北京大学学报(医学版) ›› 2021, Vol. 53 ›› Issue (1): 139-142. doi: 10.19723/j.issn.1671-167X.2021.01.021

• 论著 • 上一篇    下一篇

虚拟现实技术用于龋坏识别教学

赵思铭1,赵晓含2,张杰1,王党校2,王晓燕1,Δ()   

  1. 1.北京大学口腔医学院·口腔医院,牙体牙髓科 国家口腔疾病临床医学研究中心 口腔数字化医疗技术和材料国家工程实验室 口腔数字医学北京市重点实验室,北京 100081
    2.北京航空航天大学虚拟现实技术与系统国家重点实验室,北京 100191
  • 收稿日期:2020-09-30 出版日期:2021-02-18 发布日期:2021-02-07
  • 通讯作者: 王晓燕 E-mail:wangxiaoyan@pkuss.bjmu.edu.cn
  • 基金资助:
    北京大学口腔医学院教育教学改革基金(2016-PT-05)

Preliminary evaluation of a virtual reality dental simulation system on training of caries identification ability

ZHAO Si-ming1,ZHAO Xiao-han2,ZHANG Jie1,WANG Dang-xiao2,WANG Xiao-yan1,Δ()   

  1. 1. Department of Cariology and Endodontology, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
    2. The State Key Lab of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China
  • Received:2020-09-30 Online:2021-02-18 Published:2021-02-07
  • Contact: Xiao-yan WANG E-mail:wangxiaoyan@pkuss.bjmu.edu.cn
  • Supported by:
    Educational Reform Foundation of Peking University School of Stomatology(2016-PT-05)

摘要:

目的: 基于虚拟现实牙科模拟系统UniDental开发龋坏识别软件,应用于口腔医学专业本科生临床前期龋坏识别教学,提高学生识别龋坏组织的能力。方法: 基于UniDental系统进行龋坏识别软件开发,在软件中建立抽象龋洞模型,将龋洞分为浅、中、深3层,各层内赋予相同的硬度值和粗糙度值,其中硬度值随深度增加而增大,粗糙度值随深度增加而减小。被试选取北京大学口腔医学院2014级口腔医学专业临床前期教学阶段学生64人,使用Unidental系统的龋坏识别软件,操作力反馈手柄,分别在龋洞模型的浅层、中层、深层进行垂直向硬度探查和水平向粗糙度探查操作培训,完成培训后进行问卷调查,以1~5分评价各项力反馈效果的真实性和对龋坏识别能力提高的帮助度,选择个人倾向的教学模式,并进行相应的统计学分析。结果: 各层硬度、粗糙度及其各自变化梯度评分的中位数均为4,表示比较真实;浅层、中层、深层硬度评分结果对硬度变化梯度评分的影响均有统计学意义(P<0.05);浅层、中层粗糙度评分结果对粗糙度变化梯度评分的影响有统计学意义(P<0.05);本实验对学生能力的提高比较有帮助(中位数为4), 各层硬度和硬度变化梯度评分结果对学生能力提高帮助度的影响有统计学意义(P<0.05);90.4%的学生支持传统离体牙教学模式。结论: 虚拟现实技术对学生龋坏识别能力提高比较有帮助,但无法取代传统教学, 可作为传统离体牙教学模式的补充。

关键词: 虚拟现实, 龋齿, 培训, 仿真系统, 模拟系统, 口腔医学

Abstract:

Objective: To develop a software based on “UniDental” system which is a virtual reality dental simulation system and applied to undergraduate majoring in stomatology to improve the ability of identifying caries.Methods: A software was developed applying to identify virtual dental caries based on UniDental system. In the software, a virtual dental caries model was designed and carious tissue was separated to 3 layers by the depth. The stiffness was the same within each layer which was increasing gradually layer by layer. The roughness was also the same within each layer which was decreasing gradually layer by layer. Sixty-four participants in pre-clinical stage of the class of 2014 majoring in stomatology from Peking University School of Stomatology were trained with the software. During the training, the students should probe on the virtual dental carious tissue layer by layer and feel the difference of vertical stiffness and horizontal roughness of each layer by using a handpiece with realistic force feedback. After training, a questionnaire survey was conducted to evaluate the software including a score of 1-5 for haptic fidelity of stiffness and roughness and their relevant gradient and benefit of improving the ability of identifying caries, choosing the preferred training method. The data were statistically analyzed using Kruskal-Wallis test.Results: The median of subjective evaluation scores of the proposed metrics were all “4”, demonstrating that the software operated above medium fidelity. The stiffness scores of all 3 layers were statistically significant (P<0.05) on the stiffness gradient score. The roughness scores of the 1st and 2nd layers were statistically significant (P<0.05) on the roughness gradient score. The training was helpful to improve the ability of identifying caries (median was 4). The scores of all 3 layers stiffness and relevant gradient were statistically significant (P<0.05) on the score of benefit of improving the ability of identifying caries. 90.4% of the participants preferred the traditional extracted teeth training method.Conclusion: The virtual reality dental simulation system was helpful to improve students’ ability of identifying caries. It couldn’t replace the traditional extracted teeth training method by now, it should be used as a supplement to the traditional training method.

Key words: Virtual reality, Dental caries, Training, Simulation systems, Oral medicine

中图分类号: 

  • R781.1

图1

UniDental系统"

图2 3

抽象龋洞模型 图3 龋坏识别软件界面"

表1

问卷调查评分表"

Items Median Proportion of realism scores/% P* P#
1 2 3 4 5
Stiffness
1st layer 4 1.6 4.7 12.5 43.8 37.5 0.011 0.006
2nd layer 4 1.6 6.3 23.4 39.1 29.7 0.013 0.049
3rd layer 4 1.6 9.4 17.2 29.7 42.2 0.002 0.005
Gradient 4 0 10.9 15.6 31.3 42.2 0.004
Roughness
1st layer 4 0 3.1 17.2 40.6 39.1 0.003 0.167
2nd layer 4 1.6 3.1 18.8 35.9 40.6 0.003 0.278
3rd layer 4 1.6 1.6 20.3 29.7 46.9 0.054 0.074
Gradient 4 0 7.8 17.2 34.4 40.6 0.345
Benefit of improving 4 1.6 10.9 25.0 28.1 34.4
[1] 王嘉德, 高学军. 牙体牙髓病学[M]. 北京: 北京大学医学出版社, 2006: 51-55.
[2] Simodont® dental trainer. (2020-09-25)[2020-09-26]. https://www.moog.com/markets/medical-dental-simulation/haptic-technology-in-the-moog-simodont-dental-trainer.html.
[3] Tse B, Harwin W, Barrow A, et al. Design and development of a haptic dental training system: HapTEL[C]. Berlin Heidelberg: Springer-Verlag, 2010: 101-108.
[4] Dutã M, Amariei CI, Bogdan CM, et al. An overview of virtual and augmented reality in dental education[J]. Oral Health Dent Manag, 2011,10(1):42-49.
[5] Wang DX, Zhang YR, Hou JX, et al. iDental: a paptic-based dental simulator and its preliminary user evaluation[J]. IEEE Trans Haptics, 2012,5(4):332-343.
doi: 10.1109/TOH.2011.59 pmid: 26964131
[6] Wang DX, Zhao SM, Li T, et al. Preliminary evaluation of a virtual reality dental simulation system on drilling operation[J]. Biomed Mater Eng, 2015,26(Suppl 1):S747-S756.
[7] Wang DX, Zhao XH, Shi YJ, et al. Six degree-of-freedom haptic simulation of probing dental caries within a narrow oral cavity[J]. IEEE Trans Haptics, 2016,9(2):279-291.
doi: 10.1109/TOH.2016.2531660 pmid: 26915130
[8] Chu RH, Zhang YR, Zhang HD, et al. Co-actuation: a method for achieving high stiffness and low inertia for haptic devices[J]. IEEE Trans Haptics, 2020,13(2):312-324.
doi: 10.1109/TOH.2019.2944611 pmid: 31603800
[9] Banerjee A, Frencken JE, Schwendicke F, et al. Contemporary operative caries management: consensus recommendations on minimally invasive caries removal[J]. Br Dent J, 2017,223(3):215-222.
doi: 10.1038/sj.bdj.2017.672 pmid: 28798430
[10] Ntovas P, Loubrinis N, Maniatakos P, et al. Evaluation of dental explorer and visual inspection for the detection of residual caries among Greek dentists[J]. J Conserv Dent, 2018,21(3):311-318.
doi: 10.4103/JCD.JCD_67_17 pmid: 29899636
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