Wearable activity trackers, accuracy, adoption, acceptance and health impact: A systematic literature review

活动追踪器 可穿戴计算机 斯科普斯 可穿戴技术 计算机科学 BitTorrent跟踪器 科学网 体力活动 数字图书馆 数据科学 梅德林 医学 荟萃分析 人工智能 内科学 法学 诗歌 嵌入式系统 艺术 文学类 物理医学与康复 眼动 政治学
作者
Grace Shin,Mohammad Hossein Jarrahi,Fei Yu,Amir Karami,Nicci Gafinowitz,Ahjung Byun,Xiaopeng Lu
出处
期刊:Journal of Biomedical Informatics [Elsevier BV]
卷期号:93: 103153-103153 被引量:262
标识
DOI:10.1016/j.jbi.2019.103153
摘要

• This review synthesizes evidence from 463 studies of wearable activity trackers (WAT). • We identify six themes that capture the research trends in these studies. • The themes are technology, data, acceptance, medical, behavior change, and privacy. • Direction for research is offered based on a triad of information, technology and people. Wearable activity trackers (WAT) are electronic monitoring devices that enable users to track and monitor their health-related physical fitness metrics including steps taken, level of activity, walking distance, heart rate, and sleep patterns. Despite the proliferation of these devices in various contexts of use and rising research interests, there is limited understanding of the broad research landscape. The purpose of this systematic review is therefore to synthesize the existing wealth of research on WAT, and to provide a comprehensive summary based on common themes and approaches. This article includes academic work published between 2013 and 2017 in PubMed, Embase, Scopus, Web of Science, ACM Digital Library, and Google Scholar. A final list of 463 articles was analyzed for this review. Topic modeling methods were used to identify six key themes (topics) of WAT research, namely: (1) Technology Focus, (2) Patient Treatment and Medical Settings, (3) Behavior Change, (4) Acceptance and Adoption (Abandonment), (5) Self-monitoring Data Centered, and (6) Privacy. We take an interdisciplinary approach to wearable activity trackers to propose several new research questions. The most important research gap we identify is to attempt to understand the rich human-information interaction that is enabled by WAT adoption.

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