Affiliation:
1. Grupo de Investigación I+D+I en TIC Universidad EAFIT
2. Grupo de Investigación de Modelado Matemático Universidad EAFIT
3. Grupo de Investigación DDP Universidad EAFIT
4. Department of Surgery Stanford University
Abstract
Currently, surgical skills teaching in medical schools and hospitals is changing, requiring the development of new tools to focus on (i) the importance of the mentor’s role, (ii) teamwork skills training, and (iii) remote training support. Collaborative Networked Virtual Surgical Simulators (CNVSS) allow collaborative training of surgical procedures where remotely located users with different surgical roles can take part in the training session. To provide successful training involving good collaborative performance, CNVSS should guarantee synchronicity in time of the surgical scene viewed by each user and a quick response time which are affected by factors such as users’ machine capabilities and network conditions. To the best of our knowledge, the impact of these factors on the performance of CNVSS implementing hybrid client–server architecture has not been evaluated. In this paper the development of a CNVSS implementing a hybrid client–server architecture and two statistical designs of experiments (DOE) is described by using (i) a fractional factorial DOE and (ii) a central composite DOE, to determine the most influential factors and how these factors affect the collaboration in a CNVSS. From the results obtained, it was concluded that packet loss, bandwidth, and delay have a larger effect on the consistency of the shared virtual environment, whereas bandwidth, server machine capabilities, and delay and interaction between factors bandwidth and packet loss have a larger effect on the time difference and number of errors of the collaborative task.
Subject
Computer Vision and Pattern Recognition,Human-Computer Interaction,Control and Systems Engineering,Software
Cited by
6 articles.
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