Systematic review of smartphone-based passive sensing for health and wellbeing.

Journal of biomedical informatics(2017)

引用 256|浏览89
暂无评分
摘要
OBJECTIVE:To review published empirical literature on the use of smartphone-based passive sensing for health and wellbeing. MATERIAL AND METHODS:A systematic review of the English language literature was performed following PRISMA guidelines. Papers indexed in computing, technology, and medical databases were included if they were empirical, focused on health and/or wellbeing, involved the collection of data via smartphones, and described the utilized technology as passive or requiring minimal user interaction. RESULTS:Thirty-five papers were included in the review. Studies were performed around the world, with samples of up to 171 (median n = 15) representing individuals with bipolar disorder, schizophrenia, depression, older adults, and the general population. The majority of studies used the Android operating system and an array of smartphone sensors, most frequently capturing accelerometry, location, audio, and usage data. Captured data were usually sent to a remote server for processing but were shared with participants in only 40% of studies. Reported benefits of passive sensing included accurately detecting changes in status, behavior change through feedback, and increased accountability in participants. Studies reported facing technical, methodological, and privacy challenges. DISCUSSION:Studies in the nascent area of smartphone-based passive sensing for health and wellbeing demonstrate promise and invite continued research and investment. Existing studies suffer from weaknesses in research design, lack of feedback and clinical integration, and inadequate attention to privacy issues. Key recommendations relate to developing passive sensing strategies matching the problem at hand, using personalized interventions, and addressing methodological and privacy challenges. CONCLUSION:As evolving passive sensing technology presents new possibilities for health and wellbeing, additional research must address methodological, clinical integration, and privacy issues. Doing so depends on interdisciplinary collaboration between informatics and clinical experts.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要