کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6861006 | 1438958 | 2016 | 48 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Achieving interface and environment fidelity in the Virtual Basic Laparoscopic Surgical Trainer
ترجمه فارسی عنوان
دستیابی به واسط و محرک محیطی در مربی مجازی پایه جراحی لاپاروسکوپی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
The results indicate that user performance on the earlier version of the VBLaST resulting from the first design iteration was significantly lower than the performance on the standard FLS box-trainer. The comparative situated evaluation with domain experts permitted us to identify some issues related to the visual, haptic and interface fidelity on this early prototype. Results of the second experiment indicate that the performance on the second generation VBLaST was significantly improved as compared to the first generation and not significantly different from that of the standard FLS box-trainer. Furthermore, the subjects rated the fidelity features of the modified VBLaST version higher than the early version. These findings demonstrate the value of the comparative situated evaluation sessions entailing hands on reflection by domain experts to achieve the environment and interface fidelity and training objectives when designing a virtual reality laparoscopic trainer. This suggests that this method could be used successfully in the future to enhance the value of VR systems as an alternative to physical trainers for laparoscopic surgery skills. Some recommendations on how to use this method to achieve the environment and interface fidelity of a VR laparoscopic surgical trainer are identified.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Human-Computer Studies - Volume 96, December 2016, Pages 22-37
Journal: International Journal of Human-Computer Studies - Volume 96, December 2016, Pages 22-37
نویسندگان
Amine Chellali, Helena Mentis, Amie Miller, Woojin Ahn, Venkata S. Arikatla, Ganesh Sankaranarayanan, Suvranu De, Steven D. Schwaitzberg, Caroline G.L. Cao,