Human factors engineering for mobile health applications

Chad Snyder, J. Christen, H. M. Ross
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引用次数: 3

Abstract

Childhood asthma has effectively doubled since 1980 and currently affects about 8% of the U.S. childhood population. Efficiently analyzing quality of air data, which would ultimately improve the information available to parents with children suffering from asthma, is crucial to reduce the likelihood of a serious attack. In order to accomplish this task, the use of low-cost, wearable, environmental sensors contribute to construct a live “air-care” pollution map. Creating an alpha prototype application to gauge how well participants interact with and interpret healthcare information utilizing a “Wizard of Oz” paradigm becomes an important component in the research.
移动医疗应用的人为因素工程
自1980年以来,儿童哮喘实际上翻了一番,目前影响了约8%的美国儿童人口。有效地分析空气数据的质量对降低严重哮喘发作的可能性至关重要,这将最终改善哮喘患儿家长可获得的信息。为了完成这项任务,使用低成本、可穿戴的环境传感器有助于构建实时的“空气护理”污染地图。创建alpha原型应用程序来衡量参与者如何使用“绿野仙踪”范式与医疗保健信息进行交互和解释,这成为研究中的一个重要组成部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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