Miles To Mind
Proposing an augmented reality based running application for individuals
prescribed running to manage symptoms of mild-moderate depression.

By

Abhinav Paul

M.Des. Interdisciplinary design

A CRITICAL AND PROCESS DOCUMENTATION THESIS PAPER
SUBMITTED IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF DESIGN
EMILY CARR UNIVERSITY OF ART + DESIGN
2022

Table Of Contents
1. Abstract

3

2. List of Acronyms

4

3. Introduction

5

4. Context and Background
4.1 What is the objective?
4.2 Research direction
4.3 Research findings
4.4 Existing models

6
6-7
8-9
10

5. Criteria for Investigation

11

6. Thesis Design Project
6.1 What is the purpose of running in this application?
6.2 Effect of virtual companions in AR
6.3 Use cases
6.4 Design specifications
6.5 Design outcomes
6.6 Implication for designers
6.7 Scope and limitations

12
12
13-15
16-25
26
27-28
28

7. Analysis and Discussion

29

8. References

30-31

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1. Abstract
This thesis proposes an Augmented reality (AR) application designed to assist people
experiencing mild-moderate Major Depressive Disorder (MDD). I am building on an existing
solution space of distance running which has been shown to be an effective tool of managing
symptoms of MDD based on multiple recent studies in the field of neuroscience and exercise
science. These studies have prompted doctors to prescribe exercise treatment plans to mitigate
symptoms. However, MDD often makes it difficult for people to continue these routines due to
symptoms of fatigue associated with MDD. My proposed application design aims to address the
challenging obstacles that people face after they begin their exercise treatment plans,
specifically running.
During my recovery from moderate MDD, I understood that running just for the sake of running
was another barrier that I had to overcome. Based on some methods I used to keep myself
continue a run like chasing an imaginary animal or setting a small mental objective of 10–20 m,
I realized that the activity of running could be made more engaging and be based on a purpose
other than covering a certain distance, with the help of mixed reality mediums such as
Augmented Reality (AR). This thesis lies within a speculative framework assuming by the end of
the decade, mixed reality interaction is simplified enough for eyewear without requiring bulky
headsets.
Through the proposition of an Augmented Reality (AR) based running application, I explore the
idea of using AR to (1) use running as a play centered activity to chase using visual cues, instead
of a competitive activity to cover a certain amount of distance, and (2) explore the role of
companionship during the run in the form of a virtual companion.
The proposed model could be described as an overlap between an AR based game called
Pokémon GO and existing running services like Strava.
KEYWORDS
Depression, running, augmented reality, virtual companion, chasing, gamification.

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2. List of Acronyms
AR- Augmented Reality
BDI- Beck Depression Inventory
DG- Dentate Gyrus
EE- Energy Expenditure
HR- Heart Rate
MDD- Major Depressive Disorder
VAA- Virtually Assisted Activity
VR- Virtual Reality

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3. Introduction
The thesis is informed by a combination of existing literature in the field of neuroscience and
exercise science, on running and its effect on the symptoms of MDD along with insights from
my personal process of recovering, through medical assistance, from moderate depression over
the span of five years, from 2016 to 2021. It is important to clarify that this thesis focuses on
individuals with mild-moderate MDD who have been already prescribed physical activity to
manage the symptoms for depression and have certain minimum capacity to begin the process.
I would also like to address the ableist aspects that come into picture when researching
primarily through the lens of exercise sciences. I acknowledge that depression is a complicated
illness with many sociocultural factors that need to be taken into account when addressing the
issue. Hence this thesis does not approach depression with an intention to fix the entire
problem, rather explore one of multiple solutions like aerobic activity that are recommended to
the individuals affected by depression.
Existing research studies in the field of exercise science show that running like other forms of
aerobic activities have effects similar to medication and therapy when treating MDD (Déry et
al., 2013). However, even though I was aware of this idea, running just for the sake of running
felt less intuitive and was also challenging since depression is characterized by a severe drop in
motivation to move. Hence the methods I relied upon frequently like visualising chasing an
imaginary animal/object, imagining scenarios like “if I don’t reach that bench before that car I
would have to start over again” or even picturing dribbling a football, offered great
psychological assistance. Based on the combination of this habit of visualising, and research in
neuroscience that suggested that people with higher depression scores [measured through
Beck Depression Inventory (BDI)] showed a decline in semantic coherence tasks but displayed
above average performance in visual coherence tasks (Remmers et al., 2016), prompted me to
consider proposing augmented reality (AR) as a possible tool of assistance.
Hence in an attempt to generate any instinctive response from the user to move, the
proposition is to design a mixed reality application using Augmented Reality (AR) to incorporate
visual incentives into the real world that the user can see and react towards. The vision is to
have a moving avatar, like a virtual creatures/avatar, in an AR environment that the user is
compelled to find and capture using cues such as virtual footprints. The avatar once caught can
become a virtual companion for the next run who assists you in finding a new, more challenging
companions and explore different running routes.
This thesis also addresses the possible importance of having a virtual companion that not only
offers directions during the run but also acts as a companion to interact with in the AR
environment. There are psychological studies that show “animal-assisted interventions have
the potential to significantly reduce depressive symptom”. (Beetz et al., 2012, p.7)

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4. Context and Background
4.1 What is the objective?
The purpose of this body of work is to envision an Augmented Reality running service meant for
people prescribed aerobic activity to manage symptoms of mild-moderate MDD. I specify the
range being mild-moderate since in the literature I researched, it was specified that they were
only addressing individuals with mild-moderate MDD, and that extremely severe cases might
require a specific medical intervention (Dunn et al., 2005, p.2). In other words, many severe
cases of MDD in people have additional socio-cultural complications that need to be addressed
parallel to medical and exercise treatment through various forms of therapy1.
4.2 Research direction
When dealing with any problem space as a design learner, many traditional design approaches
try to divert away from personal experiences on which the solution is built. However, I chose to
incorporate my own experiences of recovery from moderate depression over the past five years
into my framework for two main reasons (1) Depression has variability, meaning many
combinations of events can trigger or treat depression in an individual. I believe it is important
to have these experiences shared in some space, which can then be treated like a blueprint for
anyone trying to overcome the problem themselves in the future. (2) Research is a crucial
aspect of design and in order to cultivate a precise sense of gathering research insights from
others, I think a starting point could be to research myself, the one person I know best.
Including existing research in parallel to personal experience is important. Researching
literature dealing with clinical depression along with existing services for runners was another
key aspect since many current services such as Strava, a popular mobile application used by
runners and cyclists to explore routes and record activity data, offer aspects to the user which
can be incorporated as additional frameworks.
Phase 1; March 2021 – May 2021 (Analysing running infrastructure in Vancouver)
Noticing the existing infrastructure to make a city “runner friendly” was the first thing I took
into consideration. Even though I still ran occasionally in my hometown in India, Vancouver felt
instinctively more inviting for running after I arrived here in April 2021. A key reason that is
immediately evident is the existence of pedestrian sidewalks throughout the city which was not
common in my hometown. This makes road running feel safer and someone doesn’t need to go
to a dedicated space to run like stadiums or open grounds, which is where I used to run when I
was back home. Consequently, a safer running infrastructure allows more people to run and
watching more people run gave me some psychological push to go out and run as well.
Secondly, the presence of running trails in Vancouver city offer a change in environment and
terrain for runners which also helps in keeping the activity non-monotonous. These insights
1

Therapy is however not just useful in more severe cases and is advised for MDD treatment of even mild severity.

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allowed me to have an initial image of the environment I want to use as a foundation for the
following work.
Phase 2; May 2021 – October 2021 (Literature research/ testing research)
The key source of information through literature study about running and depression was from
studies done in the field of Neuroscience and Exercise Science2. One specific research offered a
measurable component in terms of running and its effect of depression i.e., (approximately
17.5 kcal / kg / week over a period of 12 weeks is an effective treatment of MDD of mild –
moderate severity (Dunn et al., 2005). For me (75 kg) it meant having an output of ~187 kcal /
day which was around 2km / day of activity at an aerobic heart rate (HR) (136-154 bpm). This
was difficult initially because my HR was very high (anaerobic zone) (155-173bpm) in the initial
runs since I was coming from a rather sedentary lifestyle but became steady after around 3
weeks. The output was still irregular for me but there was an average consistency of around 3
runs / week along with having ~5000 steps of walking every day. At around three and half
month mark, there was a noticeable change in the general motivation to do things and I was
able to cut off medication (under medical supervision) for the first time in a span of three years.
Apart from the measurable aspect, books related to the importance of running in people of
certain cultures (e.g., Tarahumara runners mentioned in the book Born to Run) (McDougall, C.
2011) prompted the question of why humans ran in the past compared to why we run in the
modern era. This directed me to information on the evolutionary perspective of running in
humans. Research suggested that two of the original purposes of running may have been to
follow wounded prey while hunting (Bramble and Lieberman, 2004) and to escape from
predators.

2

I acknowledge that this topic does raise questions about the ableist assumptions of running, however the scope
of this thesis is such that it focuses on ‘one of the solutions’ offered in treatment instead of proposing a one size
fits all solution for depression

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4.3 What are the research findings?
The fundamental aspect of depression to consider was that a key symptom of the illness was a
prolonged drop in motivation, also commonly described as loss of interest in any activity. But
aerobic exercises like distance running can ameliorate the effects of depression in some cases
(Shulkin., 2016, p.8). This creates a deadlocked situation, where movement can generate
motivation, but you require motivation to generate movement. So even if the person suffering
gathers the effort to act towards recovery, the process offers extreme friction that they must
drive through.
A study suggested that individuals with higher depression scores on BDI (Beck Depression
Inventory) show an unusual response to instinctive stimuli. People with higher levels of
depression levels showed a decrease in semantic coherence compared to people with normal
BDI scores but, displayed not only normal, rather “enhanced” performance in visual coherence
(Remmers et al., 2016). This indicates to some extent that even though motivation is hampered
in people with MDD, certain instinctive responses can still be responsive enough. This provides
us with an inclination to use as visual stimuli as a key factor driving the run, that could work
effectively for someone with MDD.
Considering humans have been hunter gatherers for much of our ancestral past (approximately
1.6 million years), the key purpose of running has been catching, scavenging or escaping. Since
we no longer have a need to run for scavenging or hunting in the modern lifestyle, running just
for the sake of running might feel less intuitive for some people. Looking at this from another
perspective, I believe distance and pace can be viewed as outcomes of the objective, and not
the objective itself.
Another crucial insight that seemed to work as mentioned before was through research which
measured the dose response of the physical work needed to experience any noticeable
improvements in people with mild – moderate MDD. Specifically, aerobic exercise at a dose
consistent with public health recommendations (approximately 17.5 kcal / kg / week) over a
period of 12 weeks is an effective treatment of MDD of mild – moderate severity (Dunn et al.,
2005). Also, an output of around 7.0 kcal / kg / week was considered as a ‘low dose’. This gives
us 2 key points to work around,
(1) a long-term requirement of 12 weeks (“12 weeks of exercise lead to increased DG (Dentate
Gyrus) blood volume in both mice and humans, and in mice the DG (blood) volume increase
was further shown to correlate with increased neurogenesis”). (Déry et al., 2013 p.2).
(2) a short-term requirement of 7-17.5 kcal / kg / week.

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In my situation considering the depression was diagnosed to be of moderate severity, the EE
(energy expenditure) at aerobic HR at which I began to observe noticeable progress in my
health was between 4-9.3kcal/kg/week over a duration of four months which is 3-7 runs of 1
km per week. This was considerably lower than what I had estimated. Considering that the
study I referred to by A.L. Dunn in 2005 measured the prescribed range in an indoor
environment, and I always ran outdoors, I would not rule out the possibility of the potential
benefit of aerobic activity prescription in combination with open natural environments in my
process of recovery.
This literature review provided important metrics that could be measured. The research on
running, depression, and the relation between two provided with a general design framework
of running to chase. The measurable data like minimum energy expenditure (EE) and duration
of runs offered the foundation for the objectives that could be incorporated in the envisioned
design proposition.

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4.4 Existing models
Current services based on running predominantly rely on distance and pace as the key
motivators for runner and these can be categorized primarily into post run metrics. Services like
C25K (Couch to 5k) use ‘audio’ instructions to manage pace during a run for beginners who
want to achieve their first five km milestone. However, for individuals with MDD, verbal
instructions may interfere with the benefits of exposure to natural environments and also
might not be the most effective method since they are shown to have a decline in their ability
at semantic coherence tasks (Remmers et al., 2016).
Other popular running applications like Strava or Samsung health collect running data that the
user can see after the run to gain insights about their pace, distance, route covered, cadence
etc. They work much better with wearables like smart watches that allow you to record heart
rate (HR) and VO2 max which is the maximum rate of oxygen consumption measured during
incremental exercise; that is, exercise of increasing intensity. All these data visualisations offer
useful information in tracking progress however the primary aspect I would highlight in my
proposed application would be the heart rate zone instead of distance covered, since running
at an aerobic HR zone has been shown to offer the most noticeable results in treating
mild/moderate MDD. Also, a visualization of total energy expenditure so the user can see if
they are on track with the 7 - 17.5kcal / kg / week range is helpful instead of showing it in the
form of complex numerical data on the application interface.
Pokémon GO, is a similar platform that made people be ‘outside’ and interact with real world. It
is a mobile based game that uses AR where the user has to navigate their real surrounding
environment to catch various types of virtual avatars (Pokémons). Together with physical
activity and motor skills, the game encourages players to explore their local communities and,
in the process, introduces them to new spaces. (Marquet et al., 2017). Also, mediums such as
AR offer the appropriate amount of visual stimulation without blocking the awareness to
surrounding environment. But in the case of designing towards mental health, the usability is
oriented towards personal experience instead of focusing on a social experience (e.g., not
having a social comparative aspect like in Strava).

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5. Criteria of Investigation
The proposition of an AR based running application is focused on a small fraction of individuals
who experience symptoms of clinical depression. The inclusion criteria for the design
framework mostly includes,
• MDD symptoms ranging from mild to moderate
• Individuals who are taking therapy or medication to treat mild/moderate MDD
• Individuals who have been prescribed aerobic activity to manage symptoms of MDD
• Individuals who are in a physical capacity to begin the process of running3
• Individuals who have access to surroundings with a safe running infrastructure4

3

Exercise programs are encouraged to be tailored to individual needs, taking into consideration age, pre-existing
health conditions and presence of any stressors in their surrounding environment.
4
I am considering the difference in running infrastructure between my hometown, Jalandhar in India, and
Vancouver

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6. Thesis Design Direction
6.1 What is the purpose of running in this application?
Running for distance implies running towards a fixed point instead of one which is moving,
which would be the case in chasing. Running for distance and pace are however powerful
motivators in many cases and recording these metrics in fact offer valuable insights to track
progress. However, through this application instead of having the distance covered as a reward
for the run, the reward is what the runner gathered because of running that certain amount of
distance which is catching new and gradually challenging avatars and gaining incentives in the
form of virtual companions, like Pokémons. I am therefore proposing that while making a
running application for individuals with MDD, running should preferably be incorporated as an
outcome of an activity and not the activity itself.
6.2 Effect of virtual companions in AR
Animal-assisted therapies involve interaction between patients and an animal with the aim to
improve mental wellbeing in individuals. Research on dog assisted intervention in hospitalised
people with MDD concluded that animal-assisted therapy causes highly significant reductions of
state anxiety. Presence of dogs may offer an additional therapeutic benefit that might decrease
anxiety and enhance psychotherapeutic strategies and motivation of patients and therapists.
(Hoffmann, et al., 2009). However, there are difficulties that may arise in handling pet animals
during running affecting the safety of the runner or the pet. This is addressed in a recent study
that observes any psychological benefits of virtual pet assisted activities in VR on mental
wellbeing. (Nakajima, et al., 2020). The study concluded that there are benefits observed
through virtual assisted activity (VAA) but these benefits were better in open scenery virtual
environments than closed scenery environments.
Based in this particular insight, I lay greater importance on AR environments compared to VR
since AR can be set in real-world environments taking greater advantage of interaction with the
virtual companion and are much better suited for running related activities.

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6.3 Use cases
As a beginner, for someone using the running platform for managing their symptoms of MDD,
the use cases can be divided into two key sections. (1) New users (2) Using for 2-3 weeks.
The progression is very gradual, and it is important that the user begins by simply exploring the
environment and understanding the visual elements without the need to begin the running.
The user gets rewarded with a companion after completing the first one km of exploration. This
companion can now act as a navigational partner to begin the initial runs. Every companion has
a range. A companion with a 50 m range will catch the avatar for you once you are within 50 m
of the avatar you are chasing.

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USE CASE 1 (New user, currently not a runner)
1

2

User begins exploring the AR environment

3

Sees paw prints while exploring

4

Sees the details of the run and avatar

5

Double tap on the print to start the run

6

1st run, no minimum pace needed, follow
the prints

Approach the avatar to capture it

7

Congratulations! You unlocked your 1st companion

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USE CASE 2 (Using for 2-3 weeks, running with a companion)
1

2

Start the run with the companion

Or use a map to navigate without the companion

3

4

Faster and more distant avatars appear over time

The companion leads you to the next avatar

5

6

Companion approaches closer to avatar

Companion catches the avatar for you

7

New companion added

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6.4 Design Specifications
Environments
Since the objective is to replicate a scenario of chasing a moving avatar along with a
requirement for the user to be in an open environment, VR is not proposed to be the best
possible option. Additionally, VR (Virtual reality) would also restrict the movement aspect of the
running platform. AR (Augmented reality) on the other hand allows us to incorporate minor
visual elements into an existing environment without making it excessively information heavy
for the user. The speculation here is that the eyewear necessary for interacting with AR is
accessible and in an ergonomically manageable form like glasses. Glasses are potentially not a
hinderance in running experience since people already run with sunglasses in many instances.
Elements in the environment
The primary intention while proposing the design of these elements in the AR interface is to
make sure they are visually simple to avoid any interference with the real-world environment.
The visual elements are there to assist during the activity and make running more intuitive and
the intention is to allow the user to appreciate the real environment and not the visual
interface. Hence over time as one progresses in using this AR application, they can choose to
disable certain features like heart rate (HR) if they feel they have developed an intuitive sense
for knowing the current HR and a visual for that is no longer necessary. The intention is to have
visually conveyed information and not visually appealing aesthetics, so the user doesn’t end up
relying on these visuals every time they need to run. The visuals are preferred to be simple and
straightforward.
The user goes through a tutorial when they sign into the AR service explaining the role of each
visual element in the interface.
Additionally, the changes in visual elements that the user has to monitor during the run must
be visible in their peripheral vision so the user doesn’t have to focus extensively towards these
visuals allowing them to pay more attention to the surrounding environment.

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i) Virtual avatar to chase
Like Pokémon GO, where users use AR through their smartphone cameras to
physically navigate their real-world environments and catch different avatars in
various locations, the user in the AR environment in my proposed application has
avatars that are available to catch but not through smartphones, instead through an
eyewear-based AR device that allows them to see this virtual environment.
However, the locations of different avatars don’t appear in the AR interface for the
user until they start exploring the virtual AR environment. As the user progresses in
difficulty, more challenging avatars start to appear on the map. The pace at which
the avatar moves away from the user is inversely related to the user’s pace or
duration of run.

ii) Running companion
The avatar that the user catches can be used as a running companion for the next
run. The companion can serve a purpose like navigating the run towards catching
another avatar, act as a pacer or simply be a companion to run with. Companions
have attributes like range and pace. A companion with range of 50 m will catch the
avatar for the user once they are within 50 m of the avatar they are chasing.

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iii) Visualising the metrics
A progress bar in this AR interface is the key indicative of the user’s movement in the
real world. New routes and corresponding avatars become visible only after the bar
is filled. The rate at which the bar fills is synchronous to how close the user’s output
is to the 17.5 kcal / kg / week requirement. However, this EE (energy expenditure)
requirement can still be high for someone who is just beginning the exercise
process. So, the bar can be predefined to fill about four times before the EE
requirement is met. If the user is expected to have a 400 kcal EE, the bar can fill after
expenditure of every 100kcal.
To measure this EE output of a person, the information to be monitored is ;
(1) approx. calorie usage (2) body weight (3) weekly running data.
If we take an example of an existing running service like Samsung health, these three
aspects are already being recorded but not used together to generate any specific
cohesive data. Hence when designing for someone running to manage symptoms of
MDD, these can be used to visualise the EE range that the person is recommended
to follow to see progress in recovery from MDD.

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Another key piece of visual information is displaying the heart rate (HR) of the
runner. Since the existing research suggests that a steady state exercise in the
aerobic HR zone indicates the maximum amount of benefit in terms of reducing
symptoms of MDD (Shulkin J., 2016). Hence the users must preferably try to stay in
the aerobic HR zone (136 – 154 bpm).

Recommended to run in aerobic HR zone

One method to visualise the HR for the user in the AR interface while they are
running is to have the zones illustrated in the form of a bar with a pointer indicating
the user’s current HR while they are running, instead of displaying the HR
numerically. The user is encouraged to keep the pointer in the center of the bar
indicating that they are running in the aerobic HR zone (135-153 bpm).

Since for the purpose of using this application in AR, the user essentially has to know
‘if’ they are in the right HR zone, more than which HR zone they are in, we can
eliminate the extra columns representing different HR zone and have just three
columns representing the aerobic zone and anything above or below the aerobic HR
zone. The middle column represents the recommended HR zone which turns green
when the pointer is in that zone.

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However, we are still dealing with two elements in the HR visualisation which is the
bar and the pointer. Also, a bar might indicate progress, where reaching to one end
is a sign of success but here the user is trying to stay in the middle. Additionally, we
are visualising the EE in the form of a progress bar that fills up. The presence of two
similar looking elements that work in different ways would cause interference in the
user’s mind.
Hence, an alternative visualisation would be to indicate the HR using icons telling the
user to increase, decrease or stay in the current HR.

The three icons are not visible simultaneously in the AR interface but instead appear
depending upon the user’s current HR during the run.

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iv) Navigation
Each avatar to catch would have their respective running routes that the user is
encouraged to follow. Once the progress bar fills up, any available routes within 1
km radius to the user’s current location are unlocked. The routes are predefined
within a city. Each route has varied levels of difficulty depending upon terrain,
elevation and distance. Routes with higher difficulty lead to avatars that are
comparatively rare to find.

Navigation on these routes is done with the assistance of virtual directional cues in
the form of footprints. I decided to have footprints instead of arrows to guide the
user since footprints offer a greater sense that the person is trying to chase an
avatar that lives in this virtual AR world. A minor detail to make chasing more
intuitive instead of it feeling like a task. The footprints appear on the route that one
is running on and also to indicate any available route in the city.

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A compass is present in the AR interface which along with the footprints, offers a
general idea of the location of the avatar with respect to the user’s current position.
I choose to have a compass instead of a map since a compass encourages the user to
explore the surrounding and be engaged with the activity since the user is not
exactly aware of the avatar’s location. Whereas while using a map, nothing is
stopping the user to simply take a bus to reach the location. The goal is exploration
and not just reaching a specific spot.

In this instance, the avatar is roughly north-west to the user’s current position and
the direction they are facing. The point of intersection is the where the user is
currently situated.
An initial inclination was to keep the compass circular but that ends up looking like a
bullseye in the interface and therefore can cause some confusion to the user.

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23

24

AR interface with companion chasing an avatar

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6.5 Design Outcomes
Considering the ongoing development of AR technology in the next few years, an integral
component of the application yet to be explored extensively in my thesis is the user experience
of mixed reality. Understanding how the new user adapt to a new visual and spatial experience
on top of their existing knowledge. E.g., When I first experimented with Gravity Sketch which is
a VR based sketching tool that allows you to draw in 3-dimensional space, there was
interreference with my existing knowledge about sketching since I have never drawn in 3D
space ever. So, I knew how to draw a 3D object on a 2D paper, but it was harder for me to draw
the same 3D object in a 3D environment.
Similarly shifting from AR in smartphones to AR in eyewear alters the experience in aspects like
change in visual orientation from portrait in smartphones, to landscape in any speculated
eyewear.
User safety while running5 is another a major aspect to be taken into account.

5

Road safety at pedestrian ‘crossings’ is another safety concern that this thesis proposal raises. I believe that
understanding city rules regarding road safety and merging them with AR design in future running applications is
another topic to be researched entirely, which the scope of this thesis doesn’t fully address.

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6.6 Implication for designers
This thesis primarily offers insight based on personal experiences and existing research on
depression in the field of neuroscience that can be kept into consideration while designing AR
based assistance tools for individuals with mild-moderate MDD prescribed exercise treatments.
The problem space can be visualised6 based on the findings that,
i.
MDD leads to drop in motivation to generate physical movement in the affected
individuals.
ii.
Movement in the form of aerobic training can alleviate symptoms of depression.

Motivation

generates
generates

Movement

reduces

MDD

reduces

Based on my understanding of MDD and running through working on this thesis, I see
movement and motivation as codependent factors when viewing depression from the
orientation of exercise treatments. Implying that the absence of motivation in some cases can
be compensated by generating movement. Therefore, when designing for individuals with MDD
in an AR environment, generating movement will be the fundamental aspect around which the
application is designed.
Another key factor for the proposition of an AR based application is the responsiveness that
individuals with MDD have been researched to show towards visual coherence tasks according
to the research by C. Remmers in 2016. This prompted me to use visual cues as a primary mode
of communication in AR over text-based or audible information. But I would highlight that my
proposition encourages focus on visuals and not visual appeal.
The reason being that aesthetic visual experiences might not stimulate individuals with MDD as
they would with someone not affected with MDD, since a key characteristic of MDD in many
cases is presence of Anhedonia, which is the inability of an individual to experience pleasure
(Gorwood., 2008). I won’t deny the possible presence of any positive effects of having an
aesthetically pleasing visual over a rather dull one, however, I would prioritise having visually
conveyed information, like displaying numerical data visually, over aesthetical visual interfaces
and animations.

6

Visualisation based solely on the exercise treatment aspect of MDD. The diagram does not include the sociocultural, genetic and environmental factors.

27

Also from a visual design perspective, it would be my preference to avoid hyper realistic virtual
components since they can create visual interference with real world components. E.g., a real
squirrel and a virtual squirrel.
6.7 Scope and Limitations
The end goal of the research is to cultivate a habit of running in individuals working towards
treating mild-moderate MDD. The visual cues that guide the user into the earlier explorations
into the AR medium are a method of generating the initial push for someone working to
manage symptoms of mild/moderate MDD. Since one of the key motivators for someone to
continue an activity is the feedback from doing that activity. The process gains some
momentum after around 12 weeks of running which is the approximate time for the formation
of new neurons in adult humans (Déry et al., 2013).
Additionally, viewing running through a lens of play instead of competition generates some
level of curiosity towards understanding the reason behind the presence of this movement
pattern and sheds light on various cultures like the Tarahumara tribe of Copper Canyons in
Mexico, that have had running as an integral part of their lives for many generations.
One of the key limitations of this proposition is that it demands the presence of a certain level
of infrastructure to make running in an AR environment a safe option. I can envision attempts
to implement this platform in a runner friendly city like Vancouver, however, the requirements
would be entirely different if I have to consider my hometown (Jalandhar) in India. Apart from
the reasons discussed earlier like safe infrastructure for runners and presence of different
terrains that makes running in Vancouver less monotonous, Jalandhar has a higher average
summer temperature (~32°C) compared to Vancouver (~23°C) which also impacts people’s
desire to run especially during summer.
Another limitation is the accessibility of technology necessary for the AR interaction and for it
to be an ergonomically comfortable option.
Hence even though through this body of work I am trying to address a broad issue of clinical
depression, I am addressing a thin fraction of individuals in the entire spectrum of people with
different levels of severity and levels of accessibility to existing services and infrastructures.

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7. Analysis and Discussion
In the process of designing for a complicated social and psychological subject like clinical
depression that has research in multiple domains of knowledge, having my personal experience
as a guiding factor allowed me to target specific research subjects, like role of visualisation of
scenarios during running and potential benefit of companionship as a psychological support.
Additionally, I could gain some crucial insights through my own running practice. E.g., when
running with a group, I was always able run much further without needing to stop often,
however, running alone was much more effective in reliving symptoms of depression even
though I was covering lesser distance.
This offered a valuable insight that even though running was effective in managing my
symptoms, the benefits of how I run (alone) triumphed the benefits how much I run. Hence
having a socially connected model which in my own experience allowed me to run greater
distances, was not my preference when designing for individuals with diagnosed moderate
MDD.7 I am not sure if this would be considered as an appropriate research method but as a
learning experience it orients me towards researching the importance of designers’ own
experiences in the complete process of design. Consequently, it also explains the importance of
existing design methods like interviews and empathy mapping in allowing designers to not
design purely on the basis of ‘observed’ numerical data like having excessive focus on distance
covered instead of quality of the run.
Lastly, my fundamental intention of writing this thesis is the thought that back in 2017 when I
was working on my own recovery from moderate MDD, if I had stumbled upon this piece of
writing, it would have offered me valuable assistance and possibly reduced my recovery time to
almost half. I kept this thesis very factual and to-the-point from the beginning because I knew
that my 2017 self would have appreciated a more direct approach towards giving a solution
space. A motivational narrative8 would have pushed me then if I had the ability to feel
motivated in the first place.

7

On the contrary, a socially connected model like Strava might prove to be more successful with people not
diagnosed with MDD.
8
However, knowing or reading about someone’s own journey through the issue did offere a sense that the
problem is fixable, and I highly respect and acknowledge the work people put when recovering from the state of
depression.

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References
Beetz, Andrea, et al. “Psychosocial and Psychophysiological Effects of Human-Animal Interactions: The
Possible Role of Oxytocin.” Frontiers in Psychology, vol. 3, 2012,
https://doi.org/10.3389/fpsyg.2012.00234.
Bramble, D. M., & Lieberman, D. E. (2004). Endurance running and the evolution of Homo. Nature,
432(7015), 345–352. https://doi.org/10.1038/nature03052
DataFace, T. L. (2020, November 24). Case Study: Why We Run. The DataFace.
https://thedataface.com/case-study/strava-why-we-run
Déry, N., Pilgrim, M., Gibala, M., Gillen, J., Wojtowicz, J. M., MacQueen, G., & Becker, S. (2013). Adult
hippocampal neurogenesis reduces memory interference in humans: opposing effects of aerobic
exercise and depression. Frontiers in Neuroscience, 7. https://doi.org/10.3389/fnins.2013.00066
Dunn AL, Trivedi MH, Kampert JB, Clark CG, Chambliss HO. Exercise treatment for depression: efficacy
and dose response. Am J Prev Med. 2005 Jan;28(1):1-8. https://doi.org/10.1016/j.amepre.2004.09.003
PMID: 15626549.
Gorwood, P. “Neurobiological Mechanisms of Anhedonia.” Dialogues in Clinical Neuroscience, vol. 10,
no. 3, 2008, pp. 291–299., https://doi.org/10.31887/dcns.2008.10.3/pgorwood.
“Home.” Samsung Electronics America, https://www.samsung.com/us/support/owners/app/samsunghealth.
Hoffmann, Andreas O.M., et al. “Dog-Assisted Intervention Significantly Reduces Anxiety in Hospitalized
Patients with Major Depression.” European Journal of Integrative Medicine, vol. 1, no. 3, 2009, pp. 145–
148., https://doi.org/10.1016/j.eujim.2009.08.002.
Marquet, O., Alberico, C., Adlakha, D., & Hipp, J. A. (2017). Examining Motivations to Play Pokémon GO
and Their Influence on Perceived Outcomes and Physical Activity. JMIR Serious Games, 5(4), e21.
https://doi.org/10.2196/games.8048
McDougall, C. (2011). Born to Run. Adfo Books
Nakajima, Kenta, and Mihoko Niitsuma. “Effects of Space and Scenery on Virtual Pet-Assisted Activity.”
Proceedings of the 8th International Conference on Human-Agent Interaction, 2020,
https://doi.org/10.1145/3406499.3415083.
“Peripheral Vision.” Peripheral Vision - an Overview | ScienceDirect Topics,
https://www.sciencedirect.com/topics/computer-science/peripheral-vision.
Pokémon Go, https://pokemongolive.com/en/.

30

Remmers, C., & Michalak, J. (2016). Losing Gut Feelings? Intuition in Depression. Frontiers in Psychology,
07. https://doi.org/10.3389/fpsyg.2016.01291
Schulkin, J. (2016). Evolutionary Basis of Human Running and Its Impact on Neural Function. Frontiers in
Systems Neuroscience, 10. https://doi.org/10.3389/fnsys.2016.00059
“The Couch to 5K in 9 Weeks Running Program.” Couch to 5k - C25K Running Program,
http://www.c25k.com/.
“What's New.” Strava, https://www.strava.com/whats-new.
“3D Design and Modelling Software.” Gravity Sketch, 2 Dec. 2021, https://www.gravitysketch.com/.

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