Previous Article in Journal
Multiple Ways in Which Video Games Make Education Inclusive: A Systematic Review of Cognitive Enhancement for Neurodivergent Learners
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
MTI
Volume 9
Issue 6
10.3390/mti9060057
mti-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Impacts of Incorporating Virtual Reality and Data Gloves in Exergames on Intrinsic Motivation in Upper-Extremity Assessments: A Study in a Young and Healthy Group

by
He Kunze
1,
Noppon Choosri
1,2,* and
Supara Grudpan
3
1
Software Engineering Department, College of Arts, Media, and Technology, Chiang Mai University, Chiang Mai 50200, Thailand
2
DAKSH Research Group, Chiang Mai University, Chiang Mai 50200, Thailand
3
Digital Game Department, College of Arts, Media, and Technology, Chiang Mai University, Chiang Mai 50200, Thailand
*
Author to whom correspondence should be addressed.
Multimodal Technol. Interact. 2025, 9(6), 57; https://doi.org/10.3390/mti9060057
Submission received: 3 April 2025 / Revised: 19 May 2025 / Accepted: 28 May 2025 / Published: 9 June 2025
Browse Figures
Versions Notes

Abstract

:
Virtual reality (VR) technology has shown potential as a viable tool for rehabilitation. VR is a well-recognized technology that creates immersive experiences to enhance engagement and encourage more effective participation in activities. In the current study, it has been shown that using a standard VR system setup can effectively increase participant motivation for various rehabilitation applications. However, there is a research gap in terms of participant motivation, relating to the intervention of integrating data gloves into VR to improve visibility in hand tracking for rehabilitation. This study presents and assesses an integrated approach utilizing VR and data glove technology to evaluate upper extremity function in a young, healthy population, comparing this to traditional methods. Participants’ intrinsic motivation was measured using the Intrinsic Motivation Inventory (IMI). The findings indicate that the combined immersive environment outperforms conventional practice in most aspects. Therefore, this research also sheds light on the fact that a data glove is promising technology in rehabilitation applications that can augment positive experiences while having no adverse effects on the VR system.

1. Introduction

Virtual reality (VR) is a groundbreaking technology that was initially introduced in the 1950s [1]. It is defined as “the aggregate of hardware and software systems that endeavor to achieve a unified, sensory illusion of being in a different environment” [2]. Immersion is a key characteristic of VR, along with two other important characteristics—presence and interactivity [3].
One of the most promising VR applications, in addition to entertainment, is in the healthcare sector, where virtual immersive environments can be created for patient interventions [4]. Several systematic reviews and meta-analyses have provided evidence that virtual reality (VR) can be used in several medical disciplines, including mental health [5], cardiology [6], neurological diseases [7], autism research [8], and rehabilitation, on which this study is focused [4].
Rehabilitation is characterized as a collection of interventions that are aimed at improving functionality and minimizing disability in people with health conditions related to their environment [9]. This research focuses on upper-extremity (UE) rehabilitation, which is related to the recovery of the musculoskeletal system in the upper body, which includes the arms, shoulders, and hands.
In the past decade, there has been a significant increase in the amount of research conducted on VR-based interventions in the field of rehabilitation, with particular emphasis on their ability to assist patients in restoring motor functions [10]. An analysis of several literature reviews has identified the focus of VR rehabilitation research. Most of this investigation is dedicated to quantifying the effectiveness of VR as a supplementary or alternative treatment for physical therapy. This area of research is the most dominant form of VR research in the healthcare sector. Numerous systematic reviews and meta-analyses have been conducted to demonstrate the efficacy of VR treatment in specific rehabilitation subdomains, such as orthopedic rehabilitation [11], pediatric rehabilitation [12], hand rehabilitation [13], cognitive rehabilitation [14], spinal cord rehabilitation [15], and UE rehabilitation [16].
Exergaming is an emerging therapeutic approach that demonstrates significant synergy with virtual reality for rehabilitation [17,18,19]. A literature review and meta-analysis has revealed that the utilization of exergaming for therapeutic purposes typically necessitates the incorporation of external sensors, including Kinect electromyography, sensing jackets, goniometers, and haptic gloves, into the gaming system. These integrations serve various functions, such as improving the accuracy of mobility tracking and employing biosensors to monitor vital signs [20].
The focus of this research, instead of following the mainstream and focusing on the efficacy of VR as a form of treatment, is to investigate the user’s feelings of affection when engaging with the technology. Specifically, we aim to examine the human motivation that is induced by interactions with VR-integrated data glove technology. It has been confirmed in neuro-rehabilitation research that motivation is a critical factor in encouraging patients to participate in rehabilitation treatment. The way in which motivation steers physical mobility is demonstrated by the association between cognition and motor performance, as discussed in [21]. The scoping review in [22] has revealed that highly immersive VR significantly impacts motivation in exercise. For example, the authors of [23] combine the head-mounted device (HMD) used in VR with other physical effects such as the sound of wind resistance, which significantly enhances player motivation in cycling games. Meanwhile, studies have not found a significant relationship between low-immersive VR and user motivation [24,25].
Motivation can be classified into intrinsic motivation and extrinsic motivation. Intrinsic motivation is characterized by the pleasure or interest that is derived from participating in a certain activity, while extrinsic motivation arises when the objective of an activity has an external incentive that is distinct from the action itself [21]. Intrinsic motivation has garnered significant research interest due to its well-established role as a primary driver of enthusiasm [26,27]. When enthusiasm is properly triggered, it results in people engaging in activities without reinforcement being required [28].
Some prior research has focused on the motivation of users when they participate in upper-extremity (UE) rehabilitation using VR or data glove technologies independently, but not through the integration of both within a single system. VR has been shown to induce several intrinsic motivation results, including enjoyment, attraction, and effort, to higher levels in both older adult and young adult groups [29]. In addition, some studies have demonstrated positive outcomes relating to users’ intrinsic motivation when they experience VR for rehabilitation [30,31]. Some research has focused on the motivation of users in post-stroke patients when a VR-based intervention was applied to UE training. The authors of [32] indicated that stroke patients who underwent VR training had higher levels of engagement and motivation and also reported experiencing more pleasure compared to patients in the physical environment group.
For the investigation of motivation and data gloves, Friedman et al. (2014) evaluated MusicGlove, an economically active training apparatus that uses custom gloves developed by Flint Rehab, Irvine, CA, USA [33]; the results were compared to those of traditional and isometric hand therapy. MusicGlove demonstrated greater motivational efficacy compared to the other two therapies, as measured by the IMI [34]. Radde et al. (2018) assessed the feasibility of a soft robotic glove system that was designed to provide assistive support in daily activities. An IMI evaluation was administered to participants, which yielded a score of 6.3 out of 7 for therapeutic exercise [35]. Franck et al. (2019) utilized Saeboglove to develop a functional hand orthosis that was integrated with electrical stimulation. The study evaluated the effectiveness of the intervention, as well as the motivation of the patients. The findings revealed that the patients exhibited a significant degree of intrinsic motivation, with sub-scores between 4.6 and 6.3 out of 7.0 [36].
The anatomical regions covered by UE rehabilitation include all the upper extremities of the human body, including the hands and fingers. Despite the fact that the majority of current-generation virtual reality headsets have approximated optical hand tracking, which is less cumbersome, this approach has its limitations. For example, the hand tracking from VR, especially in the legacy VR model, is imprecise and is only suitable for detecting coarse hand activity, such as palm movement, rather than fine-scale movements, such as finger gestures. Furthermore, employing a controller may improve hand tracking; however, the compromise is that the hand gestures must be calibrated to correspond with the controller’s functionality, such as grab-and-click gestures. Consequently, to facilitate precise hand tracking at the finger gesture level for the natural movement in upper-extremity rehabilitation applications, data gloves or similar wearable technologies providing a Natural User Interface (NUI) would likely be required.
Research on rehabilitation data gloves has been sparse. The clinical efficacy aspects of data gloves were found to be less apparent. The effectiveness of this approach is diverse, ranging from being substantial [34] to being slightly effective [36] to not being effective [37], compared to conventional rehabilitation, as evidenced by various previous studies, whereby the clinical efficacy of data gloves was found to be slightly effective and not effective compared to conventional rehabilitation.
To the best of our knowledge, there is a scarcity of studies that analyze user motivation when VR and data gloves are merged. In addition, the current study solely utilizes this specific combination of devices in the experiment in order to investigate aspects of the VR game-based design. For example, Ballester [38] employed VR in conjunction with a data glove to study the impact of social interaction in VR games. The results highlighted that the multi-player mode outperformed the single-player mode in that it encouraged patients to reach wider elbow flexion/extension movements. In another study, it was found that when the VR and a data glove were integrated into the exergame, user motivation was potentially elevated, resulting in the enhanced playfulness of the home rehabilitation system [39].
This research aims to investigate the intrinsic motivation of participants in the context of experiencing VR and data gloves in UE assessment applications—a topic that has not previously been examined in any other study. The purpose of this study is to assess the overall impact of these integrated technologies on intrinsic motivation compared to conventional practices.

2. Methods

To assess user motivation during interactions with virtual reality and a data glove in an exergame, a specific practical solution was chosen as a case study. UE assessment for rehabilitation requires clinicians to assess the patient’s ability to perform specific hand gestures, such as grip and grasp, in conjunction with VR and experiential games that are recognized for mitigating boring activities. Standard guidelines for UE assessment, namely ARAT, are used to design the game content. A standard questionnaire for measuring intrinsic motivation—IMI—is utilized. The subsequent sections (Section 2.1, Section 2.2, Section 2.3, Section 2.4, Section 2.5 and Section 2.6) provide comprehensive data regarding device selection, game design and development, measurement techniques, and research methodology.

2.1. Devices

As concerns hardware devices, in this study, we intended to use all commercial devices in order to open up the possibility of the study being reproduced in the future, as well as to enhance the validity of comparing the results with other research. To improve the validity of hardware selection in this study, we conducted a separate preliminary study to examine and analyze the specifications of various devices that are suitable for rehabilitation use. Our research on VR selection can be seen in [40], while research on data glove selection can be found in [41]. The VR system for this project is Oculus Rift Customer Version 1, which was released in 2017. Although Oculus Touch is provided as the default controller of our Oculus Rift, its grab-and-click functionality does not align with our game objective of tracking hand gestures such as grasp, grip, and pinch according to ARAT guidelines. We have acquired the Sensoglove DK3 data glove to enhance the capabilities of standard VR for this game.

2.2. Action Research Arm Test (ARAT)

The ARAT [42] is one of the most common measurements of UE function; it works by evaluating the ability of a participant to complete four major functional tasks—“grasp”, “grip”, “pinch” and “gross motor functions” [43]. The ARAT necessitates that the participant interact with standard-sized objects to complete tasks. The evaluator then assesses the participant’s ability to perform each task by assigning them a score. Table 1 summarizes the tasks that must be completed for the ARAT.

2.3. Game Development

The development of our games started with the creation of disposable prototypes to test basic game mechanics and input devices. The games were implemented in an iterative process over a period of three months.
We used the Activity Theory-Based Model for Serious Games (ATMSG model) [44] to identify the important mechanics and functions of our VR game. The ATMSG model helps developers ensure that the mechanics of implementing serious games can meet the functional requirements of the games. The ATMSG model is implemented based on action-based theory, which explains the relationship between human actions, motives, and activities. Based on the action-based theory, the ATMSG model provides a standard notation (flowchart), as well as game and learning taxonomies to describe how the game actions respond to the non-entertainment purposes of serious games.
The Mechanics, Dynamics, and Aesthetics Framework (MDA) [45], i.e., the method that considers both the developer and the player aspects, is applied to improve the design of the games. Several formative internal game tests were conducted with a developer team to fine-tune the games’ pace and difficulty levels. For example, the think-aloud approach, in which testers were encouraged to think aloud while performing a given task [46], was applied. The summative evaluation was conducted after the first release. We finished the development phase by testing the game with external volunteers. We conducted this preliminary test to see if the setup and application of the games was practical.

Game Design for UE Assessment

The game is designed to support an important activity in UE rehabilitation—performance-based outcome measures (PBOMs)—which are used to measure the performance of the patient during treatment. PBOMs provide unbiased and reproducible assessments of limb function [47], which are typically used to inform patient progression and to document the efficacy of rehabilitation programs [48].
Despite the fact that there are numerous PBOMs available, this study is expressly designed to adhere to the ARAT approach (detailed in Section 2.2). In light of the game’s status as an ARAT alternative, the content and required interaction in game design are rigorously regulated to ensure that they align with the traditional ARAT. For instance, the size of an object in the game is comparable to that of an object in the ARAT. Additionally, players are obliged to employ the same hand gestures as specified in ARAT, such as hold and grasp, when acquiring a specific object. In addition, the objective of the game is to help rehabilitation clinicians determine whether the player can successfully interact with the ARAT item and at what level of dexterity the ARAT task can be performed.
A virtual reality game titled “Treasure Hunter” was produced. The game is a first-person perspective game that features a pirate who has survived a shipwreck. The objective of the game is to locate the sunken treasures. Each round, the game instructs the player to locate a certain treasure using hand gestures from the provided ARAT. We try to minimize the influence of the game design on VR and the data glove solely to an interaction element. If the game is designed to be very entertaining, the influence of the game design may outweigh the interaction effect in increasing IMI. The player’s view of the game interface is shown in Figure 1.
The game system also has a control panel that is displayed outside the player’s view. This section is used by the therapist, who selects the item to appear as a treasure and to monitor what ARAT activities have been completed. Figure 2 shows the control panel interface.

2.4. Intrinsic Motivation Inventory (IMI)

The Intrinsic Motivation Inventory (IMI) is a multidimensional measurement tool that is designed to assess the subjective experience of participants in relation to the laboratory experiment of the target activity [49]. Several other motivation evaluation methods exist, including the Apathy Evaluation Scale (AES) and the Center for Epidemiological Studies of Depression in Short Form—10 Items (CES-D10). The BREQ-3 (Behavioral Regulation in Exercise Questionnaire); SMSC (Sport and Movement-Specific Self-Concordance Scale); GDS-15 (Geriatric Depression Scale); and IMI represent the predominant methodologies for stroke rehabilitation, indicating great dependability in the results. Consequently, we have opted to utilize these instruments for this purpose [21]. The IMI questionnaire includes various motivation-related attributes. Motivational attributes can be selected and applied to a specific project. In this research, we focused on five subscales, which are interest/enjoyment, perceived competence, effort, perceived stress/tension, and value/usefulness. Following their interaction with the system, users are asked to score their feelings using a seven-point Likert scale. In most cases, a higher score indicates a stronger positive intrinsic motivation, but there are a few questions that work in the other direction, implying a more negative meaning. In the latter case, queries are denoted by the suffix “(R)”.
The following are example answers to a question that is used to determine the interest and enjoyment of IMI:
  • I enjoyed doing this activity very much.
  • This activity was fun to do.
  • I thought this was a boring activity (R).
  • This activity did not hold my attention at all (R).
  • I would describe this activity as very interesting.
  • I thought this activity was quite enjoyable.
  • While I was doing this activity, I was thinking about how much I enjoyed it.

2.5. Research Methodology

The research methodology is shown in Figure 3. This study aims to compare the motivation of users participating in the ARAT in two different environments. Participants were instructed to take the ARAT according to conventional protocols using standardized materials and procedures. In a different context, the participants were instructed to execute the ARAT inside a virtual reality environment via a game designed expressly for this experiment. The game was created to encourage players to execute certain movement patterns derived from the ARAT. Players used the Oculus Rift and the data glove to manipulate the game. The intrinsic motivation of the individuals involved in two settings of the ARAT was assessed to see if there were significant results between the two environments.

2.6. Evaluation and Data Collection

After the game was developed, evaluation and data collection were carried out at three prominent universities in northern Thailand—Chiang Mai University, Chiang Rai Rajabhabha University, and Mae Fah Luang University. Demonstration booths were established in public areas such as the canteen and student lounge. We recruited participants who expressed interest in the topic and were eager to participate in the investigation. Data collection involved a preliminary screening process to ensure participant eligibility and ethical compliance. All potential participants were required to complete an informed consent form, confirming their understanding of the purpose, procedures, and rights of the study as participants. Following this, they answered a series of yes/no health screening questions. If any response indicated a potential health concern (that is, a ’no’ to any required criteria), the individual was deemed ineligible and was excluded from further participation in the study in order to maintain the safety and integrity of the research. Each participant was instructed to participate in the experiment for two consecutive rounds. In the first round, participants were introduced to the ARAT before being given instructions to complete it. When they were finished, the participants were asked to complete an IMI test relating to the activity. In the second round of the experiment, the subject was invited to play the treasure hunter game, after which another IMI test was administered to gather data from the experience. The evaluation sequence was maintained by requiring participants to first undertake the conventional ARAT, followed by the VR-based test. It is also necessary to note that all participants were provided with a short amount of rest prior to the commencement of the second round of the experiment. In addition, they were encouraged to double-check their readiness to continue in order to alleviate the fatigue effect induced by the first round of the experiment.
To determine the IMI score, the mean values of each question group were initially calculated for each subject, followed by an aggregate computation for all participants. For questions that imply a negative meaning, the given scores were inverted, e.g., from 3 to 5 and vice versa, prior to aggregation with other positive scores.

3. Results

3.1. Demographics

This study successfully recruited a total of 62 individuals from three institutions. The gender distribution of the participants is about equal. The mean age was 25 years and the standard deviation (SD) was 10. Most of the study’s participants were students, despite drawing considerable interest from staff, and the majority of the participants had prior experience with VR technology. Table 2 provides demographic information on the participants.

3.2. Intrinsic Motivation

Figure 4 illustrates a comparison of the average IMI scores obtained from the conventional ARAT and the treasure hunter game, which is facilitated by the VR, exergame, and data glove technologies. In this study, the IMI test includes five intrinsic motivational characteristics. The results have shown that, in general, the treasure hunter game outperforms the regular ARAT in most positive aspects. For example, participants feel more interested in interacting with the ARAT (6.01 vs. 5.07), feel more competent at carrying out the ARAT (5.22 vs. 5.07), and are encouraged to put in more effort to connect with the ARAT and perceive its value (5.41 vs. 4.90). However, the score indicates that the participants feel slightly more pressure than when they engage with the traditional ARAT tool set.
To further examine the effects of the virtual reality (VR)-based solution compared to the traditional ARAT, a paired T-test is conducted to determine any significant influence. Significant differences in intrinsic motivation components were discovered between the standard rehabilitation system and the VR glove rehabilitation system in areas of interest, perceived competence, effort, and value, with a confidence level of 95%. The only motivating characteristic that shows no statistically significant variation is pressure. The quantitative results for this section of the study are given in Table 3.

4. Discussion

The main goal of this study is to investigate how users’ intrinsic motivation is affected by virtual reality and data gloves when these technologies are used as part of an intervention for upper-extremity rehabilitation. A VR exergame was developed to support one key activity of the clinical process—the performance-based outcome measures—and the ARAT measurement protocol was used in this study to design the game.
The game’s basic requirements are to determine whether the player can successfully interact with the ARAT object and what level of dexterity is required to complete the ARAT task. In VR UE rehabilitation, the system must have the ability to recognize and track hand and finger gestures. Although high-end and recently released VR systems provide superior finger-tracking resolution, they are accompanied by a significant cost, while legacy systems remain predominant in practical settings. Therefore, in this research, we used an external data glove to complement the VR system.
The game’s implementation is designed to function in a virtual environment utilizing VR technology, based on the premise that it will captivate users’ interest and encourage engagement with the test in a more enjoyable manner. In this system, the data glove serves as a supplementary device that is designed to address the limitations of standard virtual reality, which do not accurately capture hand tracking.
Subsequently, the ARAT developed for VR games was compared with the standard ARAT using the IMI questionnaire. According to the experimental findings, the VR approach, which is facilitated by VR and the data glove, outperforms the conventional ARAT in all motivational aspects.
The analysis of the motivation of the participants in this study has benefits in both academic and practical contexts. From an academic standpoint, this study provides empirical proof of the evaluation of the motivating experiences of the participants while engaging with virtual reality and data gloves at the UEA, which has never been documented. Intrinsic motivation is assessed using a standard instrument known as IMI; therefore, the research is reproducible and the results may be compared with those of other experimental situations in the future. The selection of young and healthy participants for this research is justified by the fact that it is the first study to evaluate user motivation while experiencing VR and a data glove simultaneously. The research team anticipated achieving a gold-standard performance in technology exposures in this setting. Similar studies that include older and younger patient groups will be conducted in the future to compare the findings.
Next, as stated in the Introduction, most studies on user motivation have focused on the effects of VR or data gloves; however, this study primarily focused on the effects of combining VR and data gloves. According to the literature, there was some evidence indicating the efficacy of VR in improving user motivation to undertake rehabilitative activities more efficiently [30,31]. Some studies have shown that the data glove is the motivational technology [34,35,36]. The integrated solution in this study provides proof that there are no adverse effects between these two gaming technologies in UEA applications.
Furthermore, while this study used a data glove as an extension of standard VR in order to overcome the limitation of imprecise hand tracking in a specific legacy VR model released in 2017, some models from commercial VR brands demonstrated higher-resolution hand tracking and may be able to replace the data glove tracking feature in some applications. For example, data gloves should remain essential for certain applications where hand tracking accuracy is critical and sensitive, such as a virtual reality surgical solution [50,51,52]. The high accuracy of data gloves is due to the use of dedicated sensors that are embedded in the glove at user-specific palm and finger positions to determine current hand positioning and gestures locally rather than projecting them from the VR headset’s position. Another important feature of high-end data gloves that is obviously superior to conventional VR is their ability to generate haptic feedback. Haptics is the science of feeling and manipulating through touch, which enables users to feel a virtual reality (VR) environment or distant objects [53]. In addition, in UE rehabilitation, haptic feedback is a well-established medication that is typically used to provide sensory information to patients with sensorimotor impairments [54]. Therefore, understanding the user experience and the impact of data gloves when integrating them with the VR system on user motivation should be a significant area of research for VR solutions.
Focusing on the main purpose of the study, which was to investigate the intrinsic motivation of the user in two UE evaluation settings, it was found that all positive IMI scores measured by the treasure hunter game—interest/enjoyment, perceived competence, perceived stress/tension, and value/use—are significantly better than those scores measured from the conventional ARAT practice. This finding raises some observations for each IMI element. The elevated “interest” score may serve as a crucial catalyst for eliciting other favorable criteria. The conventional method can be tedious and lacks attention-capturing mechanisms; however, engaging with virtual reality and data gloves is much more entertaining. The experience of “interest” can elicit more favorable perceptions. Secondly, the high score relating to the perceived competence of this IMI experiment is consistent with Ryan’s study [55]. The authors of [55] found that the perception of competence is related to the sense of presence and the intuitiveness of the controls of the game system. A critical component of VR systems is their presence, which determines the degree of immersion. In this investigation, the VR is classified as a high-immersion system by definition, as it is a head-mounted device [56]. Meanwhile, the control of this game is enhanced by the intuitiveness of the data glove, which allows for the natural execution of ARAT gestures such as pinch, grab, and grip. Next, the effort score should be considered, which is a significant adverse signal in IMI. Although the standard ARAT strategy was shown to be marginally superior, requiring less effort, than the score obtained by utilizing the treasure hunter game, the difference was not statistically significant. This means that learning how to use VR, data gloves, and the implemented exergame requires around the same amount of effort as learning how to use the regular ARAT tool set. As a result, this study suggests that the treasure hunter test is more effective than the classic ARAT. This shows that this approach has significant potential for therapeutic use. Regarding the pressure score, this study indicated that the treasure hunter game imposes a slightly stronger effect than the conventional method; this is possibly associated with the extra effort required for learning how to use the system. Finally, the treasure hunter game increases participants’ perception of the value of physical therapeutic activity compared to conventional practice. This may be due to, in a game environment, a goal such as the quest for a diamond being explicit, objective, and relevant to the user. It is also partially associated with the previous finding of Bird et al. (2015), who discovered that the benefits of exergames are evident in postplay [57].
In addition, the IMI analysis indicated that the “pressure” parameter, which is a singular parameter, did not exhibit any statistically significant differences between the traditional approach and the VR game-based approach. This finding also implies that the VR game-based approach has a favorable effect, as the additional effort that is necessary to learn how to operate the system did not have a significant impact.
Given that the study experiment was performed in a simulated environment to assess users’ intrinsic motivation, we have recognized that some procedures of the experiment may affect the validity of the results. For example, when participants were asked to interact with the system in two consecutive scenarios, there may have been residual effects from the first experiment influencing the second. The tiredness effect was anticipated and managed by permitting the participants to rest until they felt ready; nonetheless, the monotony of recurrent tasks may inevitably influence this experimental setting. However, when the results indicate that VR combined with the data glove exceeds the traditional version, it further reinforces the conclusion that the latter approach is superior to the former.
Although this study offers substantial insights into the effects of VR and data gloves on intrinsic motivation in upper-extremity assessment, it is crucial to recognize certain limitations that may affect the generalization and interpretation of the results. For example, observation was conducted in the early stages of the study, during which all subjects were young and healthy; therefore, it may be premature to assert that VR and data gloves have a positive impact on patient motivation during rehabilitation. In future plans to validate the results of this initial investigation and determine whether the results stay consistent when motor impairment conditions are included, a similar experiment must be conducted within a patient population. The alteration of the game and system is mandated upon implementation with clinical patient groups.
Furthermore, the hardware devices utilized in this study were limited to a single commercial brand for the VR headset and another specific brand and model for the data glove. In order to enhance the generalization of the findings, it is recommended that a diverse array of VR and data glove models and branding be implemented. Another factor that may influence the result is that the evaluation session was organized in a public space instead of in a private and enclosed environment.
In addition, this study recognizes the initial increase in intrinsic motivation that is observed with the implementation of VR interventions; however, it is crucial to consider the potential for this motivation to diminish over time due to novelty effects. Although VR technology initially captures interest and participation, there is a possibility that repeated exposure may lead to decreased enthusiasm among participants. To address this concern, it is important to explore strategies that maintain participant engagement beyond the initial novelty phase. This could involve incorporating varied or progressively challenging content within the VR experience. Furthermore, future research could benefit from longitudinal measures to evaluate changes in motivation over time. Understanding whether motivation wanes with repeated exposure is essential for assessing the long-term effectiveness of VR-based rehabilitation programs. This approach would provide valuable insights into sustaining motivation and optimizing rehabilitation outcomes over extended periods.

Author Contributions

Conceptualization, N.C., H.K. and S.G.; methodology, N.C.; software, S.G.; validation, H.K. and N.C.; formal analysis, H.K.; investigation, H.K.; resources, S.G.; data curation, H.K.; writing—original draft preparation, N.C., H.K. and S.G.; writing—review and editing, N.C.; visualization, N.C. and H.K.; supervision, N.C.; project administration, S.G. and N.C.; funding acquisition, N.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially support by Chiang Mai University.

Institutional Review Board Statement

The ethical approval is waived as this study is a nonintervention study, and this research project aims to investigate individuals’ attitudes toward a VR-based rehabilitation system. The study is organized in a casual, open public setting, inviting individuals who are interested in and willing to try the technology and participate in the survey. Participation is entirely voluntary, and all participants have the right to withdraw at any time without any consequences.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

No new data were created or analyzed in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Berg, L.P.; Vance, J.M. Industry use of virtual reality in product design and manufacturing: A survey. Virtual Real. 2017, 21, 1–17. [Google Scholar] [CrossRef]
  2. Biocca, F.; Delaney, B. Immersive virtual reality technology. Commun. Age Virtual Real. 1995, 15, 10–5555. [Google Scholar]
  3. Ryan, M.L. Narrative as Virtual Reality Narrative as Virtual Reality: Immersion and Interactivity in Literature and Electronic Media; Johns Hopkins University Press: Baltimore, MD, USA, 2000; pp. 357–359. ISBN 0801864879. [Google Scholar]
  4. Rose, T.; Nam, C.S.; Chen, K.B. Immersion of virtual reality for rehabilitation-Review. Appl. Ergon. 2018, 69, 153–161. [Google Scholar] [CrossRef] [PubMed]
  5. Gregg, L.; Tarrier, N. Virtual reality in mental health: A review of the literature. Soc. Psychiatry Psychiatr. Epidemiol. 2007, 42, 343–354. [Google Scholar] [CrossRef]
  6. Javaid, M.; Khan, I.H. Virtual reality (VR) applications in cardiology: A review. J. Ind. Integr. Manag. 2022, 7, 183–202. [Google Scholar] [CrossRef]
  7. Schiza, E.; Matsangidou, M.; Neokleous, K.; Pattichis, C.S. Virtual reality applications for neurological disease: A review. Front. Robot. 2019, 6, 100. [Google Scholar] [CrossRef]
  8. Savickaite, S.; McDonnell, N.; Simmons, D. Defining virtual reality (VR). Scoping literature review on VR applications in autism research. PsyArXiv 2022. [Google Scholar] [CrossRef]
  9. World Health Organization Rehabilitation. 2024. Available online: https://www.who.int/news-room/fact-sheets/detail/rehabilitation (accessed on 18 October 2024).
  10. Mazurek, J.; Kiper, P.; Cieślik, B.; Rutkowski, S.; Mehlich, K.; Turolla, A.; Szczepańska-Gieracha, J. Virtual reality in medicine: A brief overview and future research directions. Hum. Mov. 2019, 20, 16–22. [Google Scholar] [CrossRef]
  11. Gumaa, M.; Rehan Youssef, A. Is virtual reality effective in orthopedic rehabilitation? A systematic review and meta-analysis. Phys. Ther. 2019, 99, 1304–1325. [Google Scholar] [CrossRef]
  12. Parsons, T.D.; Rizzo, A.A.; Rogers, S.; York, P. Virtual reality in paediatric rehabilitation: A review. Dev. Neurorehabilit. 2009, 12, 224–238. [Google Scholar] [CrossRef]
  13. Pereira, M.F.; Prahm, C.; Kolbenschlag, J.; Oliveira, E.; Rodrigues, N.F. Application of AR and VR in hand rehabilitation: A systematic review. J. Biomed. Inform. 2020, 111, 103584. [Google Scholar] [CrossRef] [PubMed]
  14. Larson, E.B.; Feigon, M.; Gagliardo, P.; Dvorkin, A.Y. Virtual reality and cognitive rehabilitation: A review of current outcome research. NeuroRehabilitation 2014, 34, 759–772. [Google Scholar] [CrossRef] [PubMed]
  15. De Araújo, A.V.L.; Neiva, J.F.d.O.; Monteiro, C.B.d.M.; Magalhães, F.H. Efficacy of virtual reality rehabilitation after spinal cord injury: A systematic review. BioMed Res. Int. 2019, 2019, 7106951. [Google Scholar] [CrossRef]
  16. Henderson, A.; Korner-Bitensky, N.; Levin, M. Virtual reality in stroke rehabilitation: A systematic review of its effectiveness for upper limb motor recovery. Top. Stroke Rehabil. 2007, 14, 52–61. [Google Scholar] [CrossRef]
  17. Bond, S.; Laddu, D.R.; Ozemek, C.; Lavie, C.J.; Arena, R. Exergaming and virtual reality for health: Implications for cardiac rehabilitation. Curr. Probl. Cardiol. 2021, 46, 100472. [Google Scholar] [CrossRef]
  18. Chen, P.J.; Hsu, H.F.; Chen, K.M.; Belcastro, F. VR exergame interventions among older adults living in long-term care facilities: A systematic review with Meta-analysis. Ann. Phys. Rehabil. Med. 2023, 66, 101702. [Google Scholar] [CrossRef]
  19. Hadjipanayi, C.; Banakou, D.; Michael-Grigoriou, D. Virtual reality exergames for enhancing engagement in stroke rehabilitation: A narrative review. Heliyon 2024, 10, e37581. [Google Scholar] [CrossRef]
  20. Koutsiana, E.; Ladakis, I.; Fotopoulos, D.; Chytas, A.; Kilintzis, V.; Chouvarda, I. Serious gaming technology in upper extremity rehabilitation: Scoping review. JMIR Serious Games 2020, 8, e19071. [Google Scholar] [CrossRef]
  21. Verrienti, G.; Raccagni, C.; Lombardozzi, G.; De Bartolo, D.; Iosa, M. Motivation as a measurable outcome in stroke rehabilitation: A systematic review of the literature. Int. J. Environ. Res. Public Health 2023, 20, 4187. [Google Scholar] [CrossRef]
  22. Mouatt, B.; Smith, A.E.; Mellow, M.L.; Parfitt, G.; Smith, R.T.; Stanton, T.R. The use of virtual reality to influence motivation, affect, enjoyment, and engagement during exercise: A scoping review. Front. Virtual Real. 2020, 1, 564664. [Google Scholar] [CrossRef]
  23. Shaw, L.A.; Wuensche, B.C.; Lutteroth, C.; Buckley, J.; Corballis, P. Evaluating sensory feedback for immersion in exergames. In Proceedings of the Australasian Computer Science Week Multiconference, Geelong, Australia, 31 January–3 February 2017; pp. 1–6. [Google Scholar]
  24. García-Vergara, S.; Li, H.; Howard, A.M. Increasing Super Pop VRTM VRTM Users’ Intrinsic Motivation by Improving the Game’s Aesthetics. In Proceedings of the Universal Access in Human-Computer Interaction. Access to Learning, Health and Well-Being: 9th International Conference, UAHCI 2015, Held as Part of HCI International 2015, Los Angeles, CA, USA, 2–7 August 2015; Proceedings, Part III 9; Springer: Berlin/Heidelberg, Germany, 2015; pp. 432–441. [Google Scholar]
  25. Gillman, A.S.; Bryan, A.D. Effects of performance versus game-based mobile applications on response to exercise. Ann. Behav. Med. 2016, 50, 157–162. [Google Scholar] [CrossRef] [PubMed]
  26. Ryan, R.M. Control and information in the intrapersonal sphere: An extension of cognitive evaluation theory. J. Personal. Soc. Psychol. 1982, 43, 450. [Google Scholar] [CrossRef]
  27. Mandryk, R.L.; Inkpen, K.M.; Calvert, T.W. Using psychophysiological techniques to measure user experience with entertainment technologies. Behav. Inf. Technol. 2006, 25, 141–158. [Google Scholar] [CrossRef]
  28. Deci, E.L.; Koestner, R.; Ryan, R.M. A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychol. Bull. 1999, 125, 627. [Google Scholar] [CrossRef]
  29. Dong, Y.; Liu, X.; Tang, M.; Huo, H.; Chen, D.; Du, X.; Wang, J.; Tang, Z.; Qiao, X.; Guo, J.; et al. Age-related differences in upper limb motor performance and intrinsic motivation during a virtual reality task. BMC Geriatr. 2023, 23, 251. [Google Scholar] [CrossRef]
  30. Epure, P.; Holte, M.B. Analysis of motivation in virtual reality stroke rehabilitation. In Proceedings of the Interactivity, Game Creation, Design, Learning, and Innovation: 6th International Conference, ArtsIT 2017, and Second International Conference, DLI 2017, Heraklion, Greece, 30–31 October 2017; Proceedings 6; Springer: Berlin/Heidelberg, Germany, 2018; pp. 282–293. [Google Scholar]
  31. Lee, S.H.; Jung, H.Y.; Yun, S.J.; Oh, B.M.; Seo, H.G. Upper extremity rehabilitation using fully immersive virtual reality games with a head mount display: A feasibility study. PM&R 2020, 12, 257–262. [Google Scholar]
  32. Subramanian, S.; Knaut, L.A.; Beaudoin, C.; Levin, M.F. Enhanced feedback during training in virtual versus real world environments. In Proceedings of the 2007 Virtual Rehabilitation, Venice, Italy, 27–29 September 2007; pp. 8–13. [Google Scholar]
  33. Sheng, B.; Zhao, J.; Zhang, Y.; Xie, S.; Tao, J. Commercial device-based hand rehabilitation systems for stroke patients: State of the art and future prospects. Heliyon 2023, 9, e13588. [Google Scholar] [CrossRef]
  34. Friedman, N.; Chan, V.; Reinkensmeyer, A.N.; Beroukhim, A.; Zambrano, G.J.; Bachman, M.; Reinkensmeyer, D.J. Retraining and assessing hand movement after stroke using the MusicGlove: Comparison with conventional hand therapy and isometric grip training. J. Neuroeng. Rehabil. 2014, 11, 1–14. [Google Scholar] [CrossRef]
  35. Radder, B.; Prange-Lasonder, G.; Kottink, A.; Melendez-Calderon, A.; Buurke, J.; Rietman, H.J. Feasibility of a wearable soft-robotic glove to support impaired hand function in stroke patients. J. Rehabil. Med. 2018, 50, 598–606. [Google Scholar] [CrossRef]
  36. Franck, J.A.; Smeets, R.J.E.M.; Seelen, H.A.M. Evaluation of a functional hand orthosis combined with electrical stimulation adjunct to arm-hand rehabilitation in subacute stroke patients with a severely to moderately affected hand function. Disabil. Rehabil. 2019, 41, 1160–1168. [Google Scholar] [CrossRef]
  37. Radder, B.; Prange-Lasonder, G.B.; Kottink, A.I.; Gaasbeek, L.; Holmberg, J.; Meyer, T.; Melendez-Calderon, A.; Ingvast, J.; Buurke, J.H.; Rietman, J.S. A wearable soft-robotic glove enables hand support in ADL and rehabilitation: A feasibility study on the assistive functionality. J. Rehabil. Assist. Technol. Eng. 2016, 3, 2055668316670553. [Google Scholar] [CrossRef] [PubMed]
  38. Ballester, B.R.; i Badia, S.B.; Verschure, P.F. Including social interaction in stroke VR-based motor rehabilitation enhances performance: A pilot study. Presence 2012, 21, 490–501. [Google Scholar] [CrossRef]
  39. Wang, Q.; Kang, B.; Kristensson, P.O. Supporting playful rehabilitation in the home using virtual reality headsets and force feedback gloves. In Proceedings of the 2022 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Christchurch, New Zealand, 12–16 March 2022; pp. 504–513. [Google Scholar]
  40. Utthayotha, S.; Choosri, N. Survey of serious game controllers for stroke rehabilitation. In Proceedings of the 2020—5th International Conference on Information Technology (InCIT), ChonBuri, Thailand, 21–22 October 2020; pp. 71–75. [Google Scholar]
  41. He, K.; Choosri, N. Commercial data glove selection for vr-based hand rehabilitation gaming project. In Proceedings of the 2023 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON), Phuket, Thailand, 22–25 March 2023; pp. 177–182. [Google Scholar]
  42. McDonnell, M. Action research arm test. Aust. J. Physiother. 2008, 54, 220. [Google Scholar] [CrossRef]
  43. Lyle, R.C. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int. J. Rehabil. Res. 1981, 4, 483–492. [Google Scholar] [CrossRef]
  44. Carvalho, M.B.; Bellotti, F.; Berta, R.; De Gloria, A.; Sedano, C.I.; Hauge, J.B.; Hu, J.; Rauterberg, M. An activity theory-based model for serious games analysis and conceptual design. Comput. Educ. 2015, 87, 166–181. [Google Scholar] [CrossRef]
  45. Hunicke, R.; LeBlanc, M.; Zubek, R. MDA: A formal approach to game design and game research. In Proceedings of the AAAI Workshop on Challenges in Game AI; IAAA: San Jose, CA, USA, 2004; Volume 4, p. 1722. [Google Scholar]
  46. Eccles, D.W.; Arsal, G. The think aloud method: What is it and how do I use it? Qual. Res. Sport. Exerc. Health 2017, 9, 514–531. [Google Scholar] [CrossRef]
  47. Wang, S.; Hsu, C.J.; Trent, L.; Ryan, T.; Kearns, N.T.; Civillico, E.F.; Kontson, K.L. Evaluation of performance-based outcome measures for the upper limb: A comprehensive narrative review. PM&R 2018, 10, 951–962. [Google Scholar]
  48. Althobaiti, S.; Rushton, A.; Aldahas, A.; Falla, D.; Heneghan, N.R. Practicable performance-based outcome measures of trunk muscle strength and their measurement properties: A systematic review and narrative synthesis. PLoS ONE 2022, 17, e0270101. [Google Scholar] [CrossRef]
  49. Plant, R.W.; Ryan, R.M. Intrinsic motivation and the effects of self-consciousness, self-awareness, and ego-involvement: An investigation of internally controlling styles. J. Personal. 1985, 53, 435–449. [Google Scholar] [CrossRef]
  50. Saggio, G.; Lazzaro, A.; Sbernini, L.; Carrano, F.M.; Passi, D.; Corona, A.; Panetta, V.; Gaspari, A.L.; Di Lorenzo, N. Objective surgical skill assessment: An initial experience by means of a sensory glove paving the way to open surgery simulation? J. Surg. Educ. 2015, 72, 910–917. [Google Scholar] [CrossRef]
  51. Sbernini, L.; Quitadamo, L.R.; Riillo, F.; Di Lorenzo, N.; Gaspari, A.L.; Saggio, G. Sensory-glove-based open surgery skill evaluation. IEEE Trans. Hum.-Mach. Syst. 2018, 48, 213–218. [Google Scholar] [CrossRef]
  52. Chheang, V.; Apilla, V.; Saalfeld, P.; Boedecker, C.; Huber, T.; Huettl, F.; Lang, H.; Preim, B.; Hansen, C. Collaborative vr for liver surgery planning using wearable data gloves: An interactive demonstration. In Proceedings of the 2021 IEEE Conference on Virtual Reality and 3d User Interfaces Abstracts and Workshops (VRW), Lisbon, Portugal, 27 March–3 April 2021; p. 768. [Google Scholar]
  53. Shazhaev, I.; Mihaylov, D.; Shafeeg, A. A review of haptic technology applications in healthcare. Open J. Appl. Sci. 2023, 13, 163–174. [Google Scholar] [CrossRef]
  54. Gomez-Risquet, M.; Cáceres-Matos, R.; Magni, E.; Luque-Moreno, C. Effects of Haptic Feedback Interventions in Post-Stroke Gait and Balance Disorders: A Systematic Review and Meta-Analysis. J. Pers. Med. 2024, 14, 974. [Google Scholar] [CrossRef] [PubMed]
  55. Ryan, R.M.; Rigby, C.S.; Przybylski, A. The motivational pull of video games: A self-determination theory approach. Motiv. Emot. 2006, 30, 344–360. [Google Scholar] [CrossRef]
  56. Kaplan-Rakowski, R.; Gruber, A. Low-immersion versus high-immersion virtual reality: Definitions, classification, and examples with a foreign language focus. In Proceedings of the Innovation in Language Learning International Conference 2019, Florence, Italy, 14–15 November 2019. [Google Scholar]
  57. Bird, M.L.; Clark, B.; Millar, J.; Whetton, S.; Smith, S. Exposure to “exergames” increases older adults’ perception of the usefulness of technology for improving health and physical activity: A pilot study. JMIR Serious Games 2015, 3, e4275. [Google Scholar] [CrossRef]
Mti 09 00057 g001
Figure 1. Game interface: player’s view.
Figure 1. Game interface: player’s view.
Mti 09 00057 g001
Mti 09 00057 g002
Figure 2. Game interface: therapist’s view.
Figure 2. Game interface: therapist’s view.
Mti 09 00057 g002
Mti 09 00057 g003
Figure 3. Research methodology.
Figure 3. Research methodology.
Mti 09 00057 g003
Mti 09 00057 g004
Figure 4. The average IMI scores.
Figure 4. The average IMI scores.
Mti 09 00057 g004
Table 1. The action research arm test (ARAT) [42].
Table 1. The action research arm test (ARAT) [42].
ActivityObjects
Grasp1. Block, wood, 10 cm cube
2. Block, wood, 2.5 cm cube
3. Block, wood, 5 cm cube
4. Block, wood, 7.5 cm cube
5. Ball (cricket), 7.5 cm diameter
6. Stone, 10 × 2.5 × 1 cm
Grip1. Pour water from glass to glass
2. Tube, 2.25 cm
3. Tube, 1 × 16 cm
4. Washer (3.5 cm diameter) over bolt
Pinch1. Ball bearing, 6 mm, 3rd finger and thumb
2. Marble, 1.5 cm, index finger and thumb
3. Ball bearing 2nd finger and thumb
4. Ball bearing 1st finger and thumb
5. Marble, 3rd finger and thumb
6. Marble, 2nd finger and thumb
Gross Movement1. Place hand behind head
2. Place hand on top of head
3. Hand to mouth
Table 2. Participant demographics.
Table 2. Participant demographics.
GenderAgeOccupationExperiences in VR
FemaleMaleAge RangesAverage Age (Year)StudentsStaffYesNo
323018–402544182240
Table 3. The paired T-test of IMI scores between the standard rehabilitation system and the VR glove rehabilitation system.
Table 3. The paired T-test of IMI scores between the standard rehabilitation system and the VR glove rehabilitation system.
Intrinsic Motivation Attributep-Value
Interest0.000
Perceived competence0.006
Effort0.000
Pressure0.519
Value0.000
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kunze, H.; Choosri, N.; Grudpan, S. The Impacts of Incorporating Virtual Reality and Data Gloves in Exergames on Intrinsic Motivation in Upper-Extremity Assessments: A Study in a Young and Healthy Group. Multimodal Technol. Interact. 2025, 9, 57. https://doi.org/10.3390/mti9060057

AMA Style

Kunze H, Choosri N, Grudpan S. The Impacts of Incorporating Virtual Reality and Data Gloves in Exergames on Intrinsic Motivation in Upper-Extremity Assessments: A Study in a Young and Healthy Group. Multimodal Technologies and Interaction. 2025; 9(6):57. https://doi.org/10.3390/mti9060057

Chicago/Turabian Style

Kunze, He, Noppon Choosri, and Supara Grudpan. 2025. "The Impacts of Incorporating Virtual Reality and Data Gloves in Exergames on Intrinsic Motivation in Upper-Extremity Assessments: A Study in a Young and Healthy Group" Multimodal Technologies and Interaction 9, no. 6: 57. https://doi.org/10.3390/mti9060057

APA Style

Kunze, H., Choosri, N., & Grudpan, S. (2025). The Impacts of Incorporating Virtual Reality and Data Gloves in Exergames on Intrinsic Motivation in Upper-Extremity Assessments: A Study in a Young and Healthy Group. Multimodal Technologies and Interaction, 9(6), 57. https://doi.org/10.3390/mti9060057

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop