VR-ADAPT: An Immersive Learning and Training Environment for

Wheelchair Users with Recent Spinal Cord Injuries

Javier Albusac

, Diego Cordero

, Mario Jim

enez

, Rub

en Grande

, Vanesa Herrera

Raquel Perales

, M. Eugenia San Felix

and Ana de los Reyes

School of Computer Science, University of Castilla-La Mancha, Paseo de la Universidad 4, 13071 Ciudad Real, Spain

Hospital Nacional de Parapl

ejios de Toledo, Carretera de la Peraleda s/n, 45004 Toledo, Spain

Keywords:

Virtual Reality, Wheelchair Simulator, Rehabilitation, Gamiﬁcation, Spinal Cord Injury, Autonomous

Learning.

Abstract:

Each year, thousands of people worldwide suffer injuries that limit their mobility, affecting not only their

ability to walk but also, in many cases, the functionality of their upper limbs. These conditions represent a

drastic life change for patients, who must undergo an initial process of learning and adaptation to their new

circumstances. To address this challenge, we present VR-ADAPT, an innovative virtual reality-based platform

designed to facilitate the transition to a more autonomous life. VR-ADAPT integrates an advanced simulator

for learning to operate electric wheelchairs and digitized environments based on domestic and workplace

settings. These environments are gamiﬁed through serious games, allowing users to practice and develop

essential skills for conﬁdently navigating their daily lives. Additionally, the platform includes a kinematic

recording and analysis module that collects detailed data during exercises. This functionality provides clinical

teams with a valuable tool for objectively evaluating patients’ progress, enhancing the personalization and

effectiveness of therapies.

1 INTRODUCTION

Each year, between 250,000 and 500,000 new spinal

cord injuries occur worldwide, signiﬁcantly impair-

ing mobility, affecting not only the ability to walk

but also, in many cases, the functionality of the upper

limbs. This impact radically transforms the lives of

those affected, particularly in the early stages follow-

ing the injury, when they face the challenge of adapt-

ing to new circumstances. This period is critical, as

it involves not only accepting physical limitations but

also learning skills that enable them to regain a degree

of autonomy and improve their quality of life.

For instance, operating an electric wheelchair can

become a complex and daunting task for someone

who has never used such devices before. Control-

ling speed, making precise turns in conﬁned spaces,

or tackling everyday obstacles like ramps and curbs

requires a learning curve that can be frustrating with-

out proper guidance and practice. Similarly, daily

tasks such as reaching for and handling objects in a

home environment—like picking up a glass from a

high shelf or opening a jar of food—can pose signif-

icant challenges. These difﬁculties not only test the

patient’s physical abilities but also their psychologi-

cal and emotional resilience as they adapt to a new

way of life.

The process of adapting to these new circum-

stances is fraught with challenges that extend beyond

physical limitations (Herrera et al., 2025). The mag-

nitude of change in patients’ daily lives can lead to

feelings of uncertainty and frustration, particularly

when faced with tasks such as learning to operate an

electric wheelchair or performing basic activities in

the home and workplace environments. The lack of

safe and controlled spaces where they can practice

these skills exacerbates the situation, as mistakes dur-

ing this learning period can result in accidents or re-

inforce insecurities, further hindering their progress

toward autonomy (Arlati et al., 2019).

In this context, new technologies have proven to

be effective tools for facilitating the adaptation pro-

cess (Hoter and Nagar, 2023). Digital platforms, sim-

ulators, and interactive tools provide patients with

safe and controlled environments that replicate real-

world challenges. These solutions not only allow

users to practice and reﬁne speciﬁc skills without risk

but also optimize learning by offering scenarios that

can be tailored to their individual needs, promoting

gradual and structured progress.

Albusac, J., Cordero, D., Jiménez, M., Grande, R., Herrera, V., Perales, R., Felix, M. E. S. and Reyes, A. L.

VR-ADAPT: An Immersive Lear ning and Training Environment for Wheelchair Users with Recent Spinal Cord Injuries.

DOI: 10.5220/0013352900003929

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 27th International Conference on Enterprise Information Systems (ICEIS 2025) - Volume 2, pages 573-580

ISBN: 978-989-758-749-8; ISSN: 2184-4992

573

Particularly, Virtual Reality (VR) stands out as a

promising technology in this ﬁeld. Its ability to cre-

ate immersive and interactive environments enables

patients to engage in simulations that replicate real-

world scenarios (Genova et al., 2022), such as ma-

neuvering in conﬁned spaces, overcoming urban ob-

stacles, or navigating a simulated kitchen or ofﬁce.

This provides them with a unique opportunity to de-

velop essential skills in a gamiﬁed environment that

transforms learning into a motivating experience.

Both the challenges and motivation described

form the basis of our proposal: VR-ADAPT, a VR-

based platform for learning and training aimed at in-

dividuals with recent mobility-limiting injuries, de-

signed to support and complement their initial adap-

tation process. This project is a collaboration with the

Hospital Nacional de Parapl

ejicos de Toledo (HNPT)

and is funded by Indra and the Fundaci

on Univer-

sia (supported by Banco Santander) through the 8th

Call for Research Grants in Accessible Technologies.

The platform includes an immersive simulator for op-

erating electric wheelchairs, virtualization of super-

vised domestic and workplace environments, the in-

tegration of serious games within these spaces to per-

form daily tasks while simultaneously undergoing re-

habilitative therapy to recover mobility, and, ﬁnally,

the recording of kinematic data from sessions to en-

able therapists to objectively assess each patient’s

progress.

The implementation of VR-ADAPT is expected to

yield multiple beneﬁts for both patients and the clini-

cal teams responsible for their rehabilitation. For pa-

tients, the platform offers a safe and controlled en-

vironment where they can progressively acquire es-

sential skills without the risks associated with prac-

ticing in real-world settings. This not only facili-

tates the learning of practical abilities, such as operat-

ing electric wheelchairs and performing domestic and

workplace tasks, but also boosts their conﬁdence to

face real-life situations, promoting greater indepen-

dence in their daily lives. For clinical professionals,

the platform provides an advanced tool for evaluat-

ing and personalizing therapies through the record-

ing and analysis of kinematic data from each session.

This approach enables objective monitoring of patient

progress and allows therapeutic interventions to be

tailored to individual needs, thereby optimizing treat-

ment effectiveness and improving overall rehabilita-

tion outcomes. Ultimately, VR-ADAPT has the po-

tential to signiﬁcantly enhance patients’ quality of life

by accelerating their adaptation to a new environment

and reducing the barriers they face in their daily ac-

tivities.

2 RELATED WORK

Wheelchair simulators have been established as effec-

tive and safe tools for training and assessment, of-

fering controlled environments where users can de-

velop essential navigation skills and perform complex

tasks. Additionally, they are valuable for analyzing

progress in physical and cognitive rehabilitation. Re-

cent evidence highlights that these platforms not only

enable the transfer of skills to real-world scenarios

but also improve users’ conﬁdence and quality of life

(Alapakkam Govindarajan et al., 2022), (Ortiz et al.,

2021).

The sense of presence (SoP), deﬁned as the sub-

jective perception of ”being there,” is identiﬁed as a

crucial factor for the effectiveness of simulators. Var-

ious studies have shown that the use of virtual re-

ality (VR) technologies, such as head-mounted dis-

plays (HMDs), enhances immersion, although they

can induce cybersickness symptoms, particularly in

users with limited mobility (Vailland et al., 2020),

(Arlati et al., 2019). The integration of multisensory

feedback, including vestibular and haptic stimuli, im-

proves both the user experience and SoP while mini-

mizing adverse effects (Vailland et al., 2021).

These platforms have evolved to include digitized

domestic and workplace environments, broadening

their applications. For instance, the use of personal-

ized environments enables patients with recent spinal

cord injuries to learn speciﬁc functional skills and

adapt to their new reality. Additionally, gamiﬁcation

and serious games have been employed to maintain

motivation and promote physical recovery (Hoter and

Nagar, 2023).

Kinematic recording stands out as a key com-

ponent, providing objective metrics for evaluating

and adjusting rehabilitation programs. Tools such as

ViEW allow for the analysis of user performance in

both simulated and real conditions, showing a positive

correlation between acquired skills and their transfer

to real-world contexts (Mor

ere et al., 2018).

3 VR-ADAPT PLATFORM

Figure 1 provides an overview of the architecture of

the proposed platform. From bottom to top, the VR

headset allows the user to immerse themselves and

interact with the virtual world. Within the virtual

environment, users can navigate in a wheelchair us-

ing joystick controls or interact with virtual elements

using their hands, free of any controllers. This lat-

ter functionality is utilized in the serious games inte-

grated into the learning platform.

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Wheelchair

VR Simulator

Learning

Module

Domestic

Environment

Working

Environment

Serious

Games

Core

Recording and analysis of kinematics

VR HeadSet

Level Selector

Map Generator

Hand Tracking

Joystick Controller

Wheelchair Selector

Head

Right hand

Left hand

3D-printed

joystick

grips

Wheelchair

Camera mode

Figure 1: General architecture of the proposed platform.

To enable this, the headset itself includes a module

that tracks the user’s hands and head, as well as a joy-

stick controller. For patients with spinal cord injuries

affecting the upper limbs—particularly those who do

not have mobility in the hands or ﬁngers—the stan-

dard joystick associated with the VR headset lacks the

necessary accessibility features, especially due to its

small size. This creates the need to fabricate larger

and diverse grips using 3D printing, which can be at-

tached to the mini-joystick controller and simulate the

grips typically found on electric wheelchairs. Further

details on this topic will be provided in the next sec-

tion.

On the other hand, the intermediate level consists

of the wheelchair simulator. This simulator includes

options for selecting the camera mode, choosing maps

based on their level of complexity, selecting the type

of wheelchair to emulate, and generating maps ac-

cording to a set of predeﬁned rules. The camera mode

selector allows users to switch between different per-

spectives depending on their tolerance to movement

in immersive environments. A higher tolerance en-

ables a ﬁrst-person view mode, while for users experi-

encing discomfort or motion sickness, a third-person

mode with minimal camera movement may be more

suitable. Regarding wheelchair selection, the main

difference lies in the type of traction—front, central,

or rear—which inﬂuences how the wheelchair turns.

Additionally, users can train in predeﬁned spaces ap-

proved by therapists or create new maps to practice in.

There is a connection with the lower level, as the VR

wheelchair simulator utilizes the VR headset, the con-

troller, and the custom 3D-printed grip that has been

attached.

At the intermediate level, there is also a learning

module featuring the virtualization of domestic and

workplace environments, allowing users to develop

skills for navigating these everyday settings. The pri-

mary goal is to provide users with guided support to

understand potential challenges they might encounter

and how to address them, while simultaneously en-

abling hands-on practice. This module is connected

to a core system that hosts various serious games de-

signed to simulate daily tasks while also targeting

hand and arm exercises, thus contributing to the pa-

tient’s rehabilitation and improved mobility. Within

the immersive space, different games are associated

with speciﬁc zones, with each game’s theme aligning

with the characteristics of the corresponding area.

The wheelchair simulator is connected to the

learning module, allowing the user to navigate

through the virtualized environments using the

wheelchair. It should be noted that the wheelchair

simulator can also be used in open maps without be-

ing associated with domestic or workplace environ-

ments.

Finally, the upper layer focuses on kinematic

recording. During user activity, whether in the

wheelchair simulator or within the virtual environ-

ments of the learning module, the system records all

spatiotemporal data related to wheelchair movement

as well as hand and head tracking. These data, which

can be represented in various formats, provide the

clinical team with an objective means to assess the

patient’s progress.

3.1 3D-Printed Joystick Grips

In this project, we will use the Oculus Meta Quest 2

and 3 models for immersion in virtual spaces. The

choice of these devices is based on a favorable bal-

ance between cost and quality, high versatility, a

large user community, the availability of several units

within the research group as laboratory equipment,

and the team’s experience with the Meta XR Platform

SDK

Both hardware and software resources support

user interaction through external controllers (see Fig-

ure 2) as well as hand tracking for controller-free use.

In both cases, the system provides high precision,

with the latter offering a virtual representation of the

hands and reliable tracking.

Real electric wheelchairs are operated using a joy-

stick located on either the right or left armrest, de-

pending on the user’s most skillful hand. The interac-

tion mode intended for implementation in the virtual

https://developers.meta.com/horizon/downloads/

package/meta-xr-platform-sdk/

VR-ADAPT: An Immersive Learning and Training Environment for Wheelchair Users with Recent Spinal Cord Injuries

575

Figure 2: On the left, the controller model used for the Ocu-

lus Meta Quest 2. On the right, the controller model for the

Oculus Meta Quest 3.

Figure 3: Adapter designed for attachment to joysticks of

Oculus Meta Quest 2 and 3. At the bottom, 3D-printable

joystick handle models for mounting onto the adapter.

wheelchair simulator closely mimics this setup. How-

ever, as shown in Figure 2, the size of the joysticks

is too small. This issue is particularly critical for pa-

tients with spinal cord injuries, whose upper limbs are

affected and who face difﬁculties with gripping.

To address this problem, the project has set as

one of its objectives the fabrication of larger, differ-

ently shaped grips using 3D printing, designed to be

mounted onto the original controller. Since the origi-

nal joystick can be removed (see Figure 3), the HNPT

department responsible for designing and manufac-

turing adapters has developed a piece that attaches to

the movable shaft of the original controller. Once the

adapter is constructed, additional grip models in vari-

ous shapes (see the bottom of Figure 3) are fabricated

and mounted onto the intermediate piece, facilitating

their attachment.

3.2 Wheelchair VR Simulator

The VR simulator for wheelchair operation is set in

a sports hall with a spacious court measuring 45x25

meters (see Figure 4). Within this space, various

elements are placed to represent the milestones the

learner must reach, such as target points, zones to

cross, or turning maneuvers around speciﬁc markers.

The simulator includes a variety of maps, de-

signed in collaboration with the HNPT team, arranged

by levels of difﬁculty to facilitate gradual and con-

trolled learning. Additionally, the simulator imple-

ments three viewing modes:

• First-Person View. The VR camera is positioned

directly at the patient’s eye level, offering a fully

immersive experience. The primary drawback

of this mode is the potential for motion sickness

caused by the sensation of movement while the

body remains stationary. The simulator allows the

wheelchair’s movement speed to be adjusted ac-

cording to the user’s tolerance level.

• Third-Person View. The user sees the wheelchair

from an external perspective. Camera movement

is minimal and only adjusts when the wheelchair

moves sufﬁciently far from the current view.

While this mode is less realistic, it is designed for

users who experience severe motion sickness in

the ﬁrst mode.

• First-Person View Without VR Headset. In this

mode, similar to the ﬁrst, the VR camera is po-

sitioned at the patient’s eye level. However, the

scene is projected onto an external monitor, and

the patient does not wear a VR headset. This

semi-immersive mode is speciﬁcally intended for

users who cannot tolerate the other two modes.

Additionally, the simulator allows users to select

and train with electric wheelchairs featuring differ-

ent traction types: front-wheel, mid-wheel, and rear-

wheel. The physics simulator included in Unity, uti-

lized in this project, accurately replicates these be-

haviors. Traction primarily inﬂuences power delivery

but, more importantly, affects the wheelchair’s turn-

ing mechanism. Through this simulation, both the

patient and the hospital’s professional team can deter-

mine the type of wheelchair best suited to the patient’s

abilities.

Finally, two key components of the simulator de-

serve special mention: gamiﬁcation and movement

tracking. On the one hand, the simulator employs

gamiﬁcation techniques to enhance the patient’s mo-

tivation. These include scoring systems, milestone

completion tracking based on time, and visual and au-

ditory feedback associated with speciﬁc events. On

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576

Figure 4: Third-person view of the wheelchair simulator

prototype developed to date.

the other hand, the simulator records spatiotemporal

data of the wheelchair during activity sessions, en-

abling the evaluation of the patient’s progress. This

functionality will be discussed in greater detail later.

As we will see in the following section, patients

also have the opportunity to practice their wheelchair

skills in virtualized domestic or workplace environ-

ments, which more closely resemble the settings they

encounter in their daily lives. These are typically

smaller spaces, requiring a higher level of control over

the wheelchair from the user.

3.3 Learning Module: Virtual Domestic

and Working Environments

In addition to the wheelchair simulator, the plat-

form aims to incorporate virtualized environments for

learning and training. These primarily include domes-

tic settings, such as the home, where patients spend a

signiﬁcant amount of time, and workplace environ-

ments where they might engage in professional ac-

tivities. These spaces not only require wheelchair

navigation but also encourage users to perform tasks

that involve hand use. Basic functionalities are mod-

eled in these environments, such as turning lights on

and off, opening doors, or adjusting furniture height,

among others. Additionally, various serious games

are integrated into speciﬁc areas within these spaces.

The gameplay mechanics themselves require users to

achieve milestones, which, through gamiﬁcation, en-

hance patient motivation and engagement.

One of the domestic environments already virtual-

ized is the adapted apartment at HNPT. This physical

space allows patients to practice and experience sen-

sations very similar to those they might encounter at

home. It includes a kitchen, a living room, a bedroom,

and a bathroom. Figure 5 shows a digital version of

the adapted apartment on the left and real photos of

some areas on the right. The digitalization process

was carried out using Polycam

software and LiDAR

https://poly.cam/

sensors from an iPhone 15 PRO. The model was re-

ﬁned in Blender

and subsequently integrated into a

Unity 3D

project for visualization with Oculus Meta

Quest 2 and 3 devices.

Throughout the virtual apartment, ﬂoating help

buttons are distributed across different areas. At any

time, the user can interact with them. When activated,

a virtual monitor appears near the user (see Figure 6),

playing a real video featuring a therapist or an expe-

rienced patient. In each video, the speaker provides

the user with relevant information about the associ-

ated area and offers recommendations to overcome

potential challenges.

On the other hand, as mentioned earlier, the vir-

tualized spaces incorporate several serious games

across the different rooms. All these games feature

a scoring system, time tracking, and visual and au-

ditory feedback to notify the user of each occurring

event. In the speciﬁc case of the virtualized adapted

apartment at HNPT, the following serious games are

intended to be integrated:

• Kitchen Cleaning. The objective of this game

is to collect plates and utensils from the coun-

tertop and load them into the dishwasher. This

game involves arm and hand movements, as well

as wheelchair navigation.

• Recipe Preparation. The game displays various

ingredients on the kitchen countertop. The user

must follow a speciﬁc sequence to prepare the

meal. It requires arm and hand movements and

wheelchair navigation, as some ingredients need

to be retrieved from the refrigerator.

• Box and Block on the Living Room Table. Box

and Block is a standard test used in upper limb

rehabilitation. It consists of a wooden box divided

into two sections. One section contains wooden

blocks, and the patient must grasp and move them

to the other side of the box. This serious game has

already been developed and integrated (see Figure

7). It involves arm and hand movements without

requiring wheelchair navigation.

• Packing a Travel Suitcase. This serious game is

associated with the bedroom. The user must take

clothes from the wardrobe in the bedroom and

pack them into a suitcase on a table (see Figure

8). The game involves arm and hand movements

and slight wheelchair navigation.

• Tooth Brushing in the Bathroom. The serious

game simulates brushing teeth, requiring circu-

lar arm movements without the need for electric

wheelchair navigation.

https://www.blender.org/

https://unity.com/

VR-ADAPT: An Immersive Learning and Training Environment for Wheelchair Users with Recent Spinal Cord Injuries

577

Figure 5: On the left side of the image, a digital version of the adapted apartment at HNPT is shown. On the right side, real

photographs of the bathroom and kitchen are displayed.

Figure 6: Playback of real video on virtual screens, pro-

viding guidance and recommendations from therapists and

experienced patients.

3.4 Recording and Analysis of

Kinematics

A key feature of the proposed platform is the mon-

itoring and recording of user activity, both during

VR wheelchair simulator sessions and while engag-

ing with the serious games integrated into the virtu-

alized environments. Recording spatiotemporal data

for the virtual wheelchair is relatively straightforward.

Since the wheelchair exists entirely as a virtual en-

tity (represented as a GameObject) within a three-

dimensional virtual environment, it is possible to con-

tinuously track and record its position along the x, y,

and z axes. The lower section of Figure 9 provides

an example of a graphical representation of the move-

ment of a virtual wheelchair in an open space.

Figure 7: Virtualization of the standard Box & Block test for

inclusion on the living room table. The graphical scheme

also illustrates different types of grips for virtual objects,

considering hands with motor limitations.

In contrast, recording hand movements involves

greater complexity. Oculus Meta Quest VR head-

sets are equipped with four external cameras featuring

a 100-degree ﬁeld of view. These headsets include

a reliable tracking system capable of creating a vir-

tual representation of the hands that accurately aligns

with the position and orientation of the real hands.

Once the hands are virtually represented, interaction

with virtual elements becomes direct. It is possible

to track the position and orientation of the hands, as

well as detect any intersections with other objects. Ta-

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578

Figure 8: Serious game where the user must move clothes

stored in the wardrobe and place them in a suitcase located

on a table.

ble 1 lists the variables the system is currently able to

record. The upper section of Figure 9 provides an ex-

ample of graphical data representation for head move-

ment and left and right hand movements.

From the collected data, metrics are deﬁned to

measure hand velocity, the concentration or density

of recorded points (movement capacity), movement

irregularity, maximum reach ranges, and response ca-

pacity, among others. Comparing these measure-

ments across sessions over time provides therapists

with objective tools for analyzing real progress.

4 DISCUSSION AND

CHALLENGES

The VR-ADAPT platform represents a signiﬁcant ad-

vancement at the intersection of clinical rehabilitation

and immersive technology, offering a safe, ﬂexible,

and gamiﬁed environment to enhance the autonomy

and quality of life of individuals with recent spinal

cord injuries. However, the development and imple-

mentation of this solution present several key chal-

lenges that warrant discussion.

One major challenge is the acceptance of the sys-

tem by both patients and clinical professionals. While

gamiﬁcation techniques and virtual immersion show

promise for enhancing motivation, there is a risk that

some users may perceive these technologies as com-

plex or impractical compared to traditional rehabili-

Figure 9: Movement tracking of the right hand (red), left

hand (blue), and head (yellow). At the bottom, tracking

of movements performed with a virtual wheelchair in an

immersive space.

tation methods. This underscores the importance of

conducting additional studies focused on user experi-

ence and usability.

Another critical issue relates to patients’ tolerance

for simulated movement during virtual wheelchair

navigation. Motion sickness in immersive environ-

ments can limit the effectiveness of learning and re-

habilitation, particularly for more sensitive patients.

Although different viewing modes are proposed, in-

cluding ﬁrst-person mode without VR headsets, care-

ful design of simulation dynamics is required to mini-

mize these adverse effects without compromising the

immersive experience.

Finally, while the platform offers an innovative so-

lution, its integration into clinical processes and val-

idation in real-world settings pose operational chal-

lenges. It is essential to establish protocols that en-

sure the therapeutic effectiveness of exercises within

a virtual environment and their positive impact on the

transfer of skills to the physical world.

VR-ADAPT: An Immersive Learning and Training Environment for Wheelchair Users with Recent Spinal Cord Injuries

579

Table 1: Variables and spatio-temporal information related to kinematics.

Variable Data type Range of values Description

Frame number Integer 0 to n The frame number from the start

of the exercise

Time Float 0 to n seconds The time measured in seconds

Head position Vector x, y, z coordinates Position of HMD in 3D space

Hand detection Boolean True or false Detection of the hand (detected or

undetected)

3D position of hand Vector x, y, z coordinates 3D position of the hand in space

High conﬁdence Boolean True or false Conﬁdence in hand tracking; if

true, the conﬁdence level is high

Hand velocity Vector x, y, z coordinates Velocity of the hand in all direc-

tions

Pinch detection Boolean True or false Detection of a pinch (true or

false)

Palmar grasp detection Boolean True or false Detection of a palmar grasp (true

or false)

Auto-grip Boolean True or false Auto-grip mode status

Wrist twist force Float 0 to 360 Degree of hand rotation relative

to the wrist

5 CONCLUSIONS AND FUTURE

WORK

This article presents VR-ADAPT, an innovative solu-

tion for the rehabilitation of individuals with recent

spinal cord injuries, combining immersive environ-

ments, serious games, and kinematic tracking to sup-

port their transition to a more autonomous life. In the

coming months, the development team will focus on

completing the functionality of the wheelchair simu-

lator, fully integrating the serious games into both do-

mestic and workplace environments, and conducting

studies with real patients at the Hospital Nacional de

Parapl

ejicos de Toledo. These steps will enable the

analysis of the platform’s functionality and usability

in a real-world setting, laying the groundwork for its

clinical validation and future implementation.

ACKNOWLEDGEMENTS

This work has been funded by the company Indra

and the Universia Foundation through the VIII call

for grants for research projects in accessible technolo-

gies, and by University of Castilla-La Mancha under

Project ID 2023-GRIN-34400.

REFERENCES

Alapakkam Govindarajan, M. A., Archambault, P. S., and

Laplante-El Haili, Y. (2022). Comparing the us-

ability of a virtual reality manual wheelchair sim-

ulator in two display conditions. Journal of Re-

habilitation and Assistive Technology Engineering,

9:20556683211067174.

Arlati, S., Colombo, V., Ferrigno, G., Sacchetti, R., and

Sacco, M. (2019). Virtual reality-based wheelchair

simulators: A scoping review. Assistive Technology,

32(6):294–305.

Genova, C., Bifﬁ, E., Arlati, S., Redaelli, D. F., Prini, A.,

Malosio, M., Corbetta, C., Davalli, A., Sacco, M.,

and Reni, G. (2022). A simulator for both manual

and powered wheelchairs in immersive virtual reality

cave. Virtual Reality, 26:187–203.

Herrera, V., Albusac, J., Castro-Schez, J., et al. (2025).

Creating adapted environments: enhancing accessi-

bility in virtual reality for upper limb rehabilitation

through automated element adjustment. Virtual Re-

ality, 29(28).

Hoter, E. and Nagar, I. (2023). The effects of a wheelchair

simulation in a virtual world. Virtual Reality, 27:407–

419.

Mor

ere, Y., Bourhis, G., Cosnuau, K., Guilmois, G., Ru-

milly, E., and Blangy, E. (2018). View: A wheelchair

simulator for driving analysis. Assistive Technology,

32(3):125–135.

Ortiz, J. S., Palacios-Navarro, G., Andaluz, V. H., and Gue-

vara, B. S. (2021). Virtual reality-based framework

to simulate control algorithms for robotic assistance

and rehabilitation tasks through a standing wheelchair.

Sensors, 21(15).

Vailland, G., Devigne, L., Pasteau, F., Nouviale, F., Fraudet,

B., Leblong,

E., Babel, M., and Gouranton, V. (2021).

Vr based power wheelchair simulator: Usability eval-

uation through a clinically validated task with regular

users. In 2021 IEEE Virtual Reality and 3D User In-

terfaces (VR), pages 420–427.

Vailland, G., Gaffary, Y., Devigne, L., Gouranton, V., Ar-

naldi, B., and Babel, M. (2020). Power wheelchair vir-

tual reality simulator with vestibular feedback. Mod-

elling, Measurement and Control C, 81(1-4):35–42.

ICEIS 2025 - 27th International Conference on Enterprise Information Systems

580