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mHealth through quantified-self: a user study

机译:MHEALT通过量化 - 自我:用户学习

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摘要

We describe a user study of a mHealth prototype system based on a wellbeing scenario, exploiting the quantified-self approach to measurement and monitoring. We have used off-the-shelf equipment, with opensource, web-based, software, and exploiting the increasing popularity of smartphones and self-measurement devices in a user study. We emulate a mHealth scenario as a pre-clinical experiment, as a realistic alternative to a clinical scenario, with reduced risk to sensitive patient medical data. We discuss the efficacy of this approach for future mHealth systems for remote monitoring. Our system used the popular Fitbit device for monitoring personal wellbeing data, the Diaspora online social media platform (OSMP), and a simple Android/iOS remote notification application. We implemented remote monitoring, asynchronous user interaction, multiple actors, and user-controlled security and privacy mechanisms. We propose that the use of a quantified-self approach to mHealth is particularly valuable to undertake research and systems development.
机译:我们描述了基于福利场景的MHEAPH Prototype系统的用户研究,利用量化自我方法来测量和监测。我们已经使用了现成的设备,具有openSource,基于Web,软件,并利用用户学习中的智能手机和自测设备的越来越普及。我们将MHEPHEATH情景作为临床前实验,作为临床情景的现实替代品,敏感患者医疗数据的风险降低。我们讨论了这种方法对远程监控未来MHEATH系统的功效。我们的系统使用了流行的Fitbit设备,用于监控个人幸福数据,Diaspora在线社交媒体平台(OSMP)和简单的Android / IOS远程通知应用程序。我们实现了远程监控,异步用户交互,多个演员和用户控制的安全性和隐私机制。我们建议使用量化的自我方法来进行MHEALT,特别有价值的研究和系统发展。

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