S M Zhao1, X H Zhao2, J Zhang1, D X Wang2, X Y Wang1. 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.
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.
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.