Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data
Realistic tool-tissue interactive modeling has been recognized as an essential requirement in the training of virtual surgery. A virtual basic surgical training framework integrated with real-time force rendering has been recognized as one of the most immersive implementations in medical education....
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2019/9756842 |
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| _version_ | 1832560808415985664 |
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| author | Feiyan Li Yonghang Tai Qiong Li Jun Peng Xiaoqiao Huang Zaiqing Chen Junsheng Shi |
| author_facet | Feiyan Li Yonghang Tai Qiong Li Jun Peng Xiaoqiao Huang Zaiqing Chen Junsheng Shi |
| author_sort | Feiyan Li |
| collection | DOAJ |
| description | Realistic tool-tissue interactive modeling has been recognized as an essential requirement in the training of virtual surgery. A virtual basic surgical training framework integrated with real-time force rendering has been recognized as one of the most immersive implementations in medical education. Yet, compared to the original intraoperative data, there has always been an argument that these data are represented by lower fidelity in virtual surgical training. In this paper, a dynamic biomechanics experimental framework is designed to achieve a highly immersive haptic sensation during the biopsy therapy with human respiratory motion; it is the first time to introduce the idea of periodic extension idea into the dynamic percutaneous force modeling. Clinical evaluation is conducted and performed in the Yunnan First People’s Hospital, which not only demonstrated a higher fitting degree (AVG: 99.36%) with the intraoperation data than previous algorithms (AVG: 87.83%, 72.07%, and 66.70%) but also shows a universal fitting range with multilayer tissue. 27 urologists comprising 18 novices and 9 professors were invited to the VR-based training evaluation based on the proposed haptic rendering solution. Subjective and objective results demonstrated higher performance than the existing benchmark training simulator. Combining these in a systematic approach, tuned with specific fidelity requirements, haptically enabled medical simulation systems would be able to provide a more immersive and effective training environment. |
| format | Article |
| id | doaj-art-566b543586914529abe6807899e9f170 |
| institution | Kabale University |
| issn | 1176-2322 1754-2103 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-566b543586914529abe6807899e9f1702025-02-03T01:26:37ZengWileyApplied Bionics and Biomechanics1176-23221754-21032019-01-01201910.1155/2019/97568429756842Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical DataFeiyan Li0Yonghang Tai1Qiong Li2Jun Peng3Xiaoqiao Huang4Zaiqing Chen5Junsheng Shi6Yunnan Key Laboratory of Opto-electronic Information Technology, Yunnan Normal University, Kunming, ChinaYunnan Key Laboratory of Opto-electronic Information Technology, Yunnan Normal University, Kunming, ChinaYunnan Key Laboratory of Opto-electronic Information Technology, Yunnan Normal University, Kunming, ChinaDepartment of Urology Surgery, Yunnan First People’s Hospital, Kunming, ChinaYunnan Key Laboratory of Opto-electronic Information Technology, Yunnan Normal University, Kunming, ChinaYunnan Key Laboratory of Opto-electronic Information Technology, Yunnan Normal University, Kunming, ChinaYunnan Key Laboratory of Opto-electronic Information Technology, Yunnan Normal University, Kunming, ChinaRealistic tool-tissue interactive modeling has been recognized as an essential requirement in the training of virtual surgery. A virtual basic surgical training framework integrated with real-time force rendering has been recognized as one of the most immersive implementations in medical education. Yet, compared to the original intraoperative data, there has always been an argument that these data are represented by lower fidelity in virtual surgical training. In this paper, a dynamic biomechanics experimental framework is designed to achieve a highly immersive haptic sensation during the biopsy therapy with human respiratory motion; it is the first time to introduce the idea of periodic extension idea into the dynamic percutaneous force modeling. Clinical evaluation is conducted and performed in the Yunnan First People’s Hospital, which not only demonstrated a higher fitting degree (AVG: 99.36%) with the intraoperation data than previous algorithms (AVG: 87.83%, 72.07%, and 66.70%) but also shows a universal fitting range with multilayer tissue. 27 urologists comprising 18 novices and 9 professors were invited to the VR-based training evaluation based on the proposed haptic rendering solution. Subjective and objective results demonstrated higher performance than the existing benchmark training simulator. Combining these in a systematic approach, tuned with specific fidelity requirements, haptically enabled medical simulation systems would be able to provide a more immersive and effective training environment.http://dx.doi.org/10.1155/2019/9756842 |
| spellingShingle | Feiyan Li Yonghang Tai Qiong Li Jun Peng Xiaoqiao Huang Zaiqing Chen Junsheng Shi Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data Applied Bionics and Biomechanics |
| title | Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data |
| title_full | Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data |
| title_fullStr | Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data |
| title_full_unstemmed | Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data |
| title_short | Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data |
| title_sort | real time needle force modeling for vr based renal biopsy training with respiratory motion using direct clinical data |
| url | http://dx.doi.org/10.1155/2019/9756842 |
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