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Received September 18, 2024, accepted June 23, 2025, date of publication September 30, 2025.

Original Research Article

Training of Surgical Skills by a 3D Augmented Liver Model 
Response During Instrument Interactions Simulation

Veronika Ivanova1,†,*, Plamen Vasilev Vasilev2,† and Ani Todorova Boneva 3,†

1 Department of Robotized and Mechatronics Intelligent Systems, Institute of Robotics, Bulgarian Academy of Sciences, Sofia 1113, Bulgaria.
2 Department of Industrial Automation, University of Chemical Technology and Metallurgy, Sofia 1756, Bulgaria.
3 Department of Communication and Computer Systems, Institute of Information and Communication Technologies, Bulgarian Academy of 
Sciences, Sofia 1113, Bulgaria.

†These authors contributed equally to this work.

* Corresponding Author Email: iwanowa.w@abv.bg

ABSTRACT

Background and Objective: In recent years, interest in surgical robotics simulation has grown significantly, particularly 
among trainee surgeons. This trend is driven by the demand for cost-effective training solutions, improved surgical outcomes, 
and reduced training times. Simulations also play a vital role in the design and testing of surgical instruments, enabling analysis 
of static and dynamic loads and optimization of tool–tissue interactions. However, because of the complex nature of soft tissue 
deformation during surgical procedures, developing realistic and effective simulations remains a challenge. This study focuses 
on modeling liver responses during tool–tissue interactions in laparoscopic surgery. Building on prior research in surgical ro-
botics, the goal is to develop a personalized training platform that enhances the skills of surgical personnel without the need 
for live human or animal subjects.

Materials and Methods: The study begins by analyzing the motion of a tactile surgical instrument interacting with tissue. 
Direct kinematics is used to enable remote control of surgical robots by the lead surgeon. To improve control accuracy, systematic 
positional errors are introduced into the control links. A simulation program is developed to define the operational workspace 
and potential tool actions. Movement within this space is controlled by four motors connected to transmission mechanisms. 
Analytical models of these mechanisms are used to optimize performance under defined constraints. In addition, a training 
simulation program (TSP) is created to model liver responses during tool–tissue interactions. This program visualizes the 3D 
behavior of organs using physical material properties and simulates collisions between solids. The Unity Game Engine is used 
to generate animations compatible with both standard and VR/AR environments.

Results: Experimental data involving various laparoscopic instrument tips and biological tissues are stored in a MySQL da-
tabase. These data can be accessed via local workstations, institutional servers, or cloud-based platforms. Users can also store 
their simulation data on mobile devices or processor cards.

Conclusion: This study presents a comprehensive approach to developing a surgical training system that simulates realistic 
tool–tissue interactions. The findings contribute to the advancement of minimally invasive surgical education by enabling per-
sonalized, data-driven training experiences. The proposed system offers a scalable and ethical alternative to traditional training 
methods, with potential applications in both academic and clinical settings. The simulation programs effectively transferred 
acquired skills to real-world scenarios, demonstrating the system’s potential for enhancing surgical training. 

mailto:iwanowa.w@abv.bg
mailto:mulugetamideksa@gmail.com 


89 J Global Clinical Engineering Vol.7 Issue 3: 2025

Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
Simulation

Keywords—Augmented reality, Training program 
simulation (TPS), Software applications, Surgical robotics, 
Surgical training.    

Copyright © 2025. This is an open-access article distributed under 
the terms of the Creative Commons Attribution License (CC BY): Creative 
Commons - Attribution 4.0 International - CC BY 4.0. The use, distribution or 
reproduction in other forums is permitted, provided the original author(s) 
and the copyright owner(s) are credited and that the original publication 
in this journal is cited, in accordance with accepted academic practice. No 
use, distribution or reproduction is permitted which does not comply with 
these terms.

INTRODUCTION 

Software applications offer innovative solutions in 
Medicine. In surgery, this progress allows the development 
of surgical simulators that reach the maximum level of real-
ism and emulate complex procedures, taking into account 
the specificity and anatomical requirements of individual 
patients. Also, the simulation is a suitable method for 
training surgeons in complex movements and operations 
because it reduces the duration of the surgeon’s training 
in minimally invasive surgery (MIS). The methodology for 
developing a web-based laparoscopy e-training system is 
particularly important.1 Software applications can provide 
a surgical environment with its physical properties, texture, 
and complexity. Computer-based methods can be the main 
part of surgical tool design. To solve new problems that 
continue to arise in real surgical procedures, new tools 
are created every day. An important step in the creation 
of surgical instruments is the development and applica-
tion of a virtual environment and near-real models to 
simulate the response of the organ when interacting with 
an instrument. Simulation methods can provide different 
scenarios for the operation to take into account different 
anatomies, pathologies, and working areas. Training modes 
include tabletop models, virtual reality (VR), augmented 
reality (AR), animals, and cadavers. There are claims that 
the haptic interface, along with the visual simulation, aids 
the student or young surgeon to get a virtual experience 
of the surgical procedure as in a real patient operation. 
However, a number of studies prove that a combination of 
models is more effective than model-based learning alone.

The main ways to accomplish the simulation task are: a 
model, a detailed description of the real-world application 
of the model, and the applied forces/moments. Different 
medical procedures require different organ models. 

The basic approaches for model response during in-
strument interactions are Mass-Spring System (MSS)2 and 
Finite-Element Method (FEM).3 In the first approach, the 
geometric model of an organ is represented as particles 
with their own positions, velocities, and accelerations, 
which are connected by springs and dampers. The particles 
move under the influence of the forces of the surgical 
instruments. In FEM, each element of an organ model is 
calculated to obtain the deformation of the model under 
the applied forces.

Real-time surgical simulation requires computing the 
deformation of viscoelastic human tissue and generating 
both graphic and haptic feedback. Deformation simula-
tion is based on a sequential calculation of the tissues’ 
shape. The reaction forces result from the tool–tissue 
model interactions, where the virtual tools are controlled 
by the smart tools. Tissue models must look and behave 
realistically and be based on the physical laws related to 
human organ behavior.

Models used for simulation are mainly based on 
geometry or mechanics. Geometric models are not ac-
curate enough because they only simulate relative visual 
displacements. Mechanical models are accurate, but for 
a VR simulation, they can change continuously until they 
reach an equilibrium state, which makes them difficult 
for the operator to manipulate.

Sorkine and Alexa4 propose a method for surface 
modelling, where the object changes the shape of a mesh 
while preserving the details. It is characteristic that the 
peaks of the original grid must be specified. Then, the 
boundary is determined for new positions, so that the 
rest of the mesh vertices adapt to the new shape. The 
original geometric size of the mesh should preserve as 
much of the deformation as possible.

Some authors show a virtual simulator for pre-rolled 
soft tissue suturing without showing the making of knots, 
which is a basic moment in suturing.2

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J Global Clinical Engineering Vol.7 Issue 3: 2025 90

Telesurgery is evolving thanks to AR and wireless 
technology. Lead surgeons can train students and young 
surgeons in complex surgical procedures. Surgery is 
also aided by 3D printing technology. Tumor data can 
be extracted from CT or MRI scans and converted into 
a digital 3D model, which can then be 3D printed. From 
this model, the surgeon can see the relationship between 
the tumors and the surrounding tissue, which aids in 
planning the surgery.

The student or young surgeon can virtually experience 
all the essential aspects of a procedure through visual 
simulation and haptic technology, which otherwise would 
involve invasive techniques on a real patient or a corpse.

Great computing power and accuracy of haptic devices 
are only part of the advantages characteristic of modern 
laparoscopic simulations, which create favorable conditions 
for the process of preoperative planning and the training 
of surgeons. One such development is the EU PASSPORT 
for the simulation of laparoscopic liver resection, which 
uses many modern methods and the capabilities of the GPU 
to simulate various deformable organs in real time.”5 The 
work of Acharya, where the kinematics of the surrounding 
organs are studied, is also intended for simulation train-
ing and access (geometry) to the liver.6 In this research, 
diaphragm movement patterns are also presented for 
use in simulators for preoperative planning and training. 
An advancement in the field of organ modelling is also 
the work of Villard,7 where respiratory movements of 
the chest and soft tissue behavior of organs of a group of 
patients segmented by computed tomography in a liver 
biopsy simulator are modelled. A nonlinear liver model 
to measure organ response to force, accounting for organ 
deformation and boundary conditions, is presented by 
Lister.8 The accuracy of the model is assessed by drilling 
simulation.

There has also been progress in the modelling of 
surgical procedures. A team of scientists presented a 
real-time electrosurgical simulation virtual tool where 
the relationship between heat generated in the tissue 
and applied electrical potential was explored.9 All this 
finds good application in virtual surgical ablation. Over 
the years, 3D organ models have moved from linear10 to 

nonlinear,11 Moreover, simulations are increasingly com-
plex and realistic, making them accessible and attractive 
for applications.

Force feedback simulators are a more intuitive means of 
providing haptic information to the surgeon, while visual 
force feedback provides information about instrument 
contact with tissue under certain conditions. That is why 
haptic devices with touch simulation are increasingly being 
used. They are used in medicine for training and planning 
operations.12 One of the first palpation developments is 
a 3D visual and haptic liver diagnostic simulator with 
open-source software.13 SimSuiteTM System by Medical 
Simulation Corporation is one of the representatives of 
haptics devices, with a realistic simulated clinical environ-
ment.14 It offers haptic systems with real scenarios and 
images together. The force feedback is transmitted by an 
endoscope to give the real feeling. The system includes 
personal or team training with varying levels of complex-
ity. Its possibilities are the patient history, diagnosis, risk 
assessment, and intervention preparation.

The training program proposed in this publication, 
referred to as the training program simulating (TPS), 
facilitates the observation of three-dimensional (3D) 
augmented model responses during tactile instrument 
interactions within the context of surgical education. 
This program was developed to enhance the training 
of students and improve the qualifications of surgical 
personnel in the use of laparoscopic instruments. The ap-
plication presented herein represents an advancement of 
an existing mechatronic system designed for laparoscopic 
surgical training, aimed at both student education and 
the professional development of surgeons. The system 
is constructed on a modular framework, reflecting the 
principles underlying the program’s implementation. 
This training platform was developed so that students 
and surgeons can improve their qualifications without 
using living organisms—humans and animals.

VIRTUAL AND AR SIMULATORS AND THEIR PART 
IN SURGICAL EDUCATION

One of the first VR simulators is the Satava, proposed in 
1993. It used a computerized 3D model of the abdominal 
cavity and a head-mounted display (HMD).15 Satava is also 



91 J Global Clinical Engineering Vol.7 Issue 3: 2025

Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
Simulation

Telesurgery is a good aid for experienced surgeons 
teaching young surgeons in complex operations. Thanks to 
AR and wireless devices, AR simulators take advantage of 
VR and physical materials, tools, and tactile feedback. The 
3D virtual model is a static preoperative photo of a certain 
part of the body, where even respiratory movements and 
manipulation of the organ are taken into account. These 
kinds of simulators are useful for simulation immediately 
before performing complex surgical operations.24,25 The 
high simulation accuracy of the simulator allows visual-
ization of different tissues, tumors, arteries, and veins. 

AR in medicine dates back to 1988. One of the first 
medical AR systems was designed to display individual 
ultrasound slices of a fetus on a pregnant patient.26,27 
AR aids MIS by enhancing reality in the operating room, 
expanding the internal view of the patient based on 
preoperative or intraoperative data, and presenting the 
surgeon with detailed information about the operative 
field. Integrating pictures of virtual objects into real scenes 
is a major tool used in AR systems in medicine. While the 
surgeon’s working area is synthesized in the virtual envi-
ronment, AR superimposes computer-generated images 
on the actual view oriented to the direction of vision of 
the surgeon, who usually wears a suitable HMD or similar 
instruments. MEDICAL AR for Patient Workstation (ME-
DARPA) has recently been developed28 which uses AR 
without HMD. The surgeon can see the exact location of 
the damage on the patient while being observed without 
making a single incision. It is possible to design invisible 
blood vessels, reducing the risk of accidental damage. 
The improved visualization from this technology can 
benefit a variety of clinical procedures. AR serves as a 
guide for planning practical surgical actions. The patient 
is positioned in AR: with the help of AR, it is possible to 
view the entire anatomy and change the position of the 
body along the three axes. AR visualizes the target of the 
operation before it is visualized on the simulator. Some of 
their weaknesses are related to the correct alignment of 
the position and orientation of the surgeon’s eyes with a 
virtual coordinate system of the augmented images, the 
spatial tracking systems, and the virtual environment 
peripherals used.

Simulators combining haptic interfaces with AR tools 
can be used to detect deviations between the real position 

targeting the military and aerospace industries, which 
rely on VR for training, to apply this training to teach 
skills in operating rooms.16 This simulator sets the stage 
for VR training in surgery for many types of procedures, 
from elementary tasks such as suturing and knotting to 
mimicking entire surgical procedures.

Virtual-based simulators can use an application that 
allows interactive exploration of 3D anatomical models 
and animations. VR makes it possible, through developed 
mobile applications, to explore different surgical ap-
proaches using a smartphone or tablet. Each virtual study 
uses 3D anatomical models and animations. A learning 
system aimed at understanding the patient’s positioning 
according to specific anatomy and specific purpose. The 
study of each approach in 3D mode can be divided into 
phases too.

VR simulators allow trainees to practice individual 
movements or entire procedures in a near-real environ-
ment. Modern VR simulators can reproduce complex 
MIS by measuring various parameters of the procedure, 
including movement efficiency and node reliability, time 
to perform the operation, and even remote performance 
evaluation. The price of simulators is quite high, and they 
do not have tactile feedback and lack realism.17–19 Because 
of the lack of realism, the models of corpses and animals 
in VR simulators should be added to get optimal training. 
Despite these disadvantages, the number of VR training 
simulators is growing. VR simulators, such as LapSimTM 
(Surgical Science, Gothenburg, Sweden),20 were used for 
training basic laparoscopic surgery skills, and LapMen-
torTM (Simbionix Corporation, Cleveland, OH, USA),21 
was used for comprehensive training in laparoscopic 
sigmoidoscopy. Wynn et al. evaluated the effectiveness 
of this training in terms of the completion time of the 
process, the number of right and left tool movements, 
and the total route length of the right and left tool move-
ments.22 The research indicates high efficiency. Surgical 
simulation combined with virtual, mixed, and AR has 
become increasingly popular in recent years. AR is a tech-
nology where digital information does not interact with 
the real environment but is superimposed on the user’s 
view of the external environment as graphics, audio, or 
video information.23



Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
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J Global Clinical Engineering Vol.7 Issue 3: 2025 92

and the preoperative plan and to generate guiding forces 
for the surgeon. Robot-guided instruments follow the 
movement of the surgeon, who senses forces interacting 
with the tissue through the haptic device. The haptic device 
includes preoperative planning based on medical images 
and AR to guide the surgeon’s movements; AR models 
also provide visual feedback to the surgeon.

The advantage given by the simulation is that different 
parameters can be optimized, which gives good results 
in different areas of application.29

From the foregoing, it is clear that the high level of 
technical complexity of advanced laparoscopic procedures 
and the lengthy training pose many challenges to surgeons. 
This makes simulation an important tool in the training 
of complex laparoscopic surgery. That is why our efforts 
are directed in this direction.

This paper is organized into the following sections: 
Section 2 is referred to as the Investigation of Instrument 
Moving. Section 3 marks Architectures of Control Program 
Algorithms. Section 4 refers to A Simulating Approach of 
Liver Model Response during Tactile Instrument Inter-
actions and Its Results. At the end, there are sections on 
Future Challenges and Conclusions.  

Software applications offer innovative solutions in all 
spheres of human life,30,31 the most significant of which are 
in medicine. For this work, some calculating methods32 
for identifying both tool tissue force and maximum local 
strength are touched upon. Authors will specifically try 
to investigate these in the future.

A contemporary strategy yielding favorable outcomes 
involves the enhancement of existing systems across 
various domains and purposes, thereby conserving both 
financial and temporal resources in the research and 
development of new systems. An illustrative example 
is provided in reference,33 which outlines the primary 
procedures for upgrading existing systems for the au-
tomation and control of industrial and manufacturing 
processes. In alignment with this approach, it proposes to 
upgrade a laparoscopic execution tool system for robotic 
applications, incorporating functionalities that leverage 
AR and simulation technologies to facilitate the training 
of surgeons.

INVESTIGATION OF INSTRUMENT MOVING 

The action control in telecontrol (by the leading physician 
of the operation) is realized by the direct kinematic task. 
Moreover, to refine the action, the systematic positional 
error in the working position can be introduced into the 
control links. Solving the straight kinematic problem is 
a standard procedure.34 It is possible to develop a simu-
lation program to outline the workspace and possible 
actions in it. For an instrument with four independent 
movements, these movements are obtained by four mo-
tors and the corresponding transmission mechanisms 
between the motors and the executive links in this space. 
Figure 1 shows the possible instrument workspace and 
the instrument motions in this workspace. The relation 
can be written in Equation 1:

   

1
1

11

2 2 2
2

2 3 4 2

3
3

3 3

4
4

4 4

.
0 0 0

.
.

0
*.

.0 0 0
.

.0 0 0

qq

q q q q

q q

q q

ϕϕ

ϕ ϕ ϕ
ϕ

ϕ
ϕ

ϕ
ϕ

 ∂ 
  ∂   
 ∂ ∂ ∂ 
  ∂ ∂ ∂   =   ∂
  ∂   
  ∂
  ∂     

 (1)

where  [ ]1 2 3, , Tϕ ϕ ϕ ϕ=  is a vector of angular velocities of 

the executive link

1

1

2 2 2

2 3 4

3

3

4

4

0 0 0

0

0 0 0

0 0 0

q

q q q
J

q

q

ϕ

ϕ ϕ ϕ

ϕ

ϕ

∂ 
 ∂ 
 ∂ ∂ ∂
 ∂ ∂ ∂ =  ∂
 

∂ 
 ∂
 

∂  

 

where J is the Jacobian matrix, which reflects the value 
of the transfer functions, including dependent movements; 

[ ]1 2 3, , Tq q q q= is the vector of angular velocities at the 

robot’s joints. 



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Simulation

There is a need to determine the optimal area for the 
movement of the tool, using qualitative indicators. These 
indicators are based precisely on the Jacobian matrix. As 
a result, the geometry of the tool is optimized so that in 
a certain area, the configurations will provide optimal 
movement from the point of view of kinematics. This is 
important when scaling movements, that is, with a larger 
“size” of movement by the operator (master), minimal 
movements of the robotic tool are ensured. In an optimal 
configuration (a good quality indicator), these optimal 
configurations facilitate the control system.

The transmission functions  i

iq
ϕ∂
∂

 (i = 1, 2, 3, 4) along 

the main diagonal have the same structure:

      ( ), 1,2,3,4i
pi ni

i

i i i
q
φ∂

= × =
∂

 (2)

where ( )1,2,3,4pii i =  is the value of the gear ratio of the 

reducer of the corresponding circuit (most often and in 
this case are equal); ( )1,2,3,4nii i =  is the value of the gear 

ratio of the wires. For the determination of ini, kinematic 
chains of links 2 and 3 are used, as the kinematic chain 
of link 4 is similar to link 3. 

Transmitting functions at the major diagonal i

iq
ϕ∂
∂

, 

where ( )1,2,3,4pii i =  possesses a similar structure.  
 

( ), 1,2,3,4i
pi ini

i

i i i
q
φ∂

= × =
∂ (3)

where ( )1,2,3,4pii i =  is the value of the gear reduction 
ratio of the respective chain (often and in this case they 
are identical) and  ( )1,2,3,4nii i =  is the value of the gear 
transmission ratio of the wire.

The derived analytical  dependencies of  the 
transmission functions make it possible to carry 
out calculation procedures for the optimization of 
dimensions under the existing limiting conditions and 
also to be implemented in the software for controlling 
the movement of the tool, which is explained in the next 
section. 

A SIMULATIING APPROACH OF LIVER MODEL 
RESPONSE DURING INSTRUMENT INTERACTIONS

Tasks and Motions in Surgical Operation

The actions that are referred to in the performance of 
laparoscopic operations are numerous, and their priori-
ties are defined and strictly performed by the medical 
teams. In this case, when they are referring to actions 
that require manipulative movements through special-
ized tools, they include:

Visualization (illumination and movement of a mini 
video camera into the body of patients) of the manipu-
lated objects at the place where the controlled action is 
performed: 

• Gripping with positional fixation of the object in order 
to be manipulated, without being uncontrolled;

• Gripping (clamping) in order to isolate and tempo-
rarily disconnect the object during manipulation with it; 

• Clamping blood vessels to hold up bleeding damage.

Elementary actions such as touching and grasping 
are basic tool manipulations and are relatively easy to 

FIGURE 1. Possible instrument workspace and instrument 
monuments. 



Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
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J Global Clinical Engineering Vol.7 Issue 3: 2025 94

perform. More complicated actions are (1) dissections 
and (2) working with robotic suturing instruments, which 
require a lot of knowledge and skills from the surgeons, and 
they are more difficult to simulate too. However, some of 
them, such as robotic needle driving and grasping, which 
are easy in open surgery, are found to be more difficult 
to perform during laparoscopy.

A surgical task such as suturing includes a needle act-
ing with one rotation and one translation.35 The surgeon’s 
hand is close to the surface being sutured while rotating 
the needle so that the needle moves in a circular path 
without damaging the tissue. In robotic surgery, it can be 
reduced to one movement—rotating around the axis of 
the instrument, bending the short part of the needle near 
the blunt end, and just in front of where it is held by the 
slave instrument, so that the needle moves in a circular 
arc, while the tool rotates about its axis.36 Some authors 
have been focusing on knitting manipulation by robots. 
Some researchers have performed in vivo tests with 
different types of needles and tissues, showing that the 
required range of force and resolution is 2.5 N and 0.01 
N, respectively.37,38 The results in Table 1 are obtained 
with the designed laparoscopic executive instrument for 
robots (Figure 2).

 
TABLE 1. Description of usability attributes.

Samples Min. force 
(N)

Max. force
(N)

Average 
value
(N)

Amplitude
(N)

Styrofoam 
sample 0.1 1.67 0.83 1.57

Styrofoam 
rubber sample 0.785 2.26 1.13 1.47

Muscle tissue 
sample 0.45 2.4 1.21 1.94

Sample liver, 
pork 0.05 1.96 0.93 1.9

The research shows the following results. The required 
force for soft tissues is about 0.2 N, the applied gripping 
force for soft tissues is 0.5 N, and it is 0.9 N for hard tis-
sues. The required force is different for different cases. 
It depends on the patient’s age, health, gender, and other 
factors. In general, the maximum force is from 1.5 to 3 N. 
In isolated cases, the required force is from 6 to 12.5 N. 
These cases occur when the instrument is used for tis-
sue lifting. So, the instrument force is combined with the 
forces because of the properties of the fabric and those of 
gravity. However, the simulation program does not take 
gravity into account. The maximum cutting and spreading 
force is from 3 N to 6 N. Suture tasks force measurements 
show liver puncture up to 5 N, and the required gripping 
force is 3.45 N. 39–41

This information is useful for realizing a 3D augmented 
model.

A SIMULATING APPROACH OF LIVER MODEL 
RESPONSE DURING INSTRUMENT INTERACTIONS 

AND ITS RESULT

A training simulation program (TSP) has been de-
veloped wherein the 3D extended model response of 
a human organ upon impact with external objects. The 
behavior of the model is represented by the collision of 

FIGURE 2. Force measurements for different samples.



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Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
Simulation

two solid objects with different physical characteristics. 
The physical properties of the solids are transposed to 
“physical material” properties that enable the behavior of 
the object in the TSP. The Unity Game Engine is used for 
the TSP, which is intended for developing graphical anima-
tions for conventional or VR/AR artificial representations.

TSP includes surface manipulation libraries such as 
the mesh class. Meshes contain vertices and multiple 
triangle arrays with corresponding vertices. All vertex 
information is stored in separate arrays of the same size. 
The mesh class, along with its vertices, vectors, triangles, 
and normal, can be used to deform a mesh grid on a 3D 
object. An example of using the mesh class to deform a 
3D object in Unity (see Figure 3) is given with the script 
below:

using UnityEngine;

public class Example: MonoBehaviour

{

  void Update()

  {

Mesh = GetComponent<MeshFilter>().mesh;

Vector3[] vertices = mesh.vertices;

for (int i = 0; i < vertices.Length; i++) 

{

//Some conditional transformation for example

   vertices[i] += Vector3.up * Time.
deltaTime;

}

mesh.vertices = vertices;

mesh.RecalculateNormals();

mesh.UploadMeshData(false);

}

}

If the mesh surface deformation has to be executed on 
some event, the void method Start() should be invoked. 

void Start()

{

Mesh = GetComponent<MeshFilter>().mesh;

mesh.Clear(); //preserves the existing mesh vertex 
positions

        //Do some calculations with the mesh.vertices 
and mesh triangles

}

Figure 3 shows an example of the usage of the mesh 
class for deformation of a 3D object in Unity.

SOFTWARE ARCHITECTURE

The information from the experiments performed with 
different tips of the laparoscopic instrument and different 
biological tissues is recorded in a database that has a con-
nection with the database of the application (developed 
on the basis of MySQL). The databases are structured 
as a collection of directories, one for each student (sur-
geon), with each directory carrying its own ID number 
(for students, this may be a faculty number). Each of the 
directories is a collection of subdirectories as follows:

FIGURE 3. A 3D augmented model with mesh collider in Unity.



Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
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J Global Clinical Engineering Vol.7 Issue 3: 2025 96

•  Personal data for the student/surgeon (three names, 
social security number, etc.). Only the learner and the 
teacher can access this subdirectory;

• Subdirectory with information about conducted 
experiments and their results in text and graphic forms;

• Evaluation of the achieved results and attestation of 
the student/surgeon;

• Other information required by the relevant university 
or medical facility.

At the discretion of the institution/clinic concerned, 
subdirectories of experimental results may be made pub-
licly available to allow for comparisons and solutions for 
further simulations.

It is planned that the information accumulated in the 
relevant databases will be stored on a local operator 
station, a server of the relevant university/clinic, or a 
cloud medical server, on which more important results 
of conducted experiments will be published.

Each student/surgeon can save their information on 
their mobile phone or on a processor card. By their nature, 
processor cards have the same appearance as telephone 
cards. However, phone cards only have memory, while 
electronic chip cards contain a processor. The reprogram-
mable memory acts as a hard disk for the card—the data 
stored in this memory retains its values after the supply 
voltage is turned off.42 The introduction of processor 
cards in the educational system in Bulgaria will allow 
the replacement of existing paper student books with 
electronic ones, which will guarantee greater reliability, 
security of information, and access to student data at all 
levels of educational institutions. Data change is associ-
ated with different priority levels. Each teacher will have 
a unique number/password to change the data in the 
cards of students/surgeons.

The solution assumes that each classroom is equipped 
with a personal computer with a minimum configuration 
that allows work in the Windows operating system. The 
database will be installed on the teacher’s personal com-
puter, as well as the terminal program allowing working 

with the processor cards. Each student/surgeon must 
be provided with a Basic Card ZC2.3 processor card (or 
similar) upon commencement of training by the instructor. 
The teacher or another person authorized for this activity 
personalizes the card using the personal computer and 
the included reading device.42

Various means of controlling access to the information 
are provided, such as the use of passwords, QR codes (for 
mobile phones),43 ECG,44 or an identification chip of the 
company Dallas Semiconductor/Maxim-DS9490B45 (for 
access to the software installed on the teacher’s personal 
computer/laptop). The ECG device as a means of access 
control is proposed because one has already been devel-
oped for the modular laparoscopic system described above. 
At this stage, access control and information protection 
tools are based on the team’s accumulated experience in 
this area. Information encryption tools are an important 
element in building a medical security system. This fact is 
a consequence of the requirements that personal data be 
protected, both at the local operator stations and on the 
way to another destination. As a means of access control, 
the wireless ECG device developed for the mechatronic 
system can be used.

As the system is built on a modular principle, it will be 
further updated in the future, both in terms of hardware 
and in terms of developing new applications based on VR 
and AR, with the aim of improving the quality of training of 
medical students and improving the qualification of surgi-
cal personnel, which allows various skills and capabilities 
of the instruments to be acquired and tested before their 
application in real laparoscopic operations. In the area 
of information protection and access control means, the 
possibilities of using other means will be explored, which 
will be applied at all levels of usability of the accumulated 
information, which will be effectively used in improving 
the work with laparoscopic instruments. The possibilities 
and combinations of means of access control and protec-
tion of information in the developed mechatronic training 
laparoscopic system and the applications developed for it 
will be studied, as discussed in the present publication. A 
secure transfer of the information to central servers (of 
the educational or medical institution) or to specialized 
cloud medical servers is also planned.



97 J Global Clinical Engineering Vol.7 Issue 3: 2025

Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
Simulation

Unity’s physics engine is used to simulate the behaviors 
of objects in the scene and create realistic interactions 
between them, through physics-based behaviors applied 
to GameObjects (Rigidbodies and Colliders). Each of the 
objects should contain a Rigidbody component in order 
to be affected by the physics engine. The configuration 
of the Rigidbody component is made by adjusting the 
properties in the Rigidbody component’s inspector. Some 
of the properties include:

•  Mass: The mass of the object, which affects how it 
will be affected by forces;

•  Drag: The amount of air resistance the object will 
experience;

•  Angular Drag: The amount of resistance the object 
will experience when rotating;

•  Use Gravity: Enables or disables the effect of gravity 
on the object;

•  Is Kinematic: This checkbox makes the object not 
affected by forces, but it will be affected by collisions;

•  Forces can be applied to objects by using the “Add-
Force() function” of the Rigidbody component.

Using Unity’s physics engine enables tool–tissue model 
interactions to be reduced to setting parameter values, 
without the need to write complex programs with physics 
dependencies. The correct settings give a realistic concept 
of the interaction pattern between the two objects, which 
depends greatly on the level of detailing of the mesh.46 
The coding is reduced to a basic script that initiates the 
interaction between collider objects and the deformation 
of the rigid bodies. The script has to be attached to the 
corresponding object. The result from a 3D augmented 
model response because of the impact with external 
objects is shown in Figure 4.

Figure 5 shows screenshots of the MySQL-based da-
tabase in the developed application. Figure 6 shows the 
3D augmented model response during tactile instrument 
interactions simulating in surgical education.

Figure 7 shows a photograph of the laparoscopic 
instrument included in the system (Figure 6). The tool 

FIGURE 4. A 3D augmented model responds because of the 
impact with external objects.

FIGURE 5.  MySQL database.

FIGURE 6.  The 3D augmented model response during tactile 
instrument interactions simulation in surgical training. 



Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
Simulation

J Global Clinical Engineering Vol.7 Issue 3: 2025 98

EVALUATION OF ACQUIRED SKILLS

The review of the literature revealed two approaches 
to evaluate the skills of medical students and staff: (1) 
the objective structured assessment of technical skills 
checklists and (2) the GOALS.47,48 Methods using AR have 
been developed to overcome some of the shortcomings 
of working with laparoscopic instruments, and basic as-
sessment methods have been identified. More information 
on the topic is given by Roberto et al.49 These approaches 
help with the objective assessment of surgical competen-
cies before performing an MIS.50

CONCLUSION

The simulation of realistic interactions has become 
a tangible reality, despite existing challenges such as 
modeling realistic behavior during user interactions, 
fluid dynamics, and force feedback mechanisms. The 
application of computer graphics techniques in medical 
contexts is increasingly prevalent; however, numerous 
research challenges persist. These include the need for 
enhanced realism, a broader array of solution approaches, 
and improved computational methods for applications. 
The optimization of training simulators and the effective 
utilization of computer graphics methods remain critical 
areas for development.

This article presents a simulation approach that 
examines the response of a liver model during tactile 

was developed as part of the “System for analysis and 
control of mechanical properties of biological tissues,” 
and is protected by a utility model.

Figure 8 shows four tips, called end effectors, that 
were designed for contact of the tool with a given surface. 

Several experiments were performed with the developed 
experimental model of a laparoscopic executive instrument.

Figure 9 shows the frame of the AR video stream. 
The program could be installed on smart devices such 

as smartphones or smart glasses and exploit built-in 
microelectromechanical system (MEMS) sensors (accel-
erometer, gyroscope, camera, solid state compass, GPS, 
etc.) to evaluate objects and positions situated in the 
surrounding world.

FIGURE 7.  An experimental module with force capabilities. 

FIGURE 8.  End effectors for an experimental module.

FIGURE 9.  The frame of the AR video stream. The visual inter-
face contains only essential information in order to allow the 
surgeon to concentrate on the medical task.



99 J Global Clinical Engineering Vol.7 Issue 3: 2025

Ivanova, Vasilev, Boneva: Training of Surgical Skills by a 3D Augmented Liver Model Response During Instrument Interactions 
Simulation

interactions with surgical instruments. Initially, the inves-
tigation focuses on the movement of instruments, utilizing 
a direct kinematic task to control actions in teleoperated 
environments. The derived analytical dependencies of 
the transmission functions enable the execution of com-
putational procedures aimed at optimizing dimensions 
within specified constraints, which can subsequently be 
integrated into software for controlling tool movements. 
The architecture of the control program algorithms is re-
viewed, highlighting the simulation module’s relevance to 
this research. This training platform was developed so that 
students and surgeons can improve their qualifications 
without using living organisms— humans and animals

Subsequently, a 3D augmented model simulating a 
human organ’s response to external impacts is developed 
using Unity 3D modeling capabilities. The model’s behav-
ior is illustrated through the collision of two rigid objects 
exhibiting different physical properties. The application 
of the mesh class for deforming a 3D object within Unity 
is implemented via scripting. Results depicting the 3D 
augmented model’s response to external impacts are 
presented, with the coding distilled into a fundamental 
script that initiates interactions between collider objects 
and the deformation of rigid bodies. This script must be 
attached to the corresponding object, with an example 
provided utilizing the Unity Engine.

Future investigations will specifically focus on compu-
tational methods and animation projections to quantify 
both tool–tissue forces and maximum local strength. The 
outcomes of this research are deemed applicable to surgi-
cal education, allowing for the development of training 
tasks aimed at cultivating skills necessary for minimally 
invasive surgical procedures.

AUTHOR CONTRIBUTIONS

Conceptualization, V.I., P.V.V. and A.T.B.; Methodology, 
V.I., P.V.V. and A.T.B.; Software, P.V.V. and A.T.B.; Hardware, 
V.I.; Validation,  V.I, P.V.V. and A.T.B.; Formal Analysis, V.I 
and P.V.V.; Investigation V.I., P.V.V., and A.T.B.; Re-sources, 
V.I. and P.V.V.; Data Curation, V.I.; Writing–Original Draft 
Preparation, V.I., P.V.V. and A.T.B.; Writing–Review & Ed-
iting, V.I., P.V.V. and A.T.B.; Visualization, P.V.V. and A.T.B.; 
Supervision, V.I. and P.V.V.; Project Administration, V.I.

ACKNOWLEDGMENTS

This work is developed as part of contract №: 
BG16RFPR002-1.002-0009-C01, project name: 'Regional 
Center for Digital Solutions and Innovation NCIZ’, under 
Procedure BG16RFPR002-1.002-Funding of selected by the 
European Commission European Digital Innovation Hubs 
awarded with Seal of Excellence, funded by Operational 
Programme 'Research, Innovation and Digitalization for 
Smart Transformation’.

FUNDING

This research received no external funding.

DATA AVAILABILITY STATEMENT

Not applicable.

CONFLICTS OF INTEREST

The authors declare no conflict of interest.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

Not applicable.

CONSENT FOR PUBLICATION

Not applicable.

CONSENT FOR PUBLICATION

Not applicable.

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