Blending Realities: Accessible Mixed Reality for Tremor Rehabilitation

in Parkinson’s Disease

Xinjun Li

1,∗ a

and Zhenhong Lei

2,∗ b

Information Science, Cornell University, 1 E Loop Rd., New York, U.S.A.

Architecture Department, Rhode Island School of Design, 20 Washington Place, Providence, U.S.A.

Keywords:

Augmented Reality, Mixed Reality, Hand Rehabilitation, Parkinson’s Disease, Assistive Device, Haptic

Feedback.

Abstract:

This position paper presents a novel MR-based hand motion assistance device designed for individuals with

Parkinson’s disease (PD)-related tremor disorders. We argue that the integration of ergonomic hardware design

with adaptive MR software can signiﬁcantly enhance the efﬁcacy of tremor rehabilitation, improve patient en-

gagement, and lead to superior functional outcomes. Our approach combines a smartphone-based MR system

with an ergonomic physical support device, leveraging advanced spatial computing, computer vision algo-

rithms, and haptic feedback technologies. This innovative solution addresses both immediate stabilization

needs and long-term motor skill improvement, potentially revolutionizing home-based rehabilitation for mil-

lions of PD patients worldwide. By seamlessly blending virtual and real-world elements, our system creates

immersive, interactive, and personalized therapeutic experiences that overcome the limitations of traditional

rehabilitation methods. The paper discusses the design research methodology, comparative analysis with ex-

isting approaches, and the potential impact of this technology on PD rehabilitation.

1 INTRODUCTION

Parkinson’s disease (PD) is a progressive neurodegen-

erative disorder that affects millions worldwide, with

an estimated 930,000 people living with PD in the

United States alone by 2020, projected to rise to 1.2

million by 2030 (Marras et al., 2021). This alarming

increase underscores the urgent need for innovative

therapeutic approaches. The primary motor symp-

toms of PD, including tremors, rigidity, and bradyki-

nesia, signiﬁcantly impact patients’ quality of life and

ability to perform activities of daily living (ADLs)

(Dorsey et al., 2020).

Traditional rehabilitation methods often fall short

in addressing the complex needs of PD patients, par-

ticularly in maintaining long-term engagement and

providing personalized care. In recent years, mixed

reality (MR) technologies have emerged as a promis-

ing solution for enhancing rehabilitation outcomes in

various medical ﬁelds. By seamlessly blending vir-

tual and real-world elements through advanced spa-

https://orcid.org/0009-0005-5171-3566

https://orcid.org/0009-0006-3734-7421

∗

Authors contributed equally and shall both be consid-

ered ﬁrst authors

tial computing and computer vision algorithms, MR

offers unique opportunities to create immersive, inter-

active, and adaptive therapeutic experiences (Cipresso

et al., 2022). This paper presents a novel MR-based

hand motion assistance device designed speciﬁcally

for individuals with Parkinson’s-related tremor dis-

orders. Our approach combines ergonomic physical

support with MR applications to provide a compre-

hensive rehabilitation solution that addresses both im-

mediate stabilization needs and long-term motor skill

improvement.

The proposed system leverages the ubiquity of

smartphones and advanced haptic feedback technolo-

gies to deliver accessible and cost-effective MR ther-

apy, potentially reaching millions of patients world-

wide. By integrating cutting-edge sensor technol-

ogy with intuitive user interfaces based on advanced

spatial mapping and object recognition techniques,

our device aims to revolutionize home-based rehabil-

itation for PD patients. This paper argues that the

combination of ergonomic hardware design and adap-

tive MR software can signiﬁcantly improve the efﬁ-

cacy of tremor rehabilitation, enhance patient engage-

ment through gamiﬁcation techniques, and ultimately

lead to better functional outcomes for individuals with

Li, X. and Lei, Z.

Blending Realities: Accessible Mixed Reality for Tremor Rehabilitation in Parkinson’s Disease.

DOI: 10.5220/0013321800003912

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

In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2025) - Volume 1: GRAPP, HUCAPP

and IVAPP, pages 371-375

ISBN: 978-989-758-728-3; ISSN: 2184-4321

371

Parkinson’s disease.

2 COMPARATIVE ANALYSIS

The landscape of PD rehabilitation has evolved sig-

niﬁcantly in recent years, with various technologies

emerging to address the limitations of traditional ther-

apies. This section provides a comparative analysis of

existing approaches and highlights the unique advan-

tages of our proposed MR-based system.

Conventional rehabilitation methods for PD typi-

cally involve a combination of physical therapy, occu-

pational therapy, and medication management. While

these approaches have shown some efﬁcacy, they of-

ten lack the ability to provide real-time feedback and

personalized adaptation to patient needs (Bloem et al.,

2021).

Recent advancements in wearable technologies

have led to the development of various tremor-

suppression devices. For instance, researchers have

introduced a wrist-worn device that uses mechani-

cal oscillations to counteract tremors (Pahwa et al.,

2022). While such devices provide immediate tremor

reduction, they do not address the underlying motor

control deﬁcits or promote long-term skill acquisi-

tion. Our system combines physical stabilization with

interactive MR exercises, fostering both immediate

symptom relief and sustained motor learning through

neuroplasticity-inducing protocols.

Virtual reality (VR) has also been explored as a

tool for PD rehabilitation. Studies have demonstrated

that VR-based balance training could improve postu-

ral stability in PD patients (Wang et al., 2023). How-

ever, fully immersive VR systems often isolate users

from their real environment, limiting the transfer of

skills to daily activities. Our MR approach bridges

this gap by overlaying virtual elements onto the real

world using advanced spatial mapping and object

recognition techniques, allowing patients to practice

tasks in a context-relevant manner with seamless in-

tegration of digital and physical environments.

Smartphone-based applications for PD manage-

ment have gained popularity due to their accessibility

and ease of use. Researchers have developed a mobile

app for remote monitoring of PD symptoms (Arora

et al., 2021). While such apps provide valuable data

collection capabilities, they typically lack the physical

support component crucial for tremor management.

Likewise, attempts to integrate the two may still need

improvements in user interface and usability (Lei and

Li, 2024). In contrast, our MR-based system offers

continuous monitoring and adjustment of therapy in-

tensity based on individual performance and progress

to analyze movement patterns and optimize treatment

protocols.

The unique contribution of our proposed sys-

tem lies in its holistic approach to PD rehabilita-

tion. By seamlessly integrating physical support, real-

time sensing, and adaptive MR exercises, we create

a comprehensive solution that addresses multiple as-

pects of tremor management and motor skill improve-

ment. This multifaceted approach has the potential to

yield superior outcomes compared to existing single-

modality interventions, as evidenced by preliminary

studies showing signiﬁcant improvements in both mo-

tor function and quality of life metrics.

3 DESIGN RESEARCH

METHODOLOGY

Our design research methodology follows a user-

centered, iterative approach to develop an effective

MR-based rehabilitation system for PD patients. The

process encompasses three main phases: user needs

assessment, prototype development, and iterative re-

ﬁnement. In the initial phase, we conducted a com-

prehensive literature review to identify key challenges

faced by PD patients in daily activities and existing

gaps in current rehabilitation approaches. This was

supplemented by in-depth interviews with neurolo-

gists, occupational therapists, and PD patients to gain

insights into speciﬁc user needs and preferences. The

ﬁndings from this phase informed the development

of our initial design requirements, emphasizing the

importance of ergonomic comfort, intuitive usabil-

ity, and adaptive feedback mechanisms (Espay et al.,

2021).

The prototype development phase involved the

creation of both hardware and software components.

The physical device was designed using advanced 3D

modeling software and rapid prototyping techniques,

allowing for quick iterations based on user feedback.

The MR application was developed using the Unity

platform, leveraging its robust AR Foundation frame-

work and cross-platform compatibility. We imple-

mented state-of-the-art computer vision algorithms

for object recognition and tracking, enabling the sys-

tem to provide context-aware guidance during daily

tasks (Maetzler et al., 2022).

Iterative reﬁnement was carried out through a se-

ries of usability tests and focus group sessions with

PD patients and healthcare professionals. These ses-

sions provided valuable insights into the ergonomic

aspects of the device, the intuitiveness of the MR in-

terface, and the overall user experience. Quantitative

data on tremor reduction and task performance were

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collected using embedded sensors and analyzed us-

ing advanced signal processing to assess the system’s

efﬁcacy. This iterative process allowed us to contin-

uously improve the design, addressing issues such as

device weight, grip comfort, and exercise complexity

(Ginis et al., 2023).

Throughout the design process, we adhered to eth-

ical guidelines for medical device development and

ensured compliance with relevant regulatory stan-

dards. The integration of smartphone technology in

our system was carefully considered to balance func-

tionality with accessibility, aiming to create a solution

that could be widely adopted across diverse socioeco-

nomic backgrounds (Lei and Li, 2024).

By employing this rigorous design research

methodology, we have developed a MR-based reha-

bilitation system that not only addresses the imme-

diate needs of PD patients but also has the potential

to evolve and adapt to individual user progress over

time. The following sections will delve into the spe-

ciﬁc design features and technical implementation of

our proposed solution, highlighting the innovative as-

pects that set it apart in the ﬁeld of neurorehabilita-

tion.

4 DESIGN RESEARCH PROCESS

4.1 Device Mock-up

The development of the hand motion assistance de-

vice involved an iterative design process that aimed

to provide ergonomic support and tremor stabilization

for older individuals with Parkinson’s-related tremor

disorders. This lightweight device, weighing only

146 grams, was designed with an open-close mech-

anism to mimic natural hand movements essential for

tasks such as grasping and releasing objects. In its

resting state, the device maintains an open-hand posi-

tion that mirrors the palm’s natural curvature, allow-

ing users to initiate a grip comfortably and intuitively.

When the user grasps an object, the device’s embed-

ded servo motor activates to counteract tremors, lock-

ing the handles to stabilize the grip and reduce mus-

cular strain during task performance (Figure 1).

To achieve seamless usability, the device was

scaled to align with a variety of hand sizes and inte-

grated with components that enable dynamic response

to user movement. The servo motor embedded within

the thumb component not only facilitates movement

but also serves as a stabilizer, providing responsive

adjustments that enhance the user’s control over hand

movements. During the release phase, a button press

disengages the servo motor, allowing the device to

Figure 1: Functional diagram.

return smoothly to the open position. This friction-

less transition between gripping and releasing actions

minimizes the effort required from users, promoting

independence in daily activities by lessening the need

for constant grip maintenance (Figure 2).

Figure 2: Iterative design process.

The ergonomic features of the device were reﬁned

based on extensive feedback from healthcare profes-

sionals and individuals with tremor disorders, who

emphasized the importance of both comfort and func-

tionality. The ﬁnal prototype reﬂects these insights,

incorporating a form-ﬁtting design that supports the

hand’s natural range of motion and allows for sta-

ble, precise hand movements. Additionally, the adapt-

able mechanism supports a range of tremor severities,

providing immediate physical support while allowing

users to engage in activities that enhance motor con-

trol and dexterity.

4.2 Physical Prototype Design

Ergonomically, the device was designed to conform

to the natural contours of the hand, providing intu-

itive support for daily single-hand tasks such as grip-

ping and releasing objects. Its open-close mechanism

mimics natural hand movements, reducing strain and

enhancing ease of use. The device accommodates

a wide range of hand sizes and tremor patterns, re-

ﬂecting its adaptability to diverse user needs. Im-

portantly, the design encourages seamless transitions

between different hand positions, enabling users to

Blending Realities: Accessible Mixed Reality for Tremor Rehabilitation in Parkinson’s Disease

373

perform tasks independently and with minimal effort

(Figure 3).

Figure 3: Physical device prototype.

To counteract tremors effectively, the device in-

corporates a stabilization system that dynamically ad-

justs to variations in tremor intensity. A servo motor

embedded within the thumb component plays a dual

role as an actuator and stabilizer, enabling real-time

responses to user movements. This feature allows

the device to lock securely during gripping actions

while maintaining ﬂexibility during release, ensuring

both stability and natural motion. The stabilization

mechanism is complemented by embedded sensors,

including a gyroscope, which track orientation and

motion data. This data is transmitted to a MR sys-

tem, enabling synchronized virtual feedback that sup-

ports therapeutic exercises and enhances the overall

user experience.

The physical prototype was fabricated using 3D

printing technology, ensuring precision and adaptabil-

ity. The dual-component structure, connected by a

hinge, replicates the natural opposition between the

thumb and ﬁngers, a critical aspect of effective grip-

ping. The ergonomic design of the prototype mir-

rors the natural curvature of the palm, providing a

comfortable ﬁt that supports stable and precise hand

movements. A compact battery, integrated with an

Arduino Nano board and low-energy Bluetooth con-

nectivity, powers the device, allowing for lightweight,

portable, and wireless operation. These features not

only enhance mobility but also enable the potential for

telehealth applications, where healthcare providers

can remotely monitor and adjust device settings.

Feedback from initial testing sessions with health-

care professionals and users inﬂuenced the ﬁnal

design, emphasizing the importance of ergonomic

adaptability and mechanical precision. The physi-

cal prototype thus provides an effective balance be-

tween biomechanical support and ease of use, pro-

moting natural hand movement while addressing the

stabilization needs speciﬁc to older adults with tremor

disorders. By aligning the mechanical structure with

natural hand dynamics, this design supports sustained

improvements in hand dexterity and user autonomy,

reﬂecting a tailored approach to neurorehabilitation.

4.3 Mixed Reality System

The MR system revolutionizes rehabilitation for

Parkinson’s patients by combining virtual guidance

with physical stabilization on an accessible smart-

phone platform. This innovative approach leverages

familiar, cost-effective technology to deliver adaptive,

engaging therapy while broadening access to under-

served communities.

The MR system utilizes the smartphone’s camera

to recognize real-world objects and facilitate interac-

tion. By pointing the camera at items such as books

or cups, users activate the ”Grab Suggestion” feature.

This feature processes successive frames to analyze

object attributes, such as dimensions and orientation

and provides recommendations for optimal gripping

techniques. This functionality supports motor skill

rehabilitation by guiding users in adjusting hand po-

sitioning and improving object manipulation. (Fig-

ure 4)

Figure 4: Smartphone AR interface.

Integrated with the physical prototype, the MR

system receives data from an embedded gyroscope

that tracks the user’s hand movements. This data is

processed in real time and displayed as a virtual rep-

resentation on the smartphone screen. The immediate

feedback enables users to adjust their grip strength

and hand positioning with precision, fostering im-

proved task accuracy and conﬁdence.

The system’s adaptability is a key feature, as it

adjusts the difﬁculty of tasks based on the user’s

progress. This ensures that rehabilitation remains ap-

propriately challenging and engaging. Gamiﬁed ex-

ercises further enhance the experience by motivat-

ing users to remain consistent in their therapy regi-

mens. The smartphone’s familiar interface and ability

to evolve through software updates provide an acces-

sible and user-friendly platform for delivering these

features.

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374

By leveraging smartphones as the central plat-

form, the MR system offers a cost-effective alter-

native to traditional MR hardware, which often re-

lies on expensive and specialized equipment. The

widespread availability of smartphones, combined

with their advanced processing capabilities, allows

for broader adoption across resource-constrained and

underserved areas. This affordability and scalability

make the system particularly impactful for individu-

als in rural or low-income settings, where access to

healthcare technology is often limited.

5 CONCLUSION AND

DISCUSSION

The proposed MR-based hand motion assistance de-

vice advances neurorehabilitation for Parkinson’s dis-

ease by integrating physical support with adaptive

MR exercises to address tremor management and mo-

tor skill improvement comprehensively. This holis-

tic approach combines ergonomic hardware with ad-

vanced software, leveraging smartphone technology

for accessibility, cost-effectiveness, continuous mon-

itoring, and personalized therapy.

While existing technologies like wearable tremor-

suppression devices and VR-based systems show

promise, they often lack a complete solution for

immediate symptom relief and long-term skill ac-

quisition. Our MR-based system bridges this gap

with real-time stabilization, adaptive feedback, and

context-aware training. Developed through an itera-

tive design process, the system prioritizes ergonomic

comfort, intuitive usability, and therapeutic efﬁcacy.

Advanced spatial mapping and object recognition

techniques provide context-aware guidance, enhanc-

ing skill transfer to real-world activities.

While the initial results are promising, further re-

search is needed to validate the long-term efﬁcacy

of our MR-based system in large-scale clinical trials.

Future work should focus on integrating smartphone

functionality with stabilizers, dual-hand functionality,

and exploring the potential for telehealth applications

to extend the reach of specialized PD care to under-

served populations.

In conclusion, our position paper argues that the

convergence of MR technology and ergonomic design

has the potential to revolutionize PD rehabilitation.

By providing a personalized, engaging, and compre-

hensive therapeutic experience, our proposed system

represents a signiﬁcant step forward in improving the

quality of life for individuals living with Parkinson’s

disease. As we continue to reﬁne and validate this

technology, we anticipate that MR-based rehabilita-

tion will become an integral component of PD man-

agement strategies, offering new hope to millions of

patients worldwide.

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