Abstract 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 longitudinal studies can now be initiated to assess the effectiveness of m-Health interventions using the SWELL methods.

中文翻译：

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对工作幸福感的个性化支持：SWELL 项目概述

摘要 可穿戴传感器技术和智能手机的最新进展实现了简单且经济实惠的个人分析收集。本文反映了 SWELL 项目的经验教训，该项目涉及设计以用户为中心的 ICT 应用程序，以实现知识工作者领域活力的自我管理。这些工人通常有久坐不动的生活方式，并且由于工作量大而容易受到心理健康影响。我们提出了作为 SWELL 方法基础的感觉-理由-行为框架，并概述了在 SWELL 中进行的个别研究。在本文中，我们重新审视了我们在推理方面的工作：解释原始异构传感器数据和行动：提供个性化反馈以支持行为改变。我们得出的结论是，简单且价格合理的传感器可用于以物理非侵入性的方式对用户行为和健康状态进行分类。解释的数据可用于通知个性化反馈策略。现在可以启动进一步的纵向研究，以评估使用 SWELL 方法的移动健康干预措施的有效性。