Augmented reality-based visual-haptic modeling for thoracoscopic surgery training systems


Background: Compared with traditional thoracotomy, video-assisted thoracoscopic surgery (VATS) has less minor trauma, faster recovery, higher patient compliance, but higher requirements for surgeons. Virtual surgery training simulation systems are important and have been widely used in Europe and America. Augmented reality (AR) in surgical training simulation systems significantly improve the training effect of virtual surgical training, although AR technology is still in its initial stage. Mixed reality has gained increased attention in technology-driven modern medicine but has yet to be used in everyday practice. Methods: This study proposed an immersive AR lobectomy within a thoracoscope surgery training system, using visual and haptic modeling to study the potential benefits of this critical technology. The content included immersive AR visual rendering, based on the cluster-based extended position-based dynamics algorithm of soft tissue physical modeling. Furthermore, we designed an AR haptic rendering systems, whose model architecture consisted of multi-touch interaction points, including kinesthetic and pressure-sensitive points. Finally, based on the above theoretical research, we developed an AR interactive VATS surgical training platform. Results: Twenty-four volunteers were recruited from the First People's Hospital of Yunnan Province to evaluate the VATS training system. Face, content, and construct validation methods were used to assess the tactile sense, visual sense, scene authenticity, and simulator performance. Conclusions: The results of our construction validation demonstrate that the simulator is useful in improving novice and surgical skills that can be retained after a certain period of time. The video-assisted thoracoscopic system based on AR developed in this study is effective and can be used as a training device to assist in the development of thoracoscopic skills for novices.

Publication DOI:
Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
Funding Information: ? Supported by the National Science Foundations of China (62062069, 62062070, and 62005235).
Additional Information: ©Copyright 2021 Beijing Zhongke Journal Publishing Co. Ltd., Publishing services by Elsevier B.V. on behalf of KeAi Communication Co. Ltd. This is an open access article under the CC BY-NC-ND license ( Funding Information: Supported by the National Science Foundations of China (62062069, 62062070, and 62005235).
Uncontrolled Keywords: Augmented reality,Surgery training,VATS,XPBD,Computer Graphics and Computer-Aided Design,Computer Science Applications,Human-Computer Interaction
Publication ISSN: 2096-5796
Last Modified: 10 Jun 2024 07:43
Date Deposited: 31 May 2022 16:20
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.sci ... 096579621000528 (Publisher URL)
PURE Output Type: Article
Published Date: 2021-08-01
Accepted Date: 2021-06-14
Authors: Tai, Yonghang
Shi, Junsheng
Pan, Junjun
Hao, Aimin
Chang, Victor (ORCID Profile 0000-0002-8012-5852)

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