基于数字三维技术的医学芳香疗法实验教学资源建设

IF 3.1 Q1 Mathematics
Jing Xu
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引用次数: 0

摘要

摘要本文基于Unity3D引擎,对图像特征点进行粗提取,并采用基于四叉树的分割算法对FAST角点进行最优滤波。快速三维重建技术是通过类似于尺度不变特征变换(SIFT)的非线性尺度空间构造方法,根据尺度级对数层逐层递增来构建的。扩散完成后,将匹配的特征点导入模型,得到重建的三维虚拟教学实验室工具。最后,以医学芳香疗法实验课《芳香疗法治疗原发性痛经临床实验》为教学目标,对中医和针灸专业学生进行教学过程和师生行为数据分析。结果表明,实验组的iFIAS最大值为100,平均值为79.35,而对照组的技术iFIAS最大值仅为51.32,平均值为21.34,两者差异有统计学意义。结果表明,这种教学方法提高了课堂学习的兴趣和效果。本文旨在为芳香疗法教学与3D虚拟现实相结合的未来发展方向提供相关意见和参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction of medical aromatherapy experimental teaching resources based on digital three-dimensional technology
Abstract In this paper, on the basis of the Unity3D engine, image feature points are coarsely extracted, and a quadtree-based division algorithm is applied to filter the optimal FAST corner points. The fast 3D reconstruction technique is constructed through the construction method of nonlinear scale space similar to scale-invariant feature transform (SIFT), which is layer incremented according to the scale level logarithmic layer. The reconstructed 3D virtual teaching laboratory tool is obtained by importing the matched feature points into the model after the diffusion is completed. Finally, the teaching process and teacher-student behavioral data analysis were conducted for TCM and acupuncture students using the medical aromatherapy experimental course “Clinical Experiment of Aromatherapy for Primary Dysmenorrhea” as the teaching objective. The results showed that the maximum value of iFIAS of the experimental group was 100, and the mean value was 79.35, while the maximum value of technical iFIAS of the control group was only 51.32, and the mean value was 21.34, which was a significant difference between the two. It shows that the teaching method improves classroom learning interest and effect. The purpose of this paper is to provide relevant opinions and references for the future development direction of the combination of aromatherapy teaching and 3D virtual reality.
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来源期刊
Applied Mathematics and Nonlinear Sciences
Applied Mathematics and Nonlinear Sciences Engineering-Engineering (miscellaneous)
CiteScore
2.90
自引率
25.80%
发文量
203
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