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Anticipatory Computing for Human Behavioral Change Intervention: A Systematic Review
oleh: Chunpei Lin, Guanxi Zhao, Yenchun Jim Wu, Hailin Li
Format: | Article |
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Diterbitkan: | IEEE 2019-01-01 |
Deskripsi
With the rapid development of computer and communication technology, anticipatory computing has been identified as one of the most important factors affecting human behavioral change. The future of anticipatory computing will not be bright if it fails to provide useful help to human life and work. Anticipatory computing applied to behavioral change intervention (BCI) is full of challenges and is a research topic of increasing interest and importance. This paper provides an overview of the concept of anticipatory computing, BCI, as well as anticipatory computing for the BCI and offers a multistage literature analysis. Also, a systematic analytical framework articulated from the existing literature is presented to reveal the progress and details of anticipatory computing for the BCI. This framework is divided into four dimensions: 1) sensing and context inferring; 2) context prediction; 3) behavioral guidance and intervention, and; 4) application. Based on our literature analysis, 11 elements of anticipatory computing for BCI are identified and discussed in terms of principles, enablers, and activities. Afterward, contributions and possible future directions for research are summarized at the end of this paper.