Assessing Physical Activity Levels While Playing Virtual Reality

Exergames: A Pilot Study

Mário Teixeira

, Hildegardo Noronha

1,2

, Pedro Campos

1,2,3

and Cíntia França

2,4

Department of Informatics Engineering and Interactive Media Design, University of Madeira, Funchal, Portugal

LARSyS, Interactive Technologies Institute, Funchal, Portugal

WoWSystems Informática Lda, Funchal, Portugal

Department of Physical Education and Sports, University of Madeira, Funchal, Portugal

Keywords: Heart Rate, Intensity, Exercise, Adults.

Abstract: Due to the exponential growth in technology, exergames emerged as innovative tools that might be used to

promote PA enjoyably. This study describes the development of a virtual reality (VR) exergame and the

preliminary implementation results. The system was developed through the Unity3D platform and the HCT

Vive, consisting of two mini games: a dance game and a snow skiing game. Five healthy adults (25.2 ± 3.9

years) performed one VR exergame session and were monitored for PA intensity and heart rate (HR). After

the session, participants were asked to report their perceived exertion and to fill in a system usability

questionnaire. During the session, participants spent more time in sedentary activity (≈ 37.5%), followed by

light activity (≈ 35.1%), and moderate-to-vigorous activity (≈ 27.4%). An average of 27.2 steps/min and HR

of 123.5 bpm were registered while playing. Perceived exertion scores were higher in the dance mini game

than in the snow skiing mini game. Regarding usability, participants considered the system easy to use and

would like to use it more often. This study summarizes preliminary and promising results on the ability of VR

exergames to promote light and moderate PA.

1 INTRODUCTION

Worldwide, physical inactivity and increased

sedentary behavior have become public concerns

(WHO, 2020). According to the literature, physical

activity (PA) is any bodily movement produced by

skeletal muscles that promotes energy expenditure

(Caspersen et al., 1985). Although the well-

established benefits of PA on physical fitness

components (i.e., body composition, muscular

strength, balance, flexibility, etc.) (Cox et al., 2020;

Wickramarachchi et al., 2023), and overall well-being

(Trajković et al., 2023), an alarming rise in sedentary

lifestyles have been observed in the past years.

The exponential growth in technology usage has

been associated with increased screen time and

decreased PA levels (Lee et al., 2012). However,

innovative approaches based on technology have been

emerging to foster PA, particularly through exergames

(videogames that demand PA to be played) (Boulos &

Yang, 2013). In previous literature, the positive

contribution of exergames interventions to prevent

childhood obesity (Gao & Chen, 2014; Pope et al.,

2016), and to enhance strength and balance among

older adults (Alhagbani & Williams, 2021) have been

reported. Among the solutions used, commercial

devices, such as Nintendo Wii, PlayStation, and Xbox

360, have been widely implemented in exergames

interventions (Agmon et al., 2011; Trost et al., 2014).

Indeed, these solutions are presented as affordable and

can be used in home-approach.

The technological landscape has evolved in the

last few years, allowing new possibilities for human

interaction and experience. In deploying new

exergames, virtual reality (VR) arises as a more

interactive platform that can increase adherence and

the probability of achieving general health benefits.

VR is considered appealing since it takes users to

different worlds and gives them a high level of

presence and interaction. Based on previous literature

on the topic, positive outcomes have been described

on the cognitive and physical performance of

different populations through VR exergames (Costa

et al., 2019), although emphasis has been given to

younger and older populations. Therefore, this paper

aims to describe the development of an exergame

Teixeira, M., Noronha, H., Campos, P. and França, C.

Assessing Physical Activity Levels While Playing Virtual Reality Exergames: A Pilot Study.

DOI: 10.5220/0013061300003828

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

In Proceedings of the 12th International Conference on Sport Sciences Research and Technology Support (icSPORTS 2024), pages 95-101

ISBN: 978-989-758-719-1; ISSN: 2184-3201

design to promote PA among healthy adults and the

results of a first-stage testing phase (pilot study)

regarding PA intensity level and system usability.

2 METHODS

2.1 Game Development

For the development of the VR session, the authors’

developed two minigames, each centered around dance

and snow skiing themes. The review of previous

studies supports the theme selection focused on

exergames, which have commonly used dance

(Comeras-Chueca et al., 2020; Maddison et al., 2011)

and sports games (Agmon et al., 2011; Meldrum et al.,

2012) to implement PA programs among different

populations. Additionally, previous highlights of its

efficacy supported the choice to include a snow skiing

game, especially among individuals who prefer

gaming over traditional exercise (Ko et al., 2020). Both

mini games were designed to simulate real-world

physical activities, providing a fun and immersive way

to engage, particularly the aerobic capacity.

In the dance mini game (Figure 1), users engage

in a dynamic and rhythmic environment where their

body movements synchronize with virtual dance

moves. Players engaged with four music tracks,

chosen based on popularity and high danceability. In

this game, players score points by hitting color-coded

virtual obstacles that appear at foot level, timed to the

beat of the music. Green is used for the left foot and

blue for the right foot. The player must hit the

corresponding obstacle with the correct foot to earn

points. The scoring system is designed with three tiers

of accuracy: Hit, Good, and Perfect, which are

determined by how closely the player's foot aligns

with the center of the obstacle. This game tests the

player’s rhythm and coordination and provides an

aerobic workout, requiring continuous foot

movement and engagement with the music's tempo.

Figure 1: Dance mini game scenario.

The snow skiing mini game (Figure 2) aims to

transport users to a thrilling virtual snowscape,

encouraging them to simulate the physical motions of

skiing and avoid specific obstacles on the way. This

game allows players to virtually ski down a mountain,

with each run focusing on navigating a series of

challenges while descending the slope. The player

controls the direction of their descent by turning their

head left or right, corresponding to their virtual skis'

movement. The course is filled with various obstacles

that players must avoid by either ducking or jumping,

mirroring these actions in real life to navigate the

course successfully.

The game incorporates a life system where

players start with four lives. Colliding with an

obstacle results in losing a life; if all lives are lost, the

game ends prematurely. Additionally, a countdown

timer starts at two minutes, adding a layer of urgency,

with the game concluding if the timer reaches zero.

However, players can extend their time by passing

through checkpoints marked by two flags; passing

directly between them rewards the player with an

additional minute on the clock. This combination of

physical movement and time management challenges

the player’s reflexes and agility and ensures that the

game maintains a high level of aerobic activity.

Figure 2: Snow skiing mini game scenario.

2.1.1 Software and Hardware

Regarding technology, both VR mini games were

developed using the HTC Vive hardware, integrated

with Unity, with a notable difference between them:

the dance game incorporated HTC Vive Feet

Trackers, while the ski game did not require their use.

For the VR dance mini game, the SteamVR plugin

was used to streamline the integration of the foot

trackers, which were essential for tracking foot

movements. Additionally, the game employed a tool

called BeatMapper to create custom beat maps for the

music. This tool allowed the development team to

precisely map the obstacles to the rhythm of the music,

generating a file with the timing and positioning of the

notes. The game script then reads this file to spawn

obstacles at the correct times, ensuring an accurate

rhythm-based gameplay experience.

icSPORTS 2024 - 12th International Conference on Sport Sciences Research and Technology Support

In the VR snow skiing mini game, the “OpenXR

plugin” was used instead of SteamVR, as it was

simpler to work with and did not require the

complexity of integrating the feet trackers. From a

development perspective, the ski game involved more

intricate mechanics, particularly the implementation

of the jumping action. To detect a jump, three

conditions were checked: whether the player was on

the ground, whether there was acceleration along the

“Y-axis” detected by the Vive sensors, and whether

the player's current height was greater than the initial

height within a defined margin of error. A Unity

collider was dynamically adjusted in size for ducking

based on the player's height from the ground. The

collider's height would increase or decrease

accordingly, ensuring it never exceeded the initial

measured height. A force is applied to the

“Rigidbody” component to ensure the player

continuously moves downhill, simulating the effect

of gravity and momentum during the descent.

2.2 Pilot-Study

2.2.1 Participants

Participants in this pilot study were five adults (two

females) aged 25.2 ± 3.9 years (height: 166.2 ± 9.5

cm and body mass: 69.0 ± 4.8 kg). All individuals

were healthy and did not present any constraints for

PA participation. The procedures implemented in this

study were approved by the Ethics Committee of the

University of Madeira (Nº94/CEUMA/2023, 5

December), and all participants previously signed

informed consent.

2.2.2 Instruments

The ActiGraph wGT3X-BT Activity Monitor

(ActiGraph, 2023) assessed PA intensity level while

playing the VR exergame session. The device was

positioned on the right hip following previous

research recommendations (Karaca et al., 2022),

before the experiment commencement. The

accelerometer was programmed before each data

collection moment and started when the VR

exergame session began. The accelerometer was

initialized with a 30 Hz sampling frequency and raw

data from GT3x files were converted to 10 s epoch

data files before analysis. Time spent in sedentary

behavior, light PA, moderate PA, vigorous PA, very

vigorous PA, and moderate-to-vigorous PA was

calculated using the ActiLife software, version 6

(ActiGraph, Pensacola, FL, USA), using the cutoff

points suggested by the previous literature (Freedson

et al., 1998). The number of steps per minute and total

metabolic equivalent of task (MET) were also used

for analysis.

During the VR exergame session, heart rate (HR)

was monitored using the Polar H10 sensor (Polar

Electro, Kempele, Finland) (Polar, 2023), which has

been described as a valid instrument in previous

literature (Schaffarczyk et al., 2022). Participants

used the device in the chest using the manufacturer’s

strap. This positioning ensures optimal contact with

the skin, allowing the sensor’s electrodes to collect

real-time HR data. This instrument has been widely

used in several sports’ activity settings. The mean HR

scores of each session were used for analysis.

To examine the usability of the VR exergame

session, the European version of the System Usability

Scale (SUS) was used (Martins et al., 2015). The

instrument is composed of 10 statements scored on a

5-point Likert scale (1 – strongly disagree, 5 –

strongly agree) and allows the evaluation of the

system's usability. Each participant filled out the

questionnaire after the VR exergame session.

Finally, the rate of perceived exertion (RPE) scale

was used to measure the level of PA intensity based

on the participants’ perception. RPE was collected at

two moments, immediately after each mini-game

completion, using the OMNI picture system

(Robertson, 2004), elucidating different levels of

effort (0 – extremely easy, 10 – extremely hard).

2.2.3 Study Design

Data collection was conducted in a research center

facility equipped with a VR station. The experiment

comprised three phases:

(1) First, participants were asked to fill out a form

to collect information about their demographics (age,

gender, nationality, height, and body mass), followed

by a brief explanation of how the system works and

informed consent signing.

(2) Second, the HCT Vive and PA monitoring

sensors were placed on participants’ bodies, and the

VR exergame session was implemented.

(3) Third, participants reported their RPE and

responded to the SUS questionnaire right after the VR

game session.

Each mini game had a duration of approximately

20 min, and nearly 2 min were ensured for the

transition between the first (dance) and the second

game (snow skiing). The playing sequence of the two

mini games was the same for all participants: first the

dance game followed by the snow skiing game. In

total, each participant played the VR games for nearly

40 min.

Assessing Physical Activity Levels While Playing Virtual Reality Exergames: A Pilot Study

3 RESULTS

Table 1 summarizes the data collected through

accelerometry concerning PA intensity level. During

the VR game session, participants spent more time in

sedentary behavior (37.5 ± 6.6 %), followed by light

(35.1 ± 13.5 %), and moderate-to-vigorous (27.4 ±

17.6 %) activity. Overall, the VR game session

elicited a mean value of 909.6 ± 358.5 steps, with an

average of 27.1 ± 7.7 steps per minute and 123.5 ±

29.7 bpm. These data corresponded to a mean value

of 2.2 ± 0.9 METs.

Table 1: Descriptive statistics for PA intensity.

Variables

M ± SD

Sedentary behavior (min)

12.1 ± 3.0

Light PA (min)

11.1 ± 4.0

Moderate PA (min)

8.2 ± 5.5

Vigorous PA (min)

0.8 ± 0.8

Very vigorous PA (min)

0.3 ± 0.5

Moderate-to-vigorous PA (min)

9.3 ± 6.7

Sedentary behavior (%)

37.5 ± 6.6

Light activity (%)

35.1 ± 13.5

Moderate PA (%)

24.1 ± 14.3

Vigorous PA (%)

2.4 ± 2.4

Very vigorous PA (%)

0.8 ± 1.4

Moderate-to-vigorous PA (%)

27.4 ± 17.6

Total steps counts (n)

909.6 ± 358.5

Steps per min (n)

27.1 ± 7.7

METs

2.2 ± 0.9

Heart rate (bpm)

123.5 ± 29.7

M ± SD (mean ± standard deviation), PA (physical

activity), MET (metabolic equivalent of task)

Figure 3 displays the results of the RPE for each

mini game. Participants perceived exertion scores

were higher in the dance mini game than in the ski

mini game, probably due to whole-body rhythmic

movements elicited and synchronized with the virtual

dance moves.

Figure 4 presents the SUS questionnaire

responses by each participant. The results indicate

that participants would like to use this system more

frequently, and only one participant reported that the

system was not easy to use. Overall, participants

indicated that they would not need technical support

or much time to learn about the system to play the

games. Participants also agreed that most people

could learn how to use the system quickly.

Figure 3: Rate of perceived exertion reported in each mini

game.

Figure 4: System Usability Scale questionnaire responses

by each participant.

4 DISCUSSION

This study presents the preliminary results of a pilot

study conducted in the first testing stage of a new VR

exergame system designed to promote PA.

Concerning PA intensity, most of the VR game

session was spent in sedentary activity (≈ 37.5%),

followed by light activity (≈ 35.1%), and moderate-

to-vigorous activity (≈ 27.4%). Additionally,

combining the data of average steps per minute (≈

21.1) and average HR (≈ 123.5 bpm), the VR

exergame session elicited ≈ 2.2 METs.

Intensity is an indicator of the metabolic demand

of activity, and the MET is a standard unit used to

express exercise intensity, influenced by several

factors such as sex, age, and body composition (Katch

et al., 2011). Regarding METs, the results of this pilot

study were within the range of 1.6 to 2.9, which is

indicative of light PA intensity (Strath et al., 2013).

Curiously, from the participants' perception, the

intensity was higher than the objective measures

collected. Light PA has been associated with RPE

values ranging from 4 to 5 (Strath et al., 2013), which

is lower than the RPE scores reported in this pilot

study (ranging from 6 to 10). Although previous

research has reported RPE is a useful tool for most

icSPORTS 2024 - 12th International Conference on Sport Sciences Research and Technology Support

individuals, scores might be over or underestimated

based on sex or sports experience (Skatrud-

Mickelson et al., 2011).

On the other hand, HR variability is also

associated with changes in PA intensity and is a

frequently used metric for exercise prescription

(Karvonen & Vuorimaa, 1988). In several sports

contexts, professionals use average HR values to

characterize a specific activity. In this study,

participants' average HR was within the data reported

in previous studies. For instance, in a study conducted

with 24 adults aged 27.8 ± 3.3 years, the authors

reported an average HR of 122.8 ± 15.9 bpm while

playing a VR exergame involving standing, jumping,

and arm swinging movements (Park et al., 2020). In

another study involving 129 individuals aged

between 18 and 26 years, an average HR of 109.2 ±

45.0 bpm was registered while playing Just Game 3

(Lin, 2015). Although HR may present a significant

variability based on an individual’s specific

characteristics, including their maximal HR, the

results of the current pilot study suggest a moderate

intensity level elicited by the VR exergame session

(based on the estimation of 195 bpm as maximum HR

for this population). Though METs data indicate a

predominance of light intensity PA, HR insinuates

greater intensity, which might justify the results of

RPE.

In the meantime, participants accumulated ≈ 17.5

min of moderate and moderate-to-vigorous PA.

According to the American Heart Association, among

adults, substantial health benefits are related to 150

min per week of moderate PA or 75 min per week of

vigorous PA (Strath et al., 2013). Unequivocally,

these recommendations would not be achieved

exclusively using VR exergame sessions. However,

this system might emerge as a complementary tool to

traditional PA, offering a different and engaging way

of being active while providing part of the necessary

amount of PA intensity weekly recommended.

Finally, the assessment of the usability of the

system is an important phase of system/product

development (Martins et al., 2015). Besides assessing

PA levels while exergaming, this pilot study also

included the evaluation of the system from the

participants' perspective. Overall, most participants

considered the system easy to use and learn, which

validates its development process.

The current study presents several limitations that

must be recognized. First, this is a pilot study with

few participants, and although the results are

promising, more testing sessions are still needed to

validate the system thoroughly. Second, the VR

exergame session development did not consider

recommended guidelines for structuring PA sessions

(i.e., warm-up, main phase, cool-down). Indeed,

including this structure would allow us to replicate a

traditional PA class in a virtual environment. Third,

details concerning individuals’ previous PA

experience were not collected, which would allow a

more in-depth analysis of the results. Finally, data

collection was cross-sectional, while a longitudinal

approach would be far more informative. Even

though, the results presented are valuable,

particularly by emphasizing the ability of this VR

exergame session to provide light to moderate PA.

Therefore, exergames might be complementary to

traditional PA settings, providing users with a

different and engaging experience while developing

health-related benefits.

5 CONCLUSIONS

In the VR game session (dance plus snow skiing mini

games) designed for this study, participants spent

nearly 37.5%, in sedentary activity, 35.1% in light

activity, and 27.4% in moderate-to-vigorous activity.

The average of steps per minute was 21.1 and average

HR around 123.5 bpm, eliciting approximately 2.2

METs. The results regarding PA intensity suggests

predominance of light intensity activity, however, HR

values suggest greater exercise intensity which is

aligned with participants’ RPE (ranging from 6 to 10).

According to the participants’ perception, the dance

mini game was more physically demanding than the

snow skiing mini game, probably due to the need of

using continuously whole-body movements. The

results of the SUS questionnaire indicate an overall

good usability of the VR system. This study

emphasizes the ability of promoting light to moderate

PA through a VR game session. Exergames might be

implemented as a complementary and diversifying

tool to traditional PA programs.

ACKNOWLEDGEMENTS

This research was funded by the Portuguese Recovery

and Resilience Program (PRR), IAPMEI/ANI/FCT

under the Agenda C645022399-00000057

(eGamesLab).

Assessing Physical Activity Levels While Playing Virtual Reality Exergames: A Pilot Study

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