Anticipatory computing for human behavioral change intervention: A systematic review

Chunpei Lin, Guanxi Zhao, Yenchun Jim Wu*, Hailin Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Article number8779632
Pages (from-to)103738-103750
Number of pages13
JournalIEEE Access
Publication statusPublished - 2019


  • Anticipatory computing
  • Behavioral change intervention
  • Context prediction
  • Intelligent intervention
  • Sensing and context inferring

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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