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. 2008 Jun;4(2):131-8.
doi: 10.1002/rcs.185.

Development of the VBLaST: a virtual basic laparoscopic skill trainer

Anderson Maciel  1 , Youquan Liu, Woojin Ahn, T Paul Singh, Ward Dunnican, Suvranu De
Affiliations

Development of the VBLaST: a virtual basic laparoscopic skill trainer

Anderson Maciel et al. Int J Med Robot. 2008 Jun.

Abstract

Background: The FLS training tool box has now been adopted by the Society of Gastrointestinal Endoscopic Surgeons (SAGES) as an official training tool for minimally invasive procedures.

Methods: To overcome the limitations of the physical FLS training tool box, we have developed a Virtual Basic Laparoscopic Skill Trainer (VBLaSTTM) system, which is a 3D simulator that will allow trainees to acquire basic laparoscopic skill.

Results: The outcome of this work is the development of an integrated visio-haptic workstation environment including force feedback devices and a stereo display interface whereby trainees can practice on virtual versions of the FLS. Realistic graphical rendering and high fidelity haptic interactions are achieved.

Conclusions: Surgical skill training is a long and tedious process of acquiring fine motor skills. It is expected that residents would start on trainers such as VBLaSTTM and after reaching a certain level of competence would progress to the more complex trainers for training on specific surgical procedures.

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Figures

FIGURE 1
FIGURE 1
Mechanical training toolbox.
FIGURE 2
FIGURE 2
The 4 MISTELS tasks used in the FLS toolbox: (a) peg transfer; (b) circular pattern cutting; (c) ligating loop; (d) suturing.
FIGURE 3
FIGURE 3
The 4 VBLaSTTM tasks: (a) peg transfer; (b) circular pattern cutting; (c) ligating loop; (d) suturing.
FIGURE 4
FIGURE 4
The VBLaST™ workstation.
FIGURE 5
FIGURE 5
The dynamic point algorithm for a line interacting with a 3D mesh. Current dynamic point P and the closest point in the mesh Pt.
FIGURE 6
FIGURE 6
Needle-tissue interaction. (a) the needle is discretized into segments for collision detection; (b) the local frame of each segment is used to calculate resistance inside the tissue.
FIGURE 7
FIGURE 7
The suture model using a 1D mass-spring.
FIGURE 8
FIGURE 8
Self-collision and response for the thread model.
FIGURE 9
FIGURE 9
Self-collision of the thread allows to tie a knot.
FIGURE 10
FIGURE 10
The ligating loop structure. (a) in rest position and (b) when in collision with another object.
FIGURE 11
FIGURE 11
Collision detection in cutting. The instrument (scissors) is represented by 3 lines for collision detections and response. When the two lines representing the blades touch the closest point, a cutting point is established.
FIGURE 12
FIGURE 12
Collision and deformation while manipulating the ligating loop. The loop is decomposed into twenty-eight line segments for the purpose of collision detection and response. The radial lines represent the relation of proximity
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