Auto-Hierarchical Data Algorithm: Focus on Increasing Users' Motivation and Duration in Virtual Reality

Xiang Li, Yuzheng Chen*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

4 Citations (Scopus)

Abstract

Virtual reality (VR) exergames have become part of increasingly popular serious games because of both the fast development of VR technology and diversified dissemination of exergames. In this paper, we designed a built-in algorithm which based on the fatigue parameter to timely adjust the exergame's difficulty, especially in body-building/fitness exercise. The calculation method of fatigue index is obtained by using analytic hierarchy process (AHP) with six influencing factors: (1) average Heart Rate (avgHR); (2) Borg CR 6-20; (3) Calorie(s); (4) Accuracy Rate (Acc%); (5) Intensity; (6) Exercise time. Result from the experiments with 8 participants shows that the fitness exergame sorted by the auto-hierarchical algorithm we designed will be more effective than the traditional process by partly increasing both users' motivation and duration of playing exergame in the current phase.

Original languageEnglish
Title of host publication2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages150-153
Number of pages4
ISBN (Electronic)9781728141114
DOIs
Publication statusPublished - May 2020
Externally publishedYes
Event5th IEEE International Conference on Big Data Analytics, ICBDA 2020 - Xiamen, China
Duration: 8 May 202011 May 2020

Publication series

Name2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020

Conference

Conference5th IEEE International Conference on Big Data Analytics, ICBDA 2020
Country/TerritoryChina
CityXiamen
Period8/05/2011/05/20

Keywords

  • computer-human interaction
  • data modeling
  • exergame
  • virtual reality

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