Auto-Hierarchical Data Algorithm: Focus on Increasing Users’ Motivation and Duration In Virtual Reality
Auto-Hierarchical Data Algorithm: Focus on Increasing Users’ Motivation and Duration In Virtual Reality
复制标题
自动分层数据算法：专注于增加用户在虚拟现实中的动机和持续时间
DOI：
10.1109/icbda49040.2020.9101254
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Yuzheng Chen
中科院分区：
文献类型：
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作者：
Xiang Li;Yuzheng Chen
虚拟现实(VR)运动游戏由于VR技术的快速发展和运动游戏的多元化传播，已经成为越来越受欢迎的严肃游戏的一部分。在本文中，我们设计了一种基于疲劳参数的内置算法，以及时调整运动的难度，特别是在健身/健身运动中。运用层次分析法得出疲劳指数的计算方法，包括6个影响因素：(1)平均心率；(2)Borg CR6-20；(3)卡路里(S)；(4)准确率(ACC%)；(5)强度；(6)运动时间。对8名参与者的实验结果表明，本文设计的自动分层算法排序的健身锻炼游戏比传统的健身锻炼游戏过程更有效，部分地提高了用户在现阶段玩锻炼游戏的动机和持续时间
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