Real-Time Heart Rate Visualization for Individuals with Autism

Spectrum Disorder: An Evaluation of Technology Assisted Physical

Activity Application to Increase Exercise Intensity

Bo Fu

, Katrina Orevillo

, Dennis Lo

, Andrew Bae

and Melissa Bittner

Computer Engineering and Computer Science, California State University, Long Beach, U.S.A.

Department of Kinesiology, California State University, Long Beach, U.S.A.

Keywords: Real-Time Heart Rate Visualization, Eye Tracking, Autism Spectrum Disorder, Technology Assisted Exercise.

Abstract: Individuals with autism spectrum disorder (ASD) often experience negative relationships with physical

activity and a severe lack of motivation for exercise. While specialized exercise technologies such as internet-

enabled machines and mobile applications have provided some solutions for typically developing individuals,

there is a lack of research in providing exercise technology that specifically considers the needs of individuals

with ASD. This paper presents a real-time heart-rate visualization application, namely the HeartRunner 2.0

App, which aims to engage individuals with ASD to exercise at higher intensity. When used to supplement

exercise sessions, amongst a group of 20 participants with ASD, evaluation results showed that the App helped

83% of participants achieve higher heart rates, 66.6% to maintain heart rates at or above 90 BPM, and 27.7%

to re-engage and achieve heart rates at or above 90 BPM after dropping below that threshold. Furthermore,

eye tracking analyses indicate that those individuals who achieved higher heart rates have employed a more

focused gaze patterns with less distributed fixations in their visual searches, as well as greater efforts in

scanning various cues in the given visual scene, suggesting that visual interaction with the App may have

contributed to elevated performance in the experiment.

1 INTRODUCTION

Gaining popularity during the 2000s, the intertwining

developments of exercise and technology have given

rise to a joint field of digital fitness – with

technological advancements emerging to motivate

physical activity for its users (Parrott et al., 2020).

Users of fitness-oriented technical machines and

applications have often found these devices to be

useful tools for encouragement and prolonging of

physical activity, resulting in overall improvements in

personal health and quality of life. Shortcomings of

these tools, however, become prevalent when applied

to certain communities, such as those diagnosed with

autism spectrum disorder (ASD). Studies focusing on

ASD prevalence in the United States concluded that

1 in 54 children living in the U.S. were diagnosed

with ASD as of 2016 (Matthew et al., 2020) –

exhibiting characteristics including “deficits in social

communication and interaction”, “restrictive

http://orcid.org/0000-0001-9874-9551

interests”, and “repetitive behaviors” (Shaw et al.,

2023). Because individuals with ASD exhibit such

characteristics, alternative approaches toward

encouraging physical activity, including technology-

based applications and machinery, must be

considered. Individuals with ASD often experience

negative relationships with exercise due to a myriad

of factors, which can include lacking social skills,

deficits in gross motor skills, and underdeveloped

coordination leading to low motivation when

engaging in physical activities. ASD populations, as

a result, are severely more likely to experience

sedentary lifestyles, often leading to obesity and other

health conditions (Dieringer et al., 2017).

This paper aims to investigate the application of

technology-assisted exercise in supporting

individuals with ASD during physical activity. More

specifically, a tablet application is developed and

evaluated to determine whether visualizing heart rates

in real time during physical activity would be

beneficial in encouraging higher intensity of physical

Fu, B., Orevillo, K., Lo, D., Bae, A. and Bittner, M.

Real-Time Heart Rate Visualization for Individuals with Autism Spectrum Disorder: An Evaluation of Technology Assisted Physical Activity Application to Increase Exercise Intensity.

DOI: 10.5220/0012354500003660

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

In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2024) - Volume 1: GRAPP, HUCAPP

and IVAPP, pages 455-463

ISBN: 978-989-758-679-8; ISSN: 2184-4321

455

activity for individuals with ASD. A preliminary

research (Fu et al., 2020) has found that real-time

visualizations of heart rates were helpful in engaging

ASD individuals in physical activity. However, a

multi-user mode to simulate a social environment for

multiple users in one exercise session did not provide

positive encouragement, as most individuals with

ASD found it to be too competitive and some gave up

on the exercise as a result. As such, the application

presented in this paper proposes a single-user mode,

in addition to utilizing music and differing

visualization techniques - compared to those

demonstrated in (Fu et al., 2020) - that aim to

overcome the aforementioned issues discovered in

(Fu et al., 2020).

2 THE HeartRunner 2.0 APP

The HeartRunner 2.0 App is built for compatibility

with Apple iPadOS devices using the Swift

programming language in Xcode, employing the

Model-View-Controller architectural pattern to

implement the user interface derived from

FlappySwift (Murray, N., 2019). Additionally, the

application makes use of the Scosche Rhythm24

Software Development Kit (SDK)

to allow heart rate

data retrieval from the Scosche Rhythm24 Bluetooth

heart rate monitors

Prior to beginning a physical activity, a user

would open the HeartRunner 2.0 App on their iPad

device to take a photo of themselves (using the built-

in camera on the tablet) as their profile picture in the

App. Wearing a Scosche heart rate monitor, the user

can then begin an exercise session after setting a

targeted duration (i.e., a desired exercise duration in

minutes). During the exercise, the App would show

their profile picture as a main character flying

forward a path, and their heart rates measured in beats

per minute (BPM) would be visualised in real time as

the readings from the Scosche heart rate monitor

elevate or drop. The exercise session ends once the

target exercise duration is completed, and the user

will be shown the highest heart rate achieved during

that session.

Figure 1 shows a screenshot of the HeartRunner

2.0 App interface during exercise sessions that

consists multiple elements that respond to real-time

heart rate readings, including:

1. Heart Rate Label: Displays the user’s heart rate

reading in BPM in real time;

https://www.scosche.com/rhythm-sdk, last accessed Oct

2023.

2. Profile Picture: At different ranges of heart

rates (as depicted in Table 1), the profile picture

taken by the user at the beginning of the user

flow is placed at different horizontal locations

on the screen – toward the left side

(“beginning”) of the screen for lower heart rate

readings, and toward the right side (“end”) for

higher heart rate readings;

3. Sky Color and Platform Speed: At different

ranges of heart rates (shown in Table 1), the

color of the sky in the background of the

platform would be modified to provide further

indication of the changes in heart rates for that

user. Additionally, the speed at which the

platform moves in the horizontal direction is

adjusted with heart rate readings at lower

ranges moving at a slower pace than readings

at higher ranges;

4. Background Music (not pictured in Figure 1):

Upon reaching a heart rate of 90 BPM, the App

would play music using the audio player on the

tablet device. The song “Happy Rock”

(Bensound, 2022) would be played as the

exercise continues, which has the distributor

labels of having very high/high energy levels

and happy/energizing mood. 90 BPM was

chosen as the threshold to initiate music play

based on the recommended maximum heart

rate determined by age, whereby for those 16

years old and over: Maximum Heart Rate = 220

− Current Age (Centers for Disease Control and

Prevention, 2022; Riebe et al., 2018; Physical

Activity Guidelines Advisory Committee,

2008), and all participants who took part in the

evaluation of the App being in the 18-21 year

old age group;

5. Countdown Timer: Displays the remaining

time in the exercise session (in minutes). The

timer incorporates a circular display with a

yellow circle that progressively empties,

resembling a pie chart, as each second elapses.

At the completion of each minute, the circle

returns to its original yellow state and continues

the countdown cycle.

https://www.scosche.com/rhythm24-waterproof-armband-

heart-rate-monitor, last accessed Oct 2023.

HUCAPP 2024 - 8th International Conference on Human Computer Interaction Theory and Applications

456

Figure 1: The HeartRunner 2.0 App user interface with

elements that respond to real-time heart rate readings.

Table 1: The HeartRunner 2.0 App Visualization Features.

Heart

Rate

(BPM)

Profile Picture

Position

Sky

Color

Platform

Speed

Background

Music

Less than

Left-most fifth

of screen

Grey 1 Off

Between

80 & 90

Left-most fifth

of screen

Grey 1.25 Off

Between

90 & 100

Second left-

most fifth of

screen

Blue 1.5 On

Between

100 & 110

Center fifth of

screen

Green 2 On

Between

110 & 120

Second right-

most fifth of

screen

Orange 3 On

More than

120

Right-most fifth

of screen

Red 4 On

3 EVALUATION

A series of experiments were conducted over a 3-

month period involving 20 individuals with ASD. All

participants were verbal, able to read and understood

the instructions given in the experiments.

Participants were asked to complete a stationary

bicycle exercise session. Each participant took part in

the study on two separate days, completing a control

exercise session (i.e., without the support of the

HeartRunner 2.0 App) on one day and an

experimental exercise session (i.e., with the support

of the HeartRunner 2.0 App) on the other. The order

in which individual participants experienced each

session type was chosen randomly and

counterbalanced overall to minimize order effect.

Individual participants were asked to ride a Matrix

IC7 Indoor Stationary Bicycle, as shown in Figure 2.

Prior to the session, the seat and handlebar heights of

the stationary bicycle were adjusted according to the

participants’ height and comfort. These settings were

recorded so that participants would maintain the same

seat and handlebar heights for both sessions. Each

participant was also assisted to wear one Scosche

Rhythm24 Heart Rate Monitor on the upper forearm

(just below the elbow). Following the physical

configurations, each participant was given an iPad

with the HeartRunner 2.0 App installed. Participants

were assisted when completing the initial steps of the

application’s user flow, including taking a profile

picture and ensuring Bluetooth connection to the

heart rate monitor.

a. A participant in a

control exercise session

b. A participant in an

experimental exercise

ession

Figure 2: Physical setup of the two experimental conditions.

Individuals participating in the control exercise

session used a “Blank” version of the HeartRunner

2.0 App (as shown in Figure 2a), where a white screen

appeared for the duration of the session instead of the

actual HeartRunner 2.0 App interface. Participants in

this group were instructed to complete a 20-minute

exercise session on the stationary bike while using the

“Blank” version of the application. Following the

session, the heart rate monitor was removed from the

participants’ forearms, and the heart rate data was

extracted from iPad storage for analysis. Individuals

participating in the experimental exercise session

were also instructed to complete a 20-minute exercise

session on the stationary bike while using the

HeartRunner 2.0 App (as shown in Figure 2b), where

they would be able to see how various interface

components reacted according to their heart rate

changes. In addition to wearing the Rhythm24 Heart

Real-Time Heart Rate Visualization for Individuals with Autism Spectrum Disorder: An Evaluation of Technology Assisted Physical

Activity Application to Increase Exercise Intensity

457

Rate Monitor, participants in the experimental

exercise session also wore the Tobii Glasses Eye

Tracker (with controller model version 0.16194 and a

50Hz sample rate), which tracked and recorded

participants’ eye movements during an entire exercise

session. Following the session, the heart rate monitor

was removed from the participants’ forearms, and the

heart rate data was extracted from iPad storage for

analysis.

4 RESULTS

Out of the 20 participants who took part in the

experiment, we discarded corrupted data from 2

individuals (due to sensor failure and other technical

issues resulting in null data). In total, data from 18

participants, or 36 individual exercise sessions

(including 18 control exercise sessions and 18

experimental exercise sessions) were analyzed and

reported in this paper.

When comparing the heart rate readings for

participants between the experimental and control

exercise sessions, as shown in Figure 3, 15 out of 18

participants (83.3%) experienced higher average

heart rate readings when supported by HeartRunner

2.0. On average, these 15 participants exhibited an

increased heart rate of approximately 12.152 BPM.

Additionally, the heart rates of participants after

hearing the music for the first time were analyzed as

a measure of sustained physical activity. 12 out of 18

participants (66.6%) continued to exhibit heart rates

above 90 BPM for the duration of their exercise

sessions after music was played for the first time. Of

the remaining 6 participants, none moved below 90

BPM for the entirety of the remaining session time. 5

participants (27.7% of participants) had readings

which dropped below 90 BPM for short intervals

before increasing past the 90 BPM mark again – with

some only moving below 90 BPM once in the time

after first reaching that mark. After the initial music

start, these 5 individuals stayed mostly above 90 BPM

– hearing music for most of their exercise session.

The remaining 1 individual also experienced

fluctuation around the 90 BPM mark, though staying

mostly below 90 BPM and without music. The

aggregated group averages are shown in Figure 4.

These findings may indicate that the heart rate

visualization features of the HeartRunner 2.0 App

served as motivating factors for individuals with

ASD, encouraging participants to participate in their

exercise sessions at higher intensities as shown

through increased heart rate readings during

experimental exercise sessions. It may also be

suggested that, with no participants reaching heart

rate readings of 90 BPM dropping below that

threshold for the entire remaining session time,

participants interpreted changes in the visualization

elements as success signals. In response, participants

may have strived to reach “success” after elements

reverted to their original states, with 5 participants

rising above 90 BPM after the application stopped

playing music – indicating that such elements could

contribute to the sustainment of physical activity.

Figure 3: Average heart rate readings for individual participants with ASD during exercise sessions without the HeartRunner

2.0 App (denoted in solid blue, on the left) and with the HeartRunner 2.0 App (denoted in shaded orange, on the right).

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458

Figure 4: Average heart rate readings for participants with ASD over a 20-minute period, for both control exercise sessions

(denoted as a solid blue line) and experimental exercise sessions (denoted as a dashed orange line).

To further compare the visual attention and

interaction with the HeartRunner 2.0 App amongst

the participants, we grouped them into two categories

using a median split of the average heart rate recorded

across all experimental sessions. In other words, the

participants who achieved an average heart rate above

the median value (at 118 BPM) are referred to as the

above median heart rate group, and those participants

who achieved a lower average heart rate are grouped

into the below median heart rate group. Using eye

tracking, we aim to compare how these two

participant groups spent their visual attention during

the exercise, and whether there are significant

differences in gaze behaviors between the group who

achieved higher heart rates than those who did not.

In this paper, we report a number of notable gaze

measures such as saccade lengths and convex hull

areas. As participants interact with an interface such

as the HeartRunner 2.0 App showing real-time heart

rate visualizations, they would direct their gaze to

various points of interest on the screen. They may

fixate their attention on a visual point and moves their

gaze in search for the next relevant visual cue as they

interact with the App. Fixations are typically

understood as behaviors of information processing

activities, where a person’s eyes are relatively

stationary. Saccades refers to those quick eye

movements during successive pairs of fixations and

are typically understood as behaviors of information

search activities. Given fixations located on various

parts of a tablet screen, the distance (measured in px)

between pairwise fixations are determined by saccade

lengths, which typically indicate how far or close a

person searched for relevant visual information. An

interactive session would entail multiple stages of

information search and processing activities, where a

collection of fixations would be recorded by the end

of a session. The bounding fixations found in a

session would therefore outline an area (measured in

) where all fixations generated during a session

fall within, and referred to as the convex hull area,

which typically indicates how large or small a

person’s entire gaze journey captured during an

experimental session.

In addition to the results shown above, our eye

tracking analysis has revealed further insights into

how the two participant groups’ gaze behaviors

differed during the experiment. Though the

differences were not shown to be statistically

significant (potentially due to a small sample size),

these results provide useful evidence nonetheless for

future research in how accelerated heart rates may be

associated with certain desirable gaze behaviors. This

knowledge may inspire the development of

subsequent refinement of the visual features and

functionalities of the HeartRunner 2.0 App and

beyond.

Figure 5 shows the correlations between heart

rates and the average saccade lengths. In particular,

those participants who achieved higher heart rates

exhibited smaller saccade lengths (r = -0.511, p >

0.05). This result is in contrary with the participant

group who achieved lower heart rates, whereby

longer saccade lengths were found (r = 0.444, p >

0.05). In other words, those individuals who

generated higher heart rates searched for visual cues

that were relatively close to one another, suggesting a

more consistent and controlled interaction. This is

further amplified by the standard deviations (StDev)

found in each participant group. As shown in Figure

6, a positive correlation (r = 0.345, p > 0.05) was

found for the below median participant group,

whereas a negative correlation (r = -0.273, p > 0.05)

was found for the above median participant group.

This result indicates that those individuals who

achieved higher heart rates during the given physical

Real-Time Heart Rate Visualization for Individuals with Autism Spectrum Disorder: An Evaluation of Technology Assisted Physical

Activity Application to Increase Exercise Intensity

459

activity exhibited less dispersed fixation points,

suggesting more focused search behaviors during

their interaction with HeartRunner 2.0.

Figure 5: Positive (for the below median heart rate group,

where r = 0.444, p > 0.05) and negative (for the above

median heart rate group, where r = -0.511, p > 0.05)

correlations between heart rate and average saccade length.

Figure 6: Positive (for the below median heart rate group,

where r = 0.345, p > 0.05) and negative (for the above

median heart rate group, where r = -0.273, p > 0.05)

correlations between heart rate and the StDev of saccade

lengths.

Overall, throughout an entire exercise session, we

found that those individuals who achieved higher

heart rates also generated longer scanpaths (i.e., the

sum of all saccade lengths captured during an

interaction), as shown in Figure 7. This correlation

was evident in both participant groups with varied

degrees (r = 0.261, p > 0.05 for the above median

group, r = 0.416, p>0.05 for the below median group),

suggesting an increased engagement with the

HeartRunner 2.0 App may have contributed to

elevated heart rates during the experiment. Similarly,

we found positive correlations between one’s heart

rate and the visual area this person searched and

processed information (i.e., convex hull area), as

shown in Figure 8. This is evident in both participant

groups and notably, the correlation found in the above

median group is shown to be statistically significant

(r = 0.633, p < 0.05 for the above median group, r =

0.416, p > 0.05 for the below median group), showing

that the individuals with higher heart rates also

scanned a larger area as they interacted with the

HeartRunner 2.0 App.

Figure 7: Positive correlations found in both participant

groups between heart rate and scanpath length, where r =

0.261 (p > 0.05) in the above median heart rate group and

r = 0.416 (p > 0.05) in the below median heart rate group.

In summary, the experimental results showed that

83.3% of participants with ASD exhibited increased

heart rates during their exercise session supported by

the HeartRunner 2.0 App, with these participants

having an average increase of 12.152 BPM. After the

application’s music functionality was triggered for

the first time per user, 66.6% of these participants

were able to maintain heart rates at or above 90 BPM

for the entire remaining period of their exercise

sessions while another 27.7% of participants stayed

mostly at or above 90 BPM with few fluctuations

below this benchmark. These results suggest that real-

time heart rate visualizations such as those included

in the HeartRunner 2.0 App can serve as effective

motivating factors for individuals with ASD,

providing encouragement for them to exercise for

longer durations and in higher intensities.

Furthermore, the findings from analyzing

participants’ eye movements indicate that those

individuals who achieved higher heart rates have

exhibited gaze behaviors resembling a pattern of

more focused visual search (smaller saccade lengths),

HUCAPP 2024 - 8th International Conference on Human Computer Interaction Theory and Applications

460

less distributed points of interest (lower StDev of

saccade lengths), and greater efforts in scanning

various cues in the given visual scene (longer

scanpaths and larger convex hull areas). This result

provides further evidence for the effectiveness of

real-time heart rate visualization in the context of

technology-assisted exercise and the potential of its

future application in other scenarios beyond the

experimental conditions shown in this paper.

Figure 8: Positive correlations found in both participant

groups between heart rate and convex hull area, where r =

0.633 (p < 0.05) in the above median heart rate group and

r = 0.096 (p > 0.05) in the below median heart rate group.

5 RELATED WORK

A brief overview of related work is presented in this

section, more extensive reviews of empirical

evidence for the use of exercise as an evidence-based

practice for individuals with ASD can be found in

(Dillon et al., 2017; Bittner et al., 2018).

In recent years, technology assisted exercise has

been shown to have a positive effect on individuals

with ASD (Wong et al., 2015), suggesting visual

stimulation from the use of technology may increase

participation. Technology has been shown to be an

effective mean to promote motivation (Takeo et al.,

2007), with prior studies demonstrating individuals

with ASD are able to engage in more on-task

behaviors and may learn physical activity skills at a

faster rate than those without technology-aided

instruction (Case & Yun, 2015). In another study, the

notion of coupling gaming and technology is applied

to engage individuals in exercise, as body

movements, reactions, and energy expenditure are

tracked through participation (Trout & Christie,

2007). This is further investigated in (Anderson-

Hanley et al., 2011), where findings have shown

significant improvements in attention and working

memory and decreases in stereotypical behaviors in

individuals with ASD immediately after participating

in a 20-minute exergaming intervention.

Motivated by these prior research efforts, this

paper aims to extend the existing body of knowledge

in technology assisted exercise designed specifically

for individuals with ASD by proposing an application

that visualizes heart rates in real time to help with

comprehension of energy expenditures during

physical activity, and to sustain and evaluate exercise

intensity. More specifically, informed by prior

evaluations of HeartRunner 1.0 (Fu et al., 2020) that

supported a multi-user mode for multiple users to

compete with one another during an exercise session,

we aim to reduce social pressure while promoting

effective visual stimuli in HeartRunner 2.0.

6 CONCLUSIONS & FUTURE

WORK

This paper presents an application of real-time heart-

rate visualization, namely the HeartRunner 2.0 App,

which aims to promote engagement and exercise

intensity during physical activity for individuals with

ASD. The overall goal of the App is to contribute to

technology assisted exercises designed specifically

for this particular group of individuals who typically

lack motivation in exercising, which tends to lead to

a cohort of health problems. Through a controlled

experiment involving 20 individuals with ASD, we

found evidence suggesting the proposed App is

effective in helping individuals with ASD to reach

higher intensity during exercise and that engagement

with the App has likely contributed to elevation in

heart rates. However, the findings from this research

should be interpreted within the limitations of the

experiments conducted. Firstly, it may be argued that

music can be a bothersome obstacle for some

individuals with ASD, since the experiment shown in

this paper was not designed to exclusively measure or

quantify the effects of music in such cases, it would

be necessary to follow up with additional purposely

designed studies to validate potential speculations.

Secondly, although the participants who took part in

the study shown in this paper were on the ASD

spectrum, we did not group these individuals into

more refined categories, whereby future experiments

with more cultivated user groups may be helpful to

further the body of knowledge in this domain.

Thirdly, we attempted to collect participant feedback

Real-Time Heart Rate Visualization for Individuals with Autism Spectrum Disorder: An Evaluation of Technology Assisted Physical

Activity Application to Increase Exercise Intensity

461

using established usability questionnaires, however,

these questions were too difficult for the participants

to comprehend, whereby future research could

potentially focus on developing more appropriate

forms of feedback for individuals with ASD.

Furthermore, some variables were not controlled,

such as whether the participants had energy drinks

before the exercises or collecting heart rate histories

of the participants as baselines to compare against the

values collected in our study, where future research

may potentially investigate.

Nonetheless, the study shown in this paper

provides a basis for utilizing real-time heart rate

visualization and music to benefit individuals with

ASD in technology assisted exercise, future work

could collect data from larger sample sizes to analyze

in between-subject experiments. In addition, usability

studies can be integrated to assess the specific visual

components that may be deemed more usable and

effective to this particular user group. Furthermore,

additional use cases and application scenarios may be

investigated to determine the effectiveness of the

HeartRunner 2.0 App. Lastly, while the focus of the

experiment shown in this paper emphasizes on the

evaluation of whether higher intensity can be

achieved while supported the HeartRunner 2.0 App,

future experiments may investigate whether

participants supported by the App would exercise for

longer durations than those who did not.

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