Elsbeth [4 ,10 ]
van Dantzig, Saskia [5 ]
Sappelli, Maya [2 ,3 ]
Shoaib, Muhammad [6 ]
Bosems, Steven [6 ]
Achterkamp, Reinoud [6 ]
Bonomi, Alberto [5 ]
Schavemaker, John [2 ]
Hulsebosch, Bob [7 ]
Wabeke, Thymen [2 ]
Vollenbroek-Hutten, Miriam [6 ,8 ,9 ]
Neerincx, Mark [2 ,10 ]
van Sinderen, Marten [6 ]
机构
[1] Leiden Univ, LIACS, Niels Bohrweg 1, Leiden, Netherlands
[2] TNO, The Hague, Netherlands
[3] Radboud Univ Nijmegen, Nijmegen, Netherlands
[4] TNO, Leiden, Netherlands
[5] Philips Res, Eindhoven, Netherlands
[6] Univ Twente, Enschede, Netherlands
[7] Innovalor, Enschede, Netherlands
[8] Ziekenhuisgrp Twente, Hengelo, Netherlands
[9] Roessingh Res & Dev, Enschede, Netherlands
[10] Delft Univ Technol, Delft, Netherlands
关键词
Quantified self; m-Health; Privacy; Behavioural change; Context aware systems; Personalization; ACTIVITY COACHING SYSTEMS; PHYSICAL-ACTIVITY; INFORMATION OVERLOAD; STRESS; ACCELEROMETER; RECOGNITION; TECHNOLOGY; MANAGEMENT; BEHAVIOR; SPORTS;
D O I
10.1007/s11257-019-09238-3
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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 onreasoning: interpreting raw heterogeneous sensor data, andacting: 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.
引用
收藏
页码:413 / 446
页数:34
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