NIGHTMARE RUNNER: A PERSONALIZED AVATAR

AND PHYSICAL ACTIVITY GAME

A Thesis Presented to

the Faculty of the Department of Computer Science

University of Houston

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

By

Madhur Thangadurai Rajendran

May 2016 NIGHTMARE RUNNER: A PERSONALIZED AVATAR

AND PHYSICAL ACTIVITY GAME

Madhur Thangadurai Rajendran

APPROVED:

Dr. Zhigang Deng, Chairman Dept. of Computer Science

Dr. Weidong Shi Dept. of Computer Science

Dr. Daniel O’Connor Dept. of Health and Human Performance

Dean, College of Natural Sciences and Mathematics

ii Acknowledgements

I would like express my thanks to my parents, Mr. Rajendran Thangadurai & Mrs.

Bagya Latha Rajendran, and my sister, Ms. Mahitha Rajendran for motivating me throughout the entire process. I am truly grateful for their unwavering support and patience.

I would like to thank my twin, Mayur, for his contribution and support. With- out him I would be incomplete. I would also like to thank my brothers, Aditya,

Vishwanath, and Shivaram, for always being there for me.

I would also like to extend my heartfelt gratitude to Dr Zhigang Deng, who served as my advisor & committee chair and guided me throughout the project. I am also grateful to Dr. Weidong Shi, and Dr. Daniel O’Connor for being on my committee, and for their valuable insights and suggestions for this project.

I am grateful to the lecturers and professors of the Department of Computer

Science, especially Dr. Victoria Hilford, who enlightened me about the software development process. I would also like to thank my friends and colleagues at the

University of Houston for their encouragement and support which made my studies here a truly enjoyable experience.

“Be well, do good work, and keep in touch.”

iii NIGHTMARE RUNNER: A PERSONALIZED AVATAR AND PHYSICAL ACTIVITY GAME

An Abstract of a Thesis Presented to the Faculty of the Department of Computer Science University of Houston

In Partial Fulfillment of the Requirements for the Degree Master of Science

By Madhur Thangadurai Rajendran May 2016

iv Abstract

In this thesis, a novel method to calculate energy expenditure of subjects using the Microsoft Kinect is presented. There are two main types of methods used in calorime- try, direct and indirect. Direct calorimetry involves the measurement of actual heat transfer of the subject, which is infeasible in most situations. Indirect calorimetry, however, involves measuring secondary variables, like oxygen consumption, and using those measurements to calculate energy expenditure. The method presented is an indirect calorimetry method that uses basic physics laws of work and energy to cal- culate the energy expenditure of a body by continuously tracking the body through the Microsoft Kinect. A process of 3D scanning a person in order to use them as avatars in a game was developed and the feasibility and benefits of using such personalized avatars in game was tested. Lastly, a physical activity game that serves as a wrapper for both the proposed energy expenditure method, and the personalized avatar was developed.

v Contents

1 Introduction 1 1.1 Problem Statement ...... 1 1.2 Contribution ...... 2 1.3 Outline ...... 3

2 Background 4 2.1 Calorimetry ...... 4 2.1.1 Direct Calorimetry ...... 4 2.1.2 Indirect Calorimetry ...... 5 2.2 3D Scanning ...... 6 2.3 Mesh Processing ...... 7 2.4 Exercise Game ...... 7 2.4.1 ...... 8

3 Energy Expenditure Algorithm 10 3.1 Assumptions ...... 13

4 Scanning & Mesh Processing 14

5 Exercise Game 19 5.1 Development ...... 21

vi 5.1.1 Hardware Requirements ...... 21 5.1.2 Software Requirements ...... 22 5.1.3 Algorithm Integration ...... 23 5.2 Game ...... 24 5.2.1 Personalized Avatar ...... 25 5.2.2 Environment ...... 25 5.2.3 Story ...... 27 5.2.4 Cutscenes ...... 28 5.2.5 Goals ...... 33 5.2.6 Game Menus ...... 34 5.3 Gameplay ...... 38 5.3.1 Dream Energy ...... 38 5.3.2 Pick Ups ...... 39 5.3.3 Controls ...... 39

6 Results 43 6.1 Energy Expenditure Algorithm ...... 43 6.1.1 Preliminary Validation ...... 44 6.1.2 Subject Testing ...... 47 6.2 Game ...... 53

7 Conclusion 55 7.1 Future Work ...... 56 7.1.1 Algorithm ...... 56 7.1.2 Exercise Game ...... 57 7.2 Contribution ...... 57

Appendices 58

vii A Calorific Data of Child Testing 59 A.1 Average Calories Burned Per Minute ...... 59 A.2 Calories Burned per Minute ...... 61

B Calorific Data of Adult Testing 103 B.1 Calories Burned Per Interval ...... 103 B.2 Cumulative Calories Burned ...... 109

Bibliography 115

viii List of Figures

2.1 Occipital’s Structure Sensor ...... 6 2.2 Exercise Game: Nightmare Runner Menu ...... 8 2.3 Unity Game Engine ...... 9

3.1 A sample 3D model used for Algorithm ...... 11

4.1 An image of the structure sensor ...... 14 4.2 A subject being scanned by the structure sensor and ItSeez3D app . . 15 4.3 A sample model after rigging and animating ...... 16 4.4 A sample subject that has been split in Maya 2016 ...... 18

5.1 An Endless Runner Game: 2 [3] ...... 20 5.2 The Microsoft Kinect v2 ...... 22 5.3 The Mixamo Website used for Rigging ...... 23 5.4 The Floating Island Environment ...... 26 5.5 The monster in the game ...... 27 5.6 The game story screenshot ...... 28 5.7 Introduction: The player’s avatar going to sleep ...... 29 5.8 Introduction: The player’s avatar exploring the dream ...... 30 5.9 Introduction: The player’s avatar discovering the cave ...... 30 5.10 Victory: The player running away from the Nightmare Monster . . . 31

ix 5.11 Victory: The player facing their Nightmare ...... 32 5.12 Victory: The player defeating the Nightmare Monster ...... 32 5.13 Victory: The player escaping the nightmare world ...... 33 5.14 The final screen when the player beats the game ...... 34 5.15 The score menu ...... 35 5.16 The Difficulty Select screen ...... 36 5.17 The Game Over screen ...... 37 5.18 The Dream Energy Bar ...... 38 5.19 The Pick Ups used in the game ...... 39 5.20 Gameplay: Run ...... 40 5.21 Gameplay: Limp ...... 41 5.22 Gameplay: Slide ...... 41 5.23 Gameplay: Jump ...... 42

6.1 Subject 1: Calories burned per interval ...... 45 6.2 Subject 2: Calories burned per interval ...... 45 6.3 Subject 2: Calories burned over time ...... 46 6.4 Subject 2: Calories burned over time ...... 47 6.5 Average calories burned per minute by subject ...... 48 6.6 Subject 1: Comparison with Just Dance 4 ...... 51 6.7 Subject 2: Comparison with Just Dance 4 ...... 53

x List of Tables

6.1 Subject 1 Energy Expenditure Estimation Comparison ...... 50 6.2 Subject 2 Energy Expenditure Estimation Comparison ...... 52

xi Chapter 1

Introduction

1.1 Problem Statement

The standard procedure for calculating and estimating the energy expenditure of the human body is to use VO2 machines while the subject is performing the activity. However, this is bulky, requiring the subject to wear a mask that is connected to the machine, in order to be able to measure oxygen consumption. Other sensors that use accelerometers to measure activity were also used, but they’re fixed at one location on the body. While they do give a generalized estimate of the energy expenditure, the VO2 method is generally regarded as the most accurate method for calculating energy expenditure. Therefore the major drawbacks to the current methods are that they either require bulky external devices, or they aren’t as accurate due to mostly being local to a specific area of the body.

1 With current available technology, 3D graphics have become very popular. The focus of graphics technology has been the ability to create, manipulate, and animate high definition 3D models, as can be seen by recent movies and games. Many 3D scanners have been developed, allowing users to capture objects, or even people around them as a 3D file that can be printed out using a 3D printer. These models can even be skinned and rigged with a skeleton, allowing animation, and put into games. Using a person’s personalized model in a game has improved playability by improving immersion and enjoyment [7].

1.2 Contribution

In this thesis, three main contributions were presented. First, a new method of calculating the energy expenditure of a human body using the Microsoft Kinect was presented.

Secondly, a workflow was created using existing software and certain hardware systems to scan a human subject, and to create a 3D mesh that modeled the subject.

This pipeline significantly decreased the time required for scanning, mesh creation, mesh processing, and game avatar creation from the scanned model.

Lastly, an exercise game was created that uses the Microsoft Kinect as an input controller. The avatar created from the scanned model was used as the main game character, so subjects could take control of an avatar that not only represented them, but was also visually similar to them. We kept track of the energy expenditure of the subject using this method while the subject was playing the game.

2 1.3 Outline

The thesis is organized according to the following outline. In Chapter 2, some back- ground of the systems and domains used in the thesis is presented. The concepts and techniques used in the later chapters are described. In Chapter 3, the new Energy

Expenditure Algorithm. The hardware required is discussed, and the background behind the development of the algorithm is explained. In Chapter 4, the hardware and software requirements of the 3D scanning and Mesh Processing method are de- scribed. In Chapter 5, the exercise game that was created to serve as a wrapper for the algorithm, the scanned mesh and avatar is described. In Chapter 6, the results from having participants come in to play the game that was developed is presented.

The proposed algorithm is compared against the medical standard accelerometer. In the final chapter, conclusions are provided, and the limitations and future work of the project are discussed.

3 Chapter 2

Background

2.1 Calorimetry

Calorimetry is defined as the science or act of measuring changes in state variables of a body for the process of deriving heat transfer associated with changes to its state.

This is important in relation to this thesis, because we use calorimetry to evaluate the energy expenditure of a human body, i.e. the amount of calories burned by the human subject.

2.1.1 Direct Calorimetry

The method of direct calorimetry is to directly measure the heat transfer of the entire body. While this method will give you the most accurate calorific value for the time period as shown by Consolazio et al. [1], it is also usually not viable because of high

4 cost, technical difficulty, and limitations placed on the subjects mobility [4], i.e the body has to be enclosed in the calorimeter, and should be free from external con- ditions. Since human subjects cannot be isolated from external conditions, indirect calorimetry methods must be used to determine the energy expenditure.

2.1.2 Indirect Calorimetry

In indirect calorimetry, a secondary variable linked to heat transfer is measured. In most cases, oxygen consumption, and carbon dioxide generation was used for this, being accepted as industry and medical standard [8]. This methodology is relatively broad and has grown to cover any methods of energy expenditure calculation that does not involve direct measurement of heat transfer of a body. Included under indirect calorimetry is physics based calorimetry. In this method, a set of established physics equations was used to estimate and calculate the amount of energy expended by a human body in a given amount of time. The Microsoft Kinect was used to track the parameters needed for the method. While other models using the Kinect have been proposed, for example Liu et al. [5] presented a model for measuring the energy expenditure of dancers by calculating force required to overcome gravity, their applicability to exercise games has not been established.

5 2.2 3D Scanning

There are many 3D scanners available today. For this thesis, the Structure Sensor, by Occiptial, Inc was used. The app, ItSeez3D was the software behind the actual mesh capture. The ItSeez3D app works in conjunction with the Structure Sensor, to produce a 3D scanned .obj file. This file is then processed and used in the algorithm as well as to create the player’s avatar in the game. The scanner is built like the MS

Kinect, and includes a set of two cameras; a normal camera, and a depth camera.

Figure 2.1: Occipital’s Structure Sensor

6 2.3 Mesh Processing

In the Mesh Processing step, the mesh was modified and fixed in Autodesk’s Maya

2016, in case there were any errors that occured during the scanning process. The

file was then saved as two separate copies, in order to process the mesh for 2 different purposes. The first file was used for the algorithm. The file was saved in a more convenient format, and the mesh was split into separate body parts. For the second

file, the size was increased, and it was uploaded to Mixamo, part of Adobe 3D works, for rigging. A game avatar with a skeleton ready to be animated was the result.

Once this was done, the body parts and the avatar were uploaded into the game for the player to use and control.

2.4 Exercise Game

As Michael D. Gallagher, president and CEO of Entertainment Software Association, said, “Video games are ingrained in our culture.” Video games are the most preferred sedentary activity of children, bypassing reading and watching TV. In our digital age, games provide kids an escape into fantasy, and a way of relieving stress. Encouraging kids to perform moderate physical activity while playing games will help promote a healthier lifestyle. Active games provide kids the same benefits of light to moderate exercise in the same time period [9][2].

The exercise game that was created is an endless-runner game. In these type of games, the player controls a character that keeps moving forward, collecting coins

7 Figure 2.2: Exercise Game: Nightmare Runner Menu and powerups as they progress. The goal of the game is to see how far the player can move through the game. This type of game was chosen since there is no clear goal, the game can theoretically last forever, and levels of variable length could be created.

Since the game is designed for exercise, players are able to select the amount of play time for the game. Since there is no limit for the amount of time they can play, this can be any variable number that suits the player’s needs.

2.4.1 Unity Game Engine

The game was developed using the Unity Game Engine. Unity is a flexible and powerful development platform for creating multiplatform 3D and 2D games and interactive experiences. It offers many features, and is very user-friendly, with a moderate learning curve.

8 Unity Engine has been released on a free license for personal and research projects, and serves as a good platform for integrating all the components required. A Software

Development Kit is available for MS Kinect that works on Unity, and was developed by Rumen Filkov. This is used to keep track of the user’s movement for measuring physical activity, as well as to read the inputs from the player’s actions. Unity supports many development languages, but C# was the development language used.

Also, art assets from the Unity Asset Store were used to build this game.

Figure 2.3: Unity Game Engine

9 Chapter 3

Energy Expenditure Algorithm

The energy expenditure algorithm proposed can be personalized for each person, and thus requires a 3D scanned model of the person. Once built, the model is split into

12 different body parts based on the joint information provided by the Microsoft

Kinect skeleton tracking system.

Each part contains one of the joints tracked by the Kinect. The next step is to determine the approximate mass of each body part, using the total 3D volume and weight of the subject. The total 3D volume of the scanned mesh was calculated by

first computing the volumes of each elementary tetrahedron and then summing up all the individual values for the entire mesh, using the algorithm developed by Zheng and Chen [11].

10 (a) Sample whole body model (b) Model divided into parts

Figure 3.1: A sample 3D model used for Algorithm

Assuming Wtotal is the user-provided weight, Vtotal denotes the computed total

3D volume of the mesh, and Vi denotes the 3D volume of the i-th body part, then the approximate mass of the i-th body part, mi can be computed as follows (assume the mass density of the human body is even).

mi = Wtotal × Vi/Vtotal (3.1)

To compute the energy expenditure of a subject in a short period of time (∆T ), the following two steps are required: First, the amount of work done in this period was computed, measured in Joules; and then, the total work done was converted into energy expenditure in terms of Kilo-Calories, the metric used in health and fitness

11 applications, based on the well-known conversion formula: 1 kcal = 4.184 kJ.

The computation of work done within ∆T (time period) consists of two parts: the first part is the energy required to overcome the gravity, and the second part is the amount of work done due to the displacement of the body part in the Cartesian coordinate system. Specifically, the total displacements of the i-th body part was computed as the root of the sum of the squared displacements in all three orthogonal directional axes, as follows:

q 2 2 2 ∆di = (∆xi + ∆yi + ∆zi ) (3.2)

where ∆xi denotes the displacement of the i-th body part in the X direction, and

∆yi and ∆zi are defined analogously. Also, the magnitude of acceleration of the i-th

xyz body part, ai is computed using a similar formula.

q xyz x 2 y 2 z 2 ai = (|ai | + |ai | + |ai | ) (3.3)

x y z Here, ai , ai , ai represent the acceleration of the i-th body part in X, Y and Z di- rections, respectively, which easily can be computed from the MS Kinect skeleton tracking module. The work done of the i-th body part in ∆T , κi, is computed using the following equations:

xyz g κi = κi + κi (3.4)

xyz xyz κi = mi × ai × ∆di (3.5)

g g κi = mi × ai × |∆yi| (3.6)

xyz In the above equations, κi denotes the part of the work done to cause the motion

g (displacement) in three-dimensional space, and κi denotes the part of the work done

12 to overcome gravity (assume the Y-axis is the direction of gravity in the Cartesian coordinate system).

Finally, the total work done by the whole human body is the summation of the work done by each individual body part. Over a number of fixed time intervals, the values of the work done are summed to obtain the total work done in time T.

3.1 Assumptions

In our algorithm, the following assumptions are made. Firstly, that the human body has uniform density, and this is independent of age. It is also assumed that every player has the same body efficiency index for burning calories. Lastly, since the algorithm is designed to be used in personalized systems like games, only weight was asked from the player for the algorithm, even though energy expenditure is dependant on other factors as well.

13 Chapter 4

Scanning & Mesh Processing

For scanning, Occipital, Inc’s Structure Sensor is used. The Structure Sensor is a 3D scanner, made up of two cameras. It has a depth camera, that captures the mesh of the object in 3D space, and a regular camera to capture images of the object, which are then processed into a texture and applied to the model.

Figure 4.1: The Structure Sensor by Occipital, Inc.

14 A scan of the player was taken using the iPad app, ItSeez3D. ItSeez3D provided the software that makes use of the Structure Sensor to take the 3D scan of the subject.

It first creates a bounding box around the subject. The depth camera then plots the mesh outline of the subject in the 3D space of the bounding box. At the same time, the regular camera takes snapshots of the subject in order to create the final texture of the model. The subject is captured as the device moves around them. Since the scanner is a camera, all angles that are otherwise not observable directly, like the top of the head have to be obtained. It should be noted that relatively uniform lighting is required for the scanning process. Once the model has been scanned fully, the scan is uploaded to the ItSeez3D server, where the mesh data and the texture data are combined to create the 3D model of the subject. Once the model is ready, it can be saved in different 3D formats. The OBJ format was chosen, because it fits well with the program pipeline.

Figure 4.2: A subject being scanned by the structure sensor and ItSeez3D app

15 Two copies of the model file were made. The first file was processed for use in the actual game, while the second file was processed for use in the personalized algorithm.

The first file, was imported into Maya 2016 by Autodesk and was opened. The size of the model was increased to be similar to the size of the game environment.

The model can be cleaned up a little, removing small faults in the 3D mesh. Once the mesh was cleaned up, it is re-saved into FBX format. The FBX format is used by all Autodesk products for 3D modeling and animation.

(a) Sample rigged model running (b) Sample rigged model jumping

Figure 4.3: A sample model after rigging and animating

16 The FBX file was uploaded into the website, Mixamo. Mixamo, by Adobe, pro- vided a free python script to attach a skeleton and rig a model that was uploaded to the site, which was used to rig the model. Once the model was rigged, animations were applied to it. Since all the skeletons are standardized, the animations can be re-targeted to any model from Mixamo. The rigged model was downloaded in FBX format and uploaded into the Unity Game Project. The model was inserted into all the scenes that required the model, namely the cutscenes and the actual gameplay levels.

In the case of the cutscenes, the set of animations was applied to the model , and the character controller was applied to the model in the game levels. After this, the game is built, and the subject’s High Quality 3D scanned model will be the main avatar in the game, and is the model that is shown on the cutscenes of the game.

The second file was used with the personalized energy expenditure algorithm.

First, the file was uploaded into Maya. Once it was uploaded, the number of poly- gons was reduced, since the original file was high quality with upwards of a million polygons. It was reduced to around 30,000 polygons. The algorithm is more opti- mized with a reduced model, and won’t take a long time to load in the game engine.

The whole body is saved as a separate FBX file. The body is split into 12 different parts, specifically the head, the shoulders, the two elbows, the two wrists, the spine, the hips, the two knees, and the two ankles. Each of these parts corresponds to a different part of the skeleton that the Kinect tracks. Each part is saved as a sepa- rate FBX file, and all the files are uploaded together into the Unity Game Project.

Each piece of the subject’s split mesh is attached into the corresponding joint on the

17 Kinect tracking skeleton. This way, when the subject moves the specific joint, the corresponding piece was also moving. Once all the pieces and the whole mesh are linked to the scripts that contain the algorithm, it will be personalized specifically for the player who’s 3D model was used.

Figure 4.4: A sample subject that has been split in Maya 2016

18 Chapter 5

Exercise Game

While building the exercise game, a few preliminary constraints were put in place.

First, the game had to involve some sort of physical activity. The activity of our game should be significant enough to burn the same amount of calories as moderately intensive exercise. Another constraint was that the game should be enjoyable to both boys and girls, and should be competitive enough to encourage them to burn more calories. The last constraint was that the game should last for at least 20 minutes.

Based on these preliminary constraints, an endless runner game was chosen to be made. An endless runner game can be programmed to be endless, with the game only reaching a conclusion when the player is tired or after a certain amount of time has passed. Endless runner games have proven to be popular among both genders, as seen by the popular game, Temple Run, created by Imangi Studios. Imangi Studios has reported that their endless runner game, designed to work on mobile devices, has reached over 1 billion downloads.

19 Figure 5.1: An Endless Runner Game: Temple Run 2 [3]

Also, choosing an endless runner game where the avatar has to jump, duck and slide to dodge obstacles in their path, provided an ideal opportunity for incorporating physical activity into the game. Since the game was designed to be used by common people, it is planned with limited space in mind. Therefore, any physical activity must be restricted to those that can be performed in place, and jumping, squatting,

20 and running in place provided the most physical activity, and required little empty space.

The Unity Game Engine was used as the platform to create the game, and was programmed in C#.

5.1 Development

The game went through many stages before it was finally ready for testing and release. In addition to the preliminary gameplay requirements, the hardware and software for our game had to be chosen. The game was developed for the Microsoft platform, since it made use of the Microsoft Kinect.

5.1.1 Hardware Requirements

For development, a computer with the following specifications was used: 32 GB

RAM, 1 TB HDD, and Nvidia Graphics. A lot of space was required for the de- velopment, because all the player’s 3D models had to be stored before and after processing. Occipital’s Structure Sensor was required for scanning.

21 Figure 5.2: The Microsoft Kinect v2

For the final game, a Windows computer with 4GB RAM, atleast 2 GB of free space, and Nvidia Graphics is required to play. In addition, a Microsoft Kinect v2 is needed as an input device to the game.The Kinect v2 will only work on the newer

USB 3.0 slots, and hence a USB 3.0 slot is required for the game to run.

5.1.2 Software Requirements

For development, a computer that runs the Windows Operating System was re- quired. In addition, Unity Game Engine by Unity, ItSeez3D, an app for the iPad, by ItSeez3D, Inc., Maya 2016 from Autodesk, and the website, Mixamo, part of the

Adobe Creative Suite are also required.

22 Figure 5.3: The Mixamo Website used for Rigging

The main development of the game was done on the Unity Game Engine. It-

Seez3D and Maya 2016 were used for 3D scanning and mesh processing purposes.

Maya is also used for model optimization before being uploaded to Mixamo for rig- ging and animation.

To play the game, a computer running Windows Operating System is required.

The game will be self contained, and will run on any Windows OS, as long as the hardware requirements are met.

5.1.3 Algorithm Integration

The algorithm was coded in C#. The Unity Game Engine makes it easy to integrate scripts into the game. It has its own compiler to compile the code, and create an executable of the game.

23 To integrate the algorithm with the game, scripts were written that identify each body part of the player’s mesh. Also a script that calculates the volume of any 3D mesh passed to it was written. The volume script was run on the list of the body parts, and the whole body mesh. Using the whole volume and part volume, the mass of each part was calculated. Scripts that keep track of the movement of each joint of the Kinect Skeleton were also written. Each joint is linked to the specific body part it corresponds to. This movement data was passed into the algorithm, which gave an energy expenditure output. This was displayed as calories burned by the player.

5.2 Game

During development of the game, the interests of our target demographic, children between the ages of 11 and 14, had to be kept in mind. Focus was placed on the story, the high quality avatar that players would control, the gameplay and cut-scenes that drove the story along. According to a study by Dr Thompson, of Baylor College, the children’s interests lie in good graphics, an engaging story, and challenging gameplay.

Eighty-five percent of the kids also felt that the character/avatar that they control in the game was important to them. That age group further felt that things that were overly childish like clowns, bright pastel colors, and silly jokes weren’t interesting and engaging enough.

24 5.2.1 Personalized Avatar

Just as the personalized avatar was used for the algorithm calculation, the person- alized avatar was used as the main character in the game. As has been shown in previous studies, the main avatar of the game can have psychological effects on the players of the game, especially games where the player takes direct control of the character [10]. I felt that the player himself or herself being the avatar in the game would increase immersion and motivation for reaching the win condition and beating the game.

5.2.2 Environment

The environment was designed, keeping in mind the interests of the target demo- graphic. The study by Dr Thompson had mentioned that the demographic didn’t want anything that was overtly childish, but the environment could not be too scary or realistic, in order to capture their childish imagination. I came up with a floating island theme, similar to that of Temple Run 2. However, the graphics were made a little cartoon like.

25 Figure 5.4: The Floating Island Environment

Our main antagonist is the nightmare monster. We used a high-quality monster model, since the kids wanted good graphics.

26 Figure 5.5: The monster in the game

5.2.3 Story

The story of the game is the driving factor behind the immersion of the game [6]. If the storyline isn’t entertaining, the game risks boring the player.

The basic story of the game, is that the player has a tiring day, and when it’s

finally time for them to sleep, they get transported to a dream world. While trying to find a way out of the dream world, they run into a monster of their nightmares.

27 Figure 5.6: The game story screenshot

They then have to run away from the monster, which is the actual part of the game they play. When they escape their nightmare, they are finally able to defeat the monster and leave dream world.

5.2.4 Cutscenes

There are two cutscenes in the game. The intro cutscene introduces the story to the player, and the final cutscene is the victory cutscene that is played until the player has achieved the goal and satisfied the victory condition.

The cutscenes were all created in Unity, using different camera perspectives and other art assets.

28 5.2.4.1 Introduction

The introduction cutscene opens up to a room where the player is getting ready for bed. The player yawns and gets into bed, tired. Almost as soon as they fall asleep, they get transported to the dream world. He/She is dropped into the dream world suddenly, falling from a great height to the ground below. Miraculously, the player is uninjured, and he/she gets up and decides to explore this dream world in order to

find a way out. On their journey, the player comes across a creepy, skull-shaped cave.

Figuring that checking inside is worth a shot, they go into the cave and accidentally awaken a nightmare monster that starts chasing them.

Figure 5.7: Introduction: The player’s avatar going to sleep

29 Figure 5.8: Introduction: The player’s avatar exploring the dream

Figure 5.9: Introduction: The player’s avatar discovering the cave

30 5.2.4.2 Victory

In the victory cutscene, the player is shown running away from the monster when they come across a large gap in the path, too large to jump over. Unsure of what to do, they turn to face their nightmare. Trapped between the monster and a leap of faith, the player gathers their courage and makes the jump. When the player actually makes the jump, they realize that they control their dreams, and they use up their remaining dream energy to fire magical energy at the nightmare, defeating it. After a quick celebration, the player comes upon a magical portal that teleports them out of the dream world.

Figure 5.10: Victory: The player running away from the Nightmare Monster

31 Figure 5.11: Victory: The player facing their Nightmare

Figure 5.12: Victory: The player defeating the Nightmare Monster

32 Figure 5.13: Victory: The player escaping the nightmare world

5.2.5 Goals

Although originally multiple game modes were planned to be included, only one game mode was created for the initial release of the game. In this game mode, the player has to keep his character running away from the nightmare monster for a

fixed time limit. 20 minutes was the base time, but the time is variable and can be changed. The goal was not to completely run out of Dream Energy during the

20 minutes of gameplay. Dream Energy was reduced when a player was unable to dodge an obstacle by jumping or squatting, or if they take a long rest. If the player’s character survived without running out of Dream Energy in the 20 minutes, then they achieved the goal of this particular game mode.

33 Throughout the game, the player tries to collect coins, and move as much as

possible, so their score increases. The score is dependent on the amount of time the

player is moving, their energy expenditure, and the items they pick up.

Figure 5.14: The final screen when the player beats the game

5.2.6 Game Menus

The game menus also had to be designed with the target demographic in mind. The menus had to be user-friendly, not overly childish, but still easy enough that a child should be able to understand it. I settled for a runic type menu system. This had dull, cool colors that were not quite childish, yet still hinted at the fantasy aspect of the game. A simple color scheme of red, green, and yellow was used for difficulty, because these colors are widely used, and are easily recognized.

34 Figure 5.15: The score menu

The score menu will be displayed while the player is actually playing the game, i.e, the running phase of the game. It’ll keep track of the player’s score, the number of coins they collected, the number of dream shards they collected, and the calories that they have burned. Presenting this information to the player will motivate the players, who are mainly kids, to keep moving.

35 Figure 5.16: The Difficulty Select screen

The difficulty select screen is displayed to the user before the running phase of the game starts. The difficulty was based on the probability of obstacles spawning, the amount of dream energy lost per collision, and the amount of dream energy recovered per dream shard collected.

36 Figure 5.17: The Game Over screen

The game over screen is displayed to the player once they reach the fail condition and lose the game. It gives them the stats of their run, and an opportunity to restart the game, or to change the difficulty level.

37 5.3 Gameplay

The game is designed to be an infinite runner. That means the basic gameplay part of the game is the avatar running and dodging obstacles that come in their way. In this game, the player is being chased by his nightmare, and they have to try to find a way to escape.

5.3.1 Dream Energy

Dream Energy was synonymous with health in most games. Instead of using the traditional losing condition in Infinite Runner games of two successive collisions,

I came up with a system of using Dream Energy to reach a fail condition. Dream

Energy is reduced when the player crashes into obstacles or is unable to keep moving.

If the player’s dream energy ever reaches 0, then their nightmare catches up to them, and the game ends.

Figure 5.18: The Dream Energy Bar

38 5.3.2 Pick Ups

There are two different types of pick-ups that are interspersed among the different obstacles. The first pickup is a coin. Coins serve to improve your score by a small amount, but otherwise has no effect. The second pickup is a dream shard. Dream shards are used to replenish your Dream Energy.

(a) Coins (b) Dream Shards

Figure 5.19: The Pick Ups used in the game

5.3.3 Controls

The controls for this game were entirely handled by the Microsoft Kinect v2. The player controls his avatar by performing the same action needed. If they would like their avatar to jump, they would have to jump, and if they wanted their avatar to slide, they would have to squat. While their avatar is running, they will also have to continuously run in place, or they will notice that their avatar starts limping, and they start to lose dream energy at a faster rate. As soon as they perform an action,

39 or start running again, their avatar comes out of the limping animation, and the dream energy loss is reduced.

Figure 5.20: Gameplay: Run

40 Figure 5.21: Gameplay: Limp

Figure 5.22: Gameplay: Slide

41 Figure 5.23: Gameplay: Jump

42 Chapter 6

Results

In this chapter, the results of the algorithm are presented. The algorithm performed according to expectations, albeit a little optimistic, and was similar to the preliminary validation performed.

6.1 Energy Expenditure Algorithm

The algorithm was tested in two stages. In the preliminary validation phase, a small number of participants tested our algorithm compared to two other methods. In the testing phase, 42 children between the ages of 12 and 14 were invited to play the game to test the algorithm.

43 6.1.1 Preliminary Validation

In the preliminary validation, the algorithm was compared against the iPhone app, iBurn, and the Xbox game, Just Dance 4, which uses the Kinect as an input device, similar to this game. Ideally, the data should be compared against the standard VO2 method, or a direct calorimetry method, but the use of these methods are constrained by the limited space and movement. No bulky machines could be used, in case they interfered with the Kinect’s tracking system.

Two participants were scanned for the validation phase. In order to keep the data consistent, the participant was tracked by all three methods at the same time.

In all three methods, the results were recorded every ten seconds, i.e., the interval was 10 seconds. It should be noted that the iBurn app could output data as integer values, whereas the Just Dance 4 and this algorithm can output data as float values.

Participants were asked to perform certain exercise moves that would find use in the game, including walking back and forth, jumping, and squatting. The first participant jumped in the first three intervals, walked in the second set of intervals, squatted in the next three intervals, and again walked in the last three intervals.

The second participant spent the first three intervals walking, the next three inter- vals jumping, the next three intervals again walking, and the final three intervals squatting.

44 Figure 6.1: Subject 1: Calories burned per interval

Figure 6.2: Subject 2: Calories burned per interval

45 This algorithm follows the Just Dance 4 game’s method more closely. The iBurn app gave a more optimistic value of the calories burned, and since it doesn’t present the values in floats, its precision was low.

Figure 6.3: Subject 2: Calories burned over time

46 Figure 6.4: Subject 2: Calories burned over time

This algorithm, and Just Dance 4 were able to track the entire skeleton of the player, while the iBurn app used the built in accelerometer of the iphone to calculate the average energy expenditure based on the location of the phone on the player’s body. For testing purposes the phone was placed in the front pants pocket.

6.1.2 Subject Testing

For the second phase of testing, 42 children between the ages of 12 and 14 were invited to test out the game. They were scanned and personalized photo realistic avatars were created for them, as well as a personalized energy expenditure algorithm.

The students consisted of different ages, genders, weights, and activeness. The full collection of calorific data for all participating children is given in the Appendix A.

47 An accelerometer was used to compare with our algorithm for the children. The data from the algorithm compared to that of the accelerometer is given in Figure 6.5.

Figure 6.5: Average calories burned per minute by subject

A constant was integrated into the algorithm to further refine the output against the accelerometer. Some of the subjects in our results were omitted due to technical errors that occurred during the testing phase, some went out of the Kinect’s field of view, including outliers who showed exceptional calorific values in one or the other of the methods.

The differences in the results of the two could be for many reasons. Only one accelerometer as available for testing, therefore could only be placed on one location of the body. It was placed on the hip of the child. At this location, the accelerometer

48 was not able to pick up separate movement of the child’s arms or legs. In addition, the game did promote exercise, it did place a limit on their available area of play.

They cannot move past the kinect’s range, or the game will stop reading them. The accelerometer was designed more for forward movement, whereas the children spent the majority of the game running in place.

In addition to the 42 children, two adult testers were used to play the game for the same duration as the children. The calorimetry data from our algorithm was compiled to compare with the calorific values of the Just Dance 4 game for the

Microsoft Kinect.

The data of the two adult subjects’ calorie expenditure with respect to the Just

Dance 4 game is presented in Table 6.1 and Figure 6.6 for Subject One, and Table

6.2 and Figure 6.7 for Subject Two. The full data of the two adult subjects is given in Appendix B.

49 Minute Game Algorithm

1 1.61 1.35

2 4.04 2.96

3 4.89 5.27

4 5.7 7.03

5 6.98 8.52

6 7.7 9.39

7 8.48 10.32

8 9.24 12.54

9 9.83 14.02

10 10.19 14.88

11 10.64 15.73

12 11.62 16.77

13 12.28 17.69

14 12.8 18.97

15 13.21 21.16

16 13.72 22.42

17 14.32 24.31

18 15.25 25.39

19 16.01 26.57

20 16.54 27.53

Table 6.1: Subject 1 Energy Expenditure Estimation Comparison

50 Figure 6.6: Subject 1: Comparison with Just Dance 4

51 Minute Game Algorithm

1 2.66 1.95

2 4.89 3.69

3 6.09 5.38

4 6.8 7.25

5 7.75 9.15

6 8.93 10.08

7 9.69 10.92

8 10.5 12.63

9 11.09 14.42

10 11.58 16.09

11 12.4 17.11

12 12.84 17.69

13 13.4 18.27

14 13.9 20.04

15 14.36 21.5

16 14.78 22.32

17 15.1 22.96

18 15.99 24.77

19 16.28 25.72

20 16.78 26.86

Table 6.2: Subject 2 Energy Expenditure Estimation Comparison

52 Figure 6.7: Subject 2: Comparison with Just Dance 4

As can be seen by the above figures, the algorithm is more optimistic than the

Just Dance game. The squats, in particular, generally produced higher energy output than the Just Dance 4 algorithm.

6.2 Game

Most of the kids who played the game enjoyed the story line. The personalized avatar was the most interesting point to the kids, as well as their parents. They truly enjoyed seeing themselves in the game. The children were motivated to keep playing the game, even when told they could take breaks, lending support to the hypothesis that active video games provide a viable replacement to exercise. Many

53 participants expressed interest in playing other games with a photorealistic avatar of themselves as the main playable character.

54 Chapter 7

Conclusion

This thesis presents a new and efficient approach to estimating energy expenditure of a human body when he or she is playing video games. This algorithm estimates energy expenditure using the Microsoft Kinect as a motion tracking device. This algorithm provided a more realistic estimation of calories burned than methods using the accelerometer of a phone to do energy expenditure estimation. The intervals where activity was more intense, showed a higher calorific value than those intervals with less intense activity.

A limitation of this method however, was the dependence on personalized avatars.

It requires another person other than the player to operate the device, in order to scan the player. Also, this algorithm used the Kinect to calculate the acceleration of each body part. Since Kinect had a limited field of view, physical activity was restricted to within the Kinect’s field of view. However, since this method used the

Kinect as a sensor, there is nothing that the player has to wear, and it provided a

55 non-intensive convenient method to estimate the energy expenditure of the human body.

7.1 Future Work

The project can progress in two directions. It can focus more on the algorithm, and work to improve its accuracy and precision. Also the game can be improved by expanding the story with a more intricate plot line and character development.

Adding more levels that are aesthetically pleasing and well designed, can bring the game to another level in terms of graphics and game-play.

7.1.1 Algorithm

The algorithm was designed to be unique and personalized for each person playing the game. However, it had limited the parameters for energy expenditure estimation because little personal information was collected from the testers. The algorithm can be improved based on a number of additional factors that all have an effect on energy expenditure of a body: height, BMI, age, body type, blood pressure, etc.

These additional parameters can be included in future iterations of the algorithm to improve the accuracy. Also, a constant value was assumed for many parameters, but the algorithm can be improved by taking a more accurate approach to estimate the value for these parameters.

56 7.1.2 Exercise Game

The Exercise Game that was released is only in its first stage. There are a number of features that can be added to it. The game can be modified to incorporate some of the ideas provided by the participants of the first testing group. More levels can be added with different environments, to provide a change of pace. A level that is truly endless can be created that ends only when the player loses in order to increase the challenge. The difficulty levels can be changed so there is more of a challenge in the harder levels. The game’s graphics can also be continuously improved.

The game can also be improved by adding certain psychological techniques to increase the motivation of a child playing the game. For example, the player’s avatar becomes more fit as they run, and less fit as they take breaks. The amount of energy expended can be given a more significant role in the score of the game.

7.2 Contribution

This thesis presents a new energy expenditure estimation algorithm that is similar in accuracy to those used in the game industry. In addition, a pipeline that provides an easy and simple integration of a 3D scanned photo realistic avatar into a game was introduced, to improve game immersion and increase player motivation.

57 Appendices

58 Appendix A

Calorific Data of Child Testing

A.1 Average Calories Burned Per Minute

Subject IDSubjectID AccelerometerAccelerometerAccelerometer AlgorithmAlgorithmAlgorithm

20160001 6.022 7.350

20160002 7.851 6.530

20160003 6.534 8.201

20160004 4.934 5.170

20160005 4.766 5.407

20160006 5.839 5.841

20160007 6.118 6.504

20160008 1.640 5.393

20160009 6.263 6.019

59 20160010 8.055 8.992

20160011 4.032

20160012 5.287 22.026

20160013 10.340 9.086

20160014 9.109 8.815

20160015 3.839 9.729

20160016 5.614 6.221

20160017 4.672 6.081

20160018 5.056 9.155

20160019 6.994 19.484

20160021 6.565 10.617

20160024 11.175 4.644

20160025 3.942 11.931

20160026 3.757 3.387

20160027 8.673 4.221

20160028 8.194 13.803

20160029 4.772

20160030 4.013 3.208

20160031 3.659 5.853

20160033 7.605 7.975

20160034 4.530

20160035 3.968 6.036

60 20160036 6.582 4.436

20160037 7.502 29.085

20160040 8.512 11.166

20160041 8.640 13.565

20160042 6.127 2.648

20160043 8.413 20.838

20160044 5.831 8.281

20160045 9.771

20160046 3.995 1.965

20160047 6.090 3.0855

20160048 9.946 32.589

A.2 Calories Burned per Minute

Subject IDSubjectID MinuteMinuteMinute AccelerometerAccelerometerAccelerometer AlgorithmAlgorithmAlgorithm

20160001 1 5.008 5.425

20160001 2 6.482 7.480

20160001 3 4.417 6.567

20160001 4 2.956 7.937

20160001 5 6.54 5.482

61 20160001 6 5.992 4.796

20160001 7 5.92 7.023

20160001 8 6.519 13.133

20160001 9 6.986 11.763

20160001 10 5.195 8.108

20160001 11 5.585 7.766

20160001 12 5.888 8.908

20160001 13 6.883 4.911

20160001 14 7.951 9.878

20160001 15 6.393 10.906

20160001 16 6.454 5.196

20160001 17 7.624 4.911

20160001 18 7.33 6.966

20160001 19 7.424 5.310

20160001 20 7.893 4.454

20160001 21 1.031

20160002 1 0.692 5.482

20160002 2 9.026 2.969

20160002 3 9.445 6.452

20160002 4 9.255 8.736

20160002 5 9.074 6.452

20160002 6 9.756 7.651

62 20160002 7 8.497 7.709

20160002 8 9.308 5.710

20160002 9 8.876 4.625

20160002 10 8.974 6.338

20160002 11 8.844 7.309

20160002 12 8.752 8.793

20160002 13 8.823 4.225

20160002 14 8.331 4.568

20160002 15 8.229 5.082

20160002 16 7.93 7.252

20160002 17 8.138 10.735

20160002 18 8.162 7.423

20160002 19 7.335 7.994

20160002 20 7.646 5.025

20160002 21 7.631

20160002 22 0

20160003 1 1.8 6.509

20160003 2 7.859 9.593

20160003 3 9.225 9.079

20160003 4 10.006 7.594

20160003 5 10.299 14.275

20160003 6 6.818 8.337

63 20160003 7 8.663 6.738

20160003 8 6.189 3.540

20160003 9 7.569 12.733

20160003 10 7.383 11.591

20160003 11 5.587 7.366

20160003 12 6.159 10.564

20160003 13 6.794 10.107

20160003 14 5.435 10.221

20160003 15 7.637 6.966

20160003 16 6.399 4.168

20160003 17 6.197 2.798

20160003 18 5.517 6.338

20160003 19 5.33 6.224

20160003 20 5.215 9.193

20160003 21 1.135

20160004 1 3.999 3.369

20160004 2 6.225 4.340

20160004 3 5.848 6.966

20160004 4 5.999 7.823

20160004 5 6.094 5.710

20160004 6 4.651 4.283

20160004 7 5.09 4.511

64 20160004 8 6.898 6.852

20160004 9 6.629 4.454

20160004 10 5.735 5.425

20160004 11 5.508 6.224

20160004 12 5.864 5.310

20160004 13 4.798 4.682

20160004 14 4.975 3.940

20160004 15 4.743 4.625

20160004 16 3.185 4.283

20160004 17 4.615 6.224

20160004 18 2.467 5.482

20160004 19 4.719 4.054

20160004 20 4.356 4.796

20160004 21 1.224

20160005 1 2.613 11.363

20160005 2 8.242 10.278

20160005 3 7.594 7.709

20160005 4 8.181 7.080

20160005 5 6.263 4.854

20160005 6 5.727 7.423

20160005 7 5.522 4.511

20160005 8 4.541 6.110

65 20160005 9 4.238 4.968

20160005 10 6.109 5.367

20160005 11 4.328 2.969

20160005 12 4.028 5.310

20160005 13 5.61 4.340

20160005 14 5.249 3.483

20160005 15 3.521 3.654

20160005 16 5.711 7.823

20160005 17 2.874 1.827

20160005 18 2.694 3.312

20160005 19 4.086 3.083

20160005 20 2.137 2.627

20160005 21 0.826

20160006 1 1.313 10.107

20160006 2 14.22 3.997

20160006 3 9.757 3.540

20160006 4 10.464 3.198

20160006 5 7.405 8.508

20160006 6 6.218 4.682

20160006 7 4.381 6.452

20160006 8 6.414 5.596

20160006 9 8.83 4.225

66 20160006 10 8.162 4.568

20160006 11 9.002 5.139

20160006 12 5.7 16.331

20160006 13 6.516 8.337

20160006 14 4.496 4.854

20160006 15 5.417 4.968

20160006 16 3.064 5.310

20160006 17 3.565 4.853

20160006 18 1.683 5.482

20160006 19 2.837 3.141

20160006 20 2.199 3.483

20160006 21 0.977

20160007 1 3.142 3.312

20160007 2 5.636 5.767

20160007 3 5.552 6.338

20160007 4 5.905 6.624

20160007 5 7.567 6.110

20160007 6 5.678 4.796

20160007 7 7.68 4.340

20160007 8 5.491 8.565

20160007 9 6.261 5.596

20160007 10 5.61 4.511

67 20160007 11 6.651 5.082

20160007 12 6.628 4.340

20160007 13 6.163 5.139

20160007 14 7.11 7.594

20160007 15 7.403 9.193

20160007 16 6.75 12.219

20160007 17 7.405 6.452

20160007 18 6.257 6.567

20160007 19 7.515 9.421

20160007 20 7.037 8.051

20160007 21 1.044

20160008 1 0.722 6.738

20160008 2 2.562 7.252

20160008 3 3.372 8.394

20160008 4 3.131 7.994

20160008 5 1.991 3.997

20160008 6 2.972 5.425

20160008 7 1.33 6.681

20160008 8 1.744 5.482

20160008 9 1.402 4.283

20160008 10 0.813 3.597

20160008 11 1.675 3.198

68 20160008 12 1.592 3.483

20160008 13 1.099 3.654

20160008 14 1.156 3.940

20160008 15 1.515 4.454

20160008 16 0.882 4.454

20160008 17 1.123 7.537

20160008 18 1.854 6.452

20160008 19 1.327 5.938

20160008 20 2.018 4.853

20160008 21 0.159

20160009 1 6.877 3.597

20160009 2 7.464 3.769

20160009 3 7.297 6.681

20160009 4 7.204 8.622

20160009 5 4.396 7.309

20160009 6 7.382 9.707

20160009 7 6.504 5.253

20160009 8 5.593 4.911

20160009 9 5.923 4.225

20160009 10 5.575 6.167

20160009 11 5.992 5.139

20160009 12 6.128 3.198

69 20160009 13 5.767 5.310

20160009 14 4.882 6.053

20160009 15 6.691 6.338

20160009 16 6.963 6.452

20160009 17 1.628 5.139

20160009 18 1.177 7.138

20160009 19 10.543 7.766

20160009 20 10.217 7.537

20160009 21 7.314

20160010 1 2.779

20160010 2 4.728

20160010 3 5.578

20160010 4 5.872

20160010 5 7.069

20160010 6 8.35

20160010 7 8.454

20160010 8 9.686

20160010 9 9.828

20160010 10 9.592

20160010 11 9.179

20160010 12 10.521

20160010 13 9.777

70 20160010 14 9.261

20160010 15 8.362

20160010 16 9.113

20160010 17 10.486

20160010 18 8.387

20160010 19 10.282

20160010 20 9.824

20160010 21 2.035

20160011 1 3.402 10.506

20160011 2 4.746 8.222

20160011 3 5.17 6.909

20160011 4 4.867 8.851

20160011 5 5.096 9.307

20160011 6 5.832 7.138

20160011 7 0.704 7.766

20160011 8 2.446 6.452

20160011 9 6.692 6.167

20160011 10 4.39 7.766

20160011 11 3.898 6.167

20160011 12 3.949 6.681

20160011 13 2.94 7.195

20160011 14 2.999 6.452

71 20160011 15 5.179 7.080

20160011 16 3.048 15.303

20160011 17 2.982 11.306

20160011 18 3.867 11.648

20160011 19 3.427 13.990

20160011 20 4.169 14.846

20160011 21 4.859

20160012 1 4.731 8.965

20160012 2 4.149 14.275

20160012 3 3.344 31.348

20160012 4 2.732 17.244

20160012 5 4.344 24.325

20160012 6 3.785 19.985

20160012 7 0 22.783

20160012 8 4.957 12.448

20160012 9 8.465 21.755

20160012 10 7.339 36.658

20160012 11 7.466 11.420

20160012 12 4.179 25.524

20160012 13 8.954 66.464

20160012 14 8.67 31.976

20160012 15 6.868 15.246

72 20160012 16 6.992 33.860

20160012 17 6.881 6.452

20160012 18 5.244 14.789

20160012 19 5.571 17.416

20160012 20 5.939 7.366

20160012 21 2.19

20160012 22 3.523

20160013 1 3.278 13.476

20160013 2 11.247 19.414

20160013 3 12.382 14.446

20160013 4 13.776 10.278

20160013 5 14.276 10.564

20160013 6 14.087 14.446

20160013 7 13.096 12.848

20160013 8 13.779 7.195

20160013 9 13.331 5.367

20160013 10 12.518 8.394

20160013 11 11.364 3.769

20160013 12 1.998 11.534

20160013 13 12.035 5.938

20160013 14 12.208 5.482

20160013 15 10.598 5.082

73 20160013 16 10.135 7.651

20160013 17 8.391 6.053

20160013 18 7.762 7.480

20160013 19 7.352 4.054

20160013 20 12.296 8.165

20160013 21 11.572

20160013 22 0

20160014 1 0.125 3.712

20160014 2 8.966 6.452

20160014 3 10.591 7.080

20160014 4 9.729 8.965

20160014 5 9.628 8.280

20160014 6 11.509 9.707

20160014 7 11.283 9.422

20160014 8 11.389 6.452

20160014 9 10.655 8.337

20160014 10 10.07 5.253

20160014 11 10.531 11.020

20160014 12 9.225 9.764

20160014 13 9.828 10.107

20160014 14 9.93 11.820

20160014 15 9.754 6.681

74 20160014 16 9.909 6.909

20160014 17 9.075 14.161

20160014 18 9.881 9.250

20160014 19 9.054 10.107

20160014 20 9.227 12.733

20160014 21 9.974

20160014 22 0.071

20160015 1 1.635 8.108

20160015 2 3.915 5.253

20160015 3 3.725 5.881

20160015 4 6.211 5.767

20160015 5 6.784 6.110

20160015 6 5.819 7.366

20160015 7 5.143 9.935

20160015 8 6.835 14.275

20160015 9 6.583 7.709

20160015 10 3.995 9.479

20160015 11 2.739 7.537

20160015 12 5.901 6.110

20160015 13 1.798 15.132

20160015 14 2.906 7.309

20160015 15 2.69 17.644

75 20160015 16 3 16.331

20160015 17 3.698 16.616

20160015 18 3.059 11.648

20160015 19 1.794 11.306

20160015 20 2.153 4.968

20160015 21 0.231

20160016 1 0 5.881

20160016 2 3.132 7.023

20160016 3 6.716 5.310

20160016 4 6.724 8.851

20160016 5 6.923 5.025

20160016 6 7.087 5.082

20160016 7 6.362 5.139

20160016 8 7.385 3.712

20160016 9 7.239 4.283

20160016 10 6.777 5.653

20160016 11 7.179 3.711

20160016 12 6.648 7.023

20160016 13 6.176 5.653

20160016 14 7.223 10.164

20160016 15 5.838 5.710

20160016 16 6.044 4.911

76 20160016 17 3.826 10.906

20160016 18 5.294 5.996

20160016 19 3.17 5.767

20160016 20 6.02 8.565

20160016 21 5.382

20160016 22 2.352

20160017 1 0.451 7.709

20160017 2 5.261 7.366

20160017 3 6.02 9.364

20160017 4 5.876 4.225

20160017 5 4.242 6.110

20160017 6 5.156 6.224

20160017 7 5.883 6.452

20160017 8 4.583 4.968

20160017 9 4.75 5.082

20160017 10 5.654 5.082

20160017 11 4.909 5.253

20160017 12 6.093 6.795

20160017 13 5.012 5.995

20160017 14 4.371 5.082

20160017 15 6.402 6.452

20160017 16 4.51 5.310

77 20160017 17 4.263 6.338

20160017 18 4.901 5.367

20160017 19 3.882 5.824

20160017 20 5.203 6.566

20160017 21 0.698

20160018 1 2.114 8.108

20160018 2 4.074 9.650

20160018 3 3.343 12.848

20160018 4 0.095 11.763

20160018 5 0.025 12.219

20160018 6 6.079 16.616

20160018 7 8.177 6.395

20160018 8 7.225 7.709

20160018 9 6.535 8.165

20160018 10 7.232 7.937

20160018 11 7.261 4.739

20160018 12 7.565 14.104

20160018 13 6.731 2.284

20160018 14 6.654 12.905

20160018 15 4.982 9.993

20160018 16 4.825 .971

20160018 17 3.032 .114

78 20160019 1 3.251 13.247

20160019 2 8.774 28.265

20160019 3 7.747 20.271

20160019 4 8.462 17.530

20160019 5 8.564 46.479

20160019 6 8.423 31.748

20160019 7 8.905 13.361

20160019 8 8.883 25.238

20160019 9 9.729 16.388

20160019 10 8.412 15.703

20160019 11 7.634 20.042

20160019 12 7.927 21.070

20160019 13 7.86 15.988

20160019 14 3.975 4.283

20160019 15 5.242 20.099

20160019 16 7.429 25.352

20160019 17 7.649 16.959

20160019 18 7.595 15.303

20160019 19 6.485 16.159

20160019 20 3.405 5.995

20160019 21 0.529

20160021 1 8.817 9.079

79 20160021 2 10.011 15.760

20160021 3 6.526 20.328

20160021 4 4.41 14.732

20160021 5 10.485 11.591

20160021 6 9.981 15.074

20160021 7 7.806 13.647

20160021 8 9.334 11.363

20160021 9 9.185 11.591

20160021 10 9.232 9.764

20160021 11 2.818 5.938

20160021 12 10.014 10.849

20160021 13 4.333 7.880

20160021 14 4.658 12.448

20160021 15 6.072 7.537

20160021 16 4.409 4.682

20160021 17 5.796 6.452

20160021 18 3.484 8.565

20160021 19 5.956 6.452

20160021 20 4.457 8.508

20160021 21 0.085

20160024 1 6.74 8.451

20160024 2 12.971 5.425

80 20160024 3 12.222 4.568

20160024 4 12.357 4.283

20160024 5 12.377 4.568

20160024 6 12.04 3.597

20160024 7 11.433 3.712

20160024 8 11.02 3.312

20160024 9 11.471 3.540

20160024 10 11.251 4.511

20160024 11 10.845 3.483

20160024 12 11.856 4.340

20160024 13 12.287 5.082

20160024 14 12.45 5.653

20160024 15 11.027 5.025

20160024 16 11.948 5.025

20160024 17 11.804 3.883

20160024 18 11.631 5.253

20160024 19 12.689 4.511

20160024 20 11.922 4.625

20160024 21 2.329

20160025 1 4.782 4.168

20160025 2 4.315 9.650

20160025 3 4.879 18.843

81 20160025 4 3.012 14.903

20160025 5 4.511 12.733

20160025 6 4.177 13.247

20160025 7 5.535 12.733

20160025 8 3.291 15.988

20160025 9 1.253 11.706

20160025 10 0.09 13.133

20160025 11 4.569 10.449

20160025 12 4.837 9.707

20160025 13 4.087 14.218

20160025 14 3.222 12.277

20160025 15 4.415 9.079

20160025 16 3.518 11.991

20160025 17 4.865 13.361

20160025 18 4.736 10.621

20160025 19 3.865 10.050

20160025 20 4.464 9.650

20160025 21 4.363

20160026 1 3.683 4.225

20160026 2 3.617 4.111

20160026 3 5.291 5.025

20160026 4 4.247 3.654

82 20160026 5 4.152 3.141

20160026 6 2.579 2.570

20160026 7 3.63 2.570

20160026 8 3.192 3.997

20160026 9 4.851 4.911

20160026 10 3.972 5.082

20160026 11 4.131 3.083

20160026 12 3.934 3.883

20160026 13 3.091 1.999

20160026 14 3.324 2.741

20160026 15 2.794 1.485

20160026 16 2.821 2.570

20160026 17 3.957 1.999

20160026 18 5.001 3.654

20160026 19 5.531 4.054

20160026 20 4.962 2.969

20160026 21 0.132

20160027 1 7.537 6.452

20160027 2 8.278 3.369

20160027 3 9.077 4.511

20160027 4 10.024 4.283

20160027 5 9.638 3.312

83 20160027 6 9.719 4.625

20160027 7 9.403 4.111

20160027 8 9.041 4.397

20160027 9 9.314 4.168

20160027 10 9.411 4.625

20160027 11 9.319 4.568

20160027 12 9.27 4.397

20160027 13 9.153 3.883

20160027 14 9.231 3.426

20160027 15 9.285 3.597

20160027 16 9.306 4.625

20160027 17 9.141 3.940

20160027 18 9.349 4.054

20160027 19 9.275 4.454

20160027 20 7.366 3.597

20160027 21 0

20160028 1 4.679 5.824

20160028 2 8.746 11.306

20160028 3 7.768 8.793

20160028 4 8.844 14.675

20160028 5 9.359 13.590

20160028 6 10.132 20.842

84 20160028 7 9.444 21.527

20160028 8 10.148 17.130

20160028 9 9.814 15.074

20160028 10 9.684 10.621

20160028 11 9.674 13.590

20160028 12 9.854 9.307

20160028 13 8.82 15.074

20160028 14 8.68 17.187

20160028 15 8.176 14.789

20160028 16 8.066 15.760

20160028 17 7.358 10.506

20160028 18 7.33 18.558

20160028 19 8.47 7.651

20160028 20 7.298 16.331

20160028 21 7.586 11.591

20160028 22 0.328

20160029 1 0.322 7.195

20160029 2 0.49 9.479

20160029 3 5.191 8.337

20160029 4 6.399 6.281

20160029 5 6.309 8.908

20160029 6 7.573 3.826

85 20160029 7 7.766 9.821

20160029 8 2.287 10.678

20160029 9 0.071 5.710

20160029 10 3.972 6.681

20160029 11 9.033 4.854

20160029 12 5.092 40.141

20160029 13 3.932 .228

20160029 14 4.059 11.477

20160029 15 3.042 10.164

20160029 16 0.96 8.337

20160029 17 0.658 7.366

20160029 18 0 7.080

20160029 19 8.611 1.199

20160029 20 8.67

20160029 21 8.637

20160029 22 8.623

20160029 23 8.061

20160030 1 4.182 5.596

20160030 2 11.835 5.425

20160030 3 10.475 5.938

20160030 4 9.069 3.597

20160030 5 4.581 5.139

86 20160030 6 5.634 3.769

20160030 7 3.65 1.999

20160030 8 1.932 2.570

20160030 9 1.371 1.770

20160030 10 1.379 2.113

20160030 11 2.804 3.540

20160030 12 3.082 2.170

20160030 13 3.826 3.826

20160030 14 3.051 2.570

20160030 15 3.599 2.969

20160030 16 2.396 2.512

20160030 17 2.817 1.999

20160030 18 2.788 1.599

20160030 19 2.732 2.284

20160030 20 2.586 2.741

20160030 21 0.491

20160031 1 0

20160031 2 0

20160031 3 3.729 7.366

20160031 4 6.639 5.596

20160031 5 5.342 4.968

20160031 6 5.576 6.567

87 20160031 7 5.212 4.796

20160031 8 3.618 7.709

20160031 9 5.044 4.911

20160031 10 4.022 7.651

20160031 11 3.76 5.938

20160031 12 4.771 5.425

20160031 13 3.166 4.568

20160031 14 3.402 5.710

20160031 15 4.215 6.224

20160031 16 3.415 5.710

20160031 17 3.866 5.539

20160031 18 3.33 5.310

20160031 19 3.587 4.397

20160031 20 3.41 5.367

20160031 21 3.511 8.051

20160031 22 0.885 5.196

20160033 1 4.91 5.139

20160033 2 10.991 6.795

20160033 3 11.116 3.997

20160033 4 11.482 9.136

20160033 5 6.956 10.906

20160033 6 7.661 8.165

88 20160033 7 4.049 8.679

20160033 8 11.409 14.618

20160033 9 7.608 8.108

20160033 10 5.689 9.193

20160033 11 9.251 9.079

20160033 12 7.256 7.594

20160033 13 8.734 8.051

20160033 14 10.152 6.395

20160033 15 7.66 7.994

20160033 16 9.476 9.307

20160033 17 8.691 5.996

20160033 18 6.544 6.281

20160033 19 8.984 6.795

20160033 20 6.958 7.195

20160033 21 1.726

20160033 22 0

20160034 1 4.891

20160034 2 9.826

20160034 3 11.379

20160034 4 3.659

20160034 5 7.521

20160034 6 6.688

89 20160034 7 6.653

20160034 8 3.872

20160034 9 3.607

20160034 10 3.476

20160034 11 2.913

20160034 12 4.14

20160034 13 3.768

20160034 14 3.157

20160034 15 3.504

20160034 16 2.571

20160034 17 3.48

20160034 18 3.46

20160034 19 2.663

20160034 20 3.359

20160034 21 0.543

20160035 1 1.845 4.911

20160035 2 3.769 4.054

20160035 3 3.463 4.054

20160035 4 2.764 3.712

20160035 5 3.518 3.883

20160035 6 3.885 4.454

20160035 7 4.103 6.738

90 20160035 8 3.786 7.138

20160035 9 4.696 6.681

20160035 10 5.535 7.080

20160035 11 5.638 7.252

20160035 12 4.614 7.651

20160035 13 3.563 6.338

20160035 14 3.951 5.253

20160035 15 4.154 6.966

20160035 16 4.795 8.051

20160035 17 4.287 5.767

20160035 18 4.334 7.309

20160035 19 5.335 5.482

20160035 20 4.613 7.880

20160035 21 0.69

20160036 1 0.733 4.568

20160036 2 6.476 3.997

20160036 3 7.405 4.682

20160036 4 6.53 5.881

20160036 5 7.698 4.796

20160036 6 7.026 4.854

20160036 7 7.5 4.625

20160036 8 7.045 3.426

91 20160036 9 6.547 4.054

20160036 10 6.963 3.141

20160036 11 6.383 4.283

20160036 12 7.427 4.340

20160036 13 6.338 4.911

20160036 14 7.57 4.739

20160036 15 7.032 4.796

20160036 16 8.025 5.082

20160036 17 7.66 3.997

20160036 18 7.373 3.883

20160036 19 7.299 3.540

20160036 20 7.733 5.082

20160036 21 1.451

20160037 1 1.788 10.678

20160037 2 7.288 29.064

20160037 3 7.957 35.745

20160037 4 9.029 26.095

20160037 5 8.135 23.183

20160037 6 9.7 37.686

20160037 7 8.358 71.718

20160037 8 8.899 36.259

20160037 9 9.342 39.742

92 20160037 10 9.349 23.697

20160037 11 8.597 35.059

20160037 12 8.114 39.913

20160037 13 8.353 20.784

20160037 14 8.137 23.697

20160037 15 8.432 26.437

20160037 16 8.377 24.039

20160037 17 8.399 18.215

20160037 18 8.016 17.872

20160037 19 8.153 23.240

20160037 20 7.56 18.272

20160037 21 3.052

20160037 22 0

20160040 1 5.973 14.903

20160040 2 9.421 12.905

20160040 3 9.854 10.564

20160040 4 9.803 9.079

20160040 5 8.967 12.619

20160040 6 10.068 13.019

20160040 7 9.507 10.107

20160040 8 9.853 10.906

20160040 9 9.641 10.906

93 20160040 10 9.971 12.105

20160040 11 8.407 7.937

20160040 12 8.315 10.107

20160040 13 9.097 11.648

20160040 14 8.604 10.107

20160040 15 8.902 10.335

20160040 16 8.538 10.278

20160040 17 8.202 10.678

20160040 18 8.033 9.421

20160040 19 7.66 13.647

20160040 20 8.425 11.934

20160040 21 1.51

20160041 1 6.691 4.397

20160041 2 8.84 5.196

20160041 3 8.221 9.935

20160041 4 8.211 12.962

20160041 5 8.541 17.701

20160041 6 9.307 14.789

20160041 7 6.389 7.880

20160041 8 7.257 7.423

20160041 9 9.771 16.616

20160041 10 9.912 14.275

94 20160041 11 10.793 19.071

20160041 12 7.702 19.700

20160041 13 11.455 19.357

20160041 14 10.269 15.189

20160041 15 10.523 9.479

20160041 16 9.707 11.877

20160041 17 9.795 8.793

20160041 18 10.051 13.647

20160041 19 11.163 28.150

20160041 20 6.833 14.732

20160041 21 0

20160042 1 5.61 1.485

20160042 2 7.744 3.083

20160042 3 8.196 2.969

20160042 4 7.287 2.455

20160042 5 7.551 2.341

20160042 6 7.661 3.198

20160042 7 6.185 1.999

20160042 8 6.147 2.227

20160042 9 4.893 1.313

20160042 10 5.656 1.941

20160042 11 6.128 1.713

95 20160042 12 6.472 3.483

20160042 13 6.699 1.713

20160042 14 6.031 2.570

20160042 15 5.832 3.883

20160042 16 5.773 3.198

20160042 17 5.505 3.483

20160042 18 6.02 2.284

20160042 19 6.363 3.255

20160042 20 6.096 4.340

20160042 21 0.827

20160043 1 9.455 5.025

20160043 2 9.189 15.474

20160043 3 9.301 25.295

20160043 4 9.214 44.824

20160043 5 9.136 24.039

20160043 6 4.131 14.789

20160043 7 0 23.011

20160043 8 9.375 20.784

20160043 9 8.371 24.781

20160043 10 10.074 12.391

20160043 11 5.963 14.732

20160043 12 9.798 35.459

96 20160043 13 9.745 23.925

20160043 14 9.606 12.905

20160043 15 8.932 22.669

20160043 16 8.478 11.591

20160043 17 9.795 29.407

20160043 18 9.532 13.761

20160043 19 9.158 18.272

20160043 20 8.526 23.411

20160043 21 8.892

20160044 1 0.869 7.309

20160044 2 6.763 5.082

20160044 3 7.012 9.136

20160044 4 6.437 8.908

20160044 5 7.379 7.480

20160044 6 6.192 6.567

20160044 7 6.832 11.249

20160044 8 6.147 7.366

20160044 9 6.173 8.508

20160044 10 5.824 7.366

20160044 11 6.045 7.651

20160044 12 6.14 9.307

20160044 13 6.304 10.963

97 20160044 14 5.716 10.164

20160044 15 7.082 9.364

20160044 16 6.935 10.678

20160044 17 7.118 8.108

20160044 18 6.177 6.852

20160044 19 5.938 6.167

20160044 20 5.881 7.309

20160044 21 5.317

20160044 22 0

20160045 1 4.326

20160045 2 16.715

20160045 3 15.59

20160045 4 16.693

20160045 5 13.488

20160045 6 15.64

20160045 7 15.633

20160045 8 14.764

20160045 9 13.547

20160045 10 14.332

20160045 11 12.759

20160045 12 9.355

20160045 13 5.338

98 20160045 14 4.69

20160045 15 6.304

20160045 16 6.267

20160045 17 5.565

20160045 18 6.29

20160045 19 6.049

20160045 20 5.438

20160045 21 6.177

20160045 22 0

20160046 1 3.059 4.283

20160046 2 3.635 .914

20160046 3 4.022 1.313

20160046 4 3.276 1.142

20160046 5 3.835 2.227

20160046 6 3.49 1.199

20160046 7 3.471 1.199

20160046 8 4.44 1.370

20160046 9 2.81 .971

20160046 10 3.011 1.770

20160046 11 3.051 1.370

20160046 12 5.696 2.341

20160046 13 4.472 1.827

99 20160046 14 4.383 1.999

20160046 15 5.445 1.884

20160046 16 5.124 1.713

20160046 17 5.175 1.656

20160046 18 4.998 4.397

20160046 19 5.447 2.398

20160046 20 3.886 3.312

20160046 21 1.162

20160047 1 5.526 4.568

20160047 2 1.097 1.085

20160047 3 2.668 2.398

20160047 4 8.694 1.941

20160047 5 7.281 2.398

20160047 6 6.622 3.369

20160047 7 5.421 3.255

20160047 8 6.56 2.969

20160047 9 6.767 3.654

20160047 10 7.347 3.483

20160047 11 8.568 2.398

20160047 12 5.254 2.741

20160047 13 6.468 3.083

20160047 14 6.283 3.426

100 20160047 15 6.11 2.684

20160047 16 6.429 3.026

20160047 17 5.362 3.198

20160047 18 5.996 3.369

20160047 19 5.661 3.198

20160047 20 7.309 5.425

20160047 21 6.462

20160048 1 8.734 13.533

20160048 2 11.53 54.816

20160048 3 13.349 29.692

20160048 4 13.555 29.863

20160048 5 7.601 45.509

20160048 6 12.109 38.371

20160048 7 12.759 41.398

20160048 8 11.567 25.010

20160048 9 12.171 40.198

20160048 10 12.249 24.096

20160048 11 11.965 31.805

20160048 12 12.509 36.259

20160048 13 9.137 31.234

20160048 14 5.93 22.726

20160048 15 6.556 25.923

101 20160048 16 6.876 38.600

20160048 17 6.472 19.071

20160048 18 7.924 35.973

20160048 19 13.053 31.405

20160048 20 10.988 35.973

20160048 21 1.838

102 Appendix B

Calorific Data of Adult Testing

B.1 Calories Burned Per Interval

IntervalIntervalInterval Subject 1Subject1 Subject 2Subject2

(10 sec) GameGameGame AlgorithmAlgorithmAlgorithm GameGameGame AlgorithmAlgorithmAlgorithm

1 0.21 0.19 0.1 0.07

2 0.29 0.16 0.3 0.64

3 0.06 0.31 0.46 0.31

4 0.27 0.05 0.27 0.24

5 0.45 0.19 0.86 0.24

6 0.33 0.45 0.67 0.45

7 0.31 0.21 0.88 0.39

8 0.38 0.27 0.4 0.3

103 9 0.7 0.22 0.73 0.32

10 0.25 0.41 0 0.65

11 0.38 0.17 0.1 0.08

12 0.41 0.33 0.12 0

13 0 0.18 0.15 0.27

14 0 0.32 0.18 0.28

15 0.4 0.17 0.31 0.39

16 0.13 0.31 0.28 0.38

17 0.15 0.7 0.05 0.23

18 0.17 0.63 0.23 0.14

19 0.16 0.23 0.1 0.47

20 0.09 0.32 0.12 0.34

21 0.13 0.47 0.13 0.2

22 0.14 0.28 0.14 0.23

23 0.15 0.26 0.1 0.35

24 0.14 0.2 0.12 0.28

25 0.15 0.09 0.16 0.15

26 0.38 0.36 0.2 0.3

27 0.2 0.26 0.16 0.3

28 0.13 0.05 0.21 0.49

29 0.22 0.2 0.22 0.28

30 0.2 0.53 0 0.38

104 31 0.1 0.08 0.16 0.2

32 0.09 0.02 0.11 0

33 0.13 0.21 0.19 0.11

34 0.02 0.16 0.21 0.11

35 0.18 0.24 0.26 0.24

36 0.2 0.16 0.25 0.27

37 0.23 0.22 0.38 0.23

38 0.18 0.2 0.2 0.26

39 0.11 0.08 0.08 0.22

40 0.05 0.09 0 0.05

41 0.07 0.2 0.02 0.08

42 0.14 0.14 0.08 0

43 0 1.27 0.09 0.2

44 0.3 0.12 0.09 0.17

45 0.09 0.27 0.09 0.3

46 0.14 0.13 0.23 0.37

47 0.1 0.2 0.18 0.14

48 0.13 0.23 0.13 0.53

49 0.06 0.25 0.09 0.43

50 0.06 0.1 0.09 0.28

51 0.09 0.09 0.08 0.31

52 0.08 0.36 0.15 0.33

105 53 0.14 0.32 0.07 0.34

54 0.16 0.36 0.11 0.1

55 0.07 0.14 0.11 0.45

56 0.07 0.09 0.12 0.45

57 0 0.02 0.06 0.46

58 0 0 0.02 0.09

59 0.08 0.16 0.07 0.06

60 0.14 0.45 0.11 0.16

61 0.03 0.36 0.23 0.17

62 0.09 0.19 0.34 0.25

63 0.2 0.12 0.1 0.3

64 0.05 0.1 0 0.17

65 0 0 0.01 0.13

66 0.08 0.08 0.14 0

67 0.08 0.17 0.07 0.2

68 0.21 0.15 0.09 0.1

69 0.2 0.3 0.04 0.16

70 0.14 0.15 0.07 0.01

71 0.2 0.2 0.11 0.01

72 0.15 0.07 0.06 0.1

73 0.19 0.33 0.23 0.16

74 0.11 0.06 0 0.14

106 75 0 0.04 0.12 0.02

76 0.06 0.05 0.04 0.14

77 0.08 0.17 0.02 0.1

78 0.22 0.27 0.15 0.02

79 0.07 0.38 0.07 0.66

80 0.06 0.16 0.07 0.11

81 0.09 0.29 0.13 0.3

82 0.11 0.17 0.08 0.12

83 0.09 0.13 0.09 0.22

84 0.1 0.15 0.06 0.36

85 0.12 0.17 0.04 0.22

86 0.11 0.19 0.06 0.18

87 0.06 1.46 0.06 0.18

88 0.04 0.06 0.08 0.33

89 0.04 0.12 0.12 0.34

90 0.04 0.19 0.1 0.21

91 0.12 0.13 0.13 0.19

92 0.11 0.16 0.08 0.11

93 0.07 0.29 0.084 0.2

94 0.08 0.22 0.036 0.18

95 0.06 0.2 0.03 0.1

96 0.07 0.26 0.06 0.04

107 97 0.07 0.29 0.03 0.11

98 0 0.28 0.05 0.15

99 0.05 0.04 0 0.14

100 0.12 0.07 0.05 0.14

101 0.13 0.96 0.11 0

102 0.23 0.25 0.08 0.1

103 0.18 0.35 0.17 0.26

104 0.16 0.32 0.15 0.18

105 0.16 0.11 0.21 0.41

106 0.2 0.09 0.09 0.65

107 0.23 0.08 0.08 0.1

108 0 0.13 0.19 0.21

109 0.08 0 0.11 0.1

110 0.08 0.04 0 0.24

111 0.11 0.35 0.09 0.21

112 0.23 0.18 0.01 0.16

113 0.14 0.47 0.04 0.08

114 0.12 0.14 0.04 0.16

115 0.07 0.14 0.13 0.29

116 0.07 0.16 0.13 0.27

117 0.03 0.14 0.12 0.16

118 0.12 0.11 0.08 0.31

108 119 0.13 0.28 0.04 0.11

120 0.11 0.13

B.2 Cumulative Calories Burned

IntervalIntervalInterval Subject 1Subject1 Subject 2Subject2

(10 sec) GameGameGame AlgorithmAlgorithmAlgorithm GameGameGame AlgorithmAlgorithmAlgorithm

1 0.21 0.19 0.1 0.07

2 0.5 0.35 0.4 0.71

3 0.56 0.66 0.86 1.02

4 0.83 0.71 1.13 1.26

5 1.28 0.9 1.99 1.5

6 1.61 1.35 2.66 1.95

7 1.92 1.56 3.54 2.34

8 2.3 1.83 3.94 2.64

9 3 2.05 4.67 2.96

10 3.25 2.46 4.67 3.61

11 3.63 2.63 4.77 3.69

12 4.04 2.96 4.89 3.69

13 4.04 3.14 5.04 3.96

109 14 4.04 3.46 5.22 4.24

15 4.44 3.63 5.53 4.63

16 4.57 3.94 5.81 5.01

17 4.72 4.64 5.86 5.24

18 4.89 5.27 6.09 5.38

19 5.05 5.5 6.19 5.85

20 5.14 5.82 6.31 6.19

21 5.27 6.29 6.44 6.39

22 5.41 6.57 6.58 6.62

23 5.56 6.83 6.68 6.97

24 5.7 7.03 6.8 7.25

25 5.85 7.12 6.96 7.4

26 6.23 7.48 7.16 7.7

27 6.43 7.74 7.32 8

28 6.56 7.79 7.53 8.49

29 6.78 7.99 7.75 8.77

30 6.98 8.52 7.75 9.15

31 7.08 8.6 7.91 9.35

32 7.17 8.62 8.02 9.35

33 7.3 8.83 8.21 9.46

34 7.32 8.99 8.42 9.57

35 7.5 9.23 8.68 9.81

110 36 7.7 9.39 8.93 10.08

37 7.93 9.61 9.31 10.31

38 8.11 9.81 9.51 10.57

39 8.22 9.89 9.59 10.79

40 8.27 9.98 9.59 10.84

41 8.34 10.18 9.61 10.92

42 8.48 10.32 9.69 10.92

43 8.48 11.59 9.78 11.12

44 8.78 11.71 9.87 11.29

45 8.87 11.98 9.96 11.59

46 9.01 12.11 10.19 11.96

47 9.11 12.31 10.37 12.1

48 9.24 12.54 10.5 12.63

49 9.3 12.79 10.59 13.06

50 9.36 12.89 10.68 13.34

51 9.45 12.98 10.76 13.65

52 9.53 13.34 10.91 13.98

53 9.67 13.66 10.98 14.32

54 9.83 14.02 11.09 14.42

55 9.9 14.16 11.2 14.87

56 9.97 14.25 11.32 15.32

57 9.97 14.27 11.38 15.78

111 58 9.97 14.27 11.4 15.87

59 10.05 14.43 11.47 15.93

60 10.19 14.88 11.58 16.09

61 10.22 15.24 11.81 16.26

62 10.31 15.43 12.15 16.51

63 10.51 15.55 12.25 16.81

64 10.56 15.65 12.25 16.98

65 10.56 15.65 12.26 17.11

66 10.64 15.73 12.4 17.11

67 10.72 15.9 12.47 17.31

68 10.93 16.05 12.56 17.41

69 11.13 16.35 12.6 17.57

70 11.27 16.5 12.67 17.58

71 11.47 16.7 12.78 17.59

72 11.62 16.77 12.84 17.69

73 11.81 17.1 13.07 17.85

74 11.92 17.16 13.07 17.99

75 11.92 17.2 13.19 18.01

76 11.98 17.25 13.23 18.15

77 12.06 17.42 13.25 18.25

78 12.28 17.69 13.4 18.27

79 12.35 18.07 13.47 18.93

112 80 12.41 18.23 13.54 19.04

81 12.5 18.52 13.67 19.34

82 12.61 18.69 13.75 19.46

83 12.7 18.82 13.84 19.68

84 12.8 18.97 13.9 20.04

85 12.92 19.14 13.94 20.26

86 13.03 19.33 14 20.44

87 13.09 20.79 14.06 20.62

88 13.13 20.85 14.14 20.95

89 13.17 20.97 14.26 21.29

90 13.21 21.16 14.36 21.5

91 13.33 21.29 14.49 21.69

92 13.44 21.45 14.57 21.8

93 13.51 21.74 14.654 22

94 13.59 21.96 14.69 22.18

95 13.65 22.16 14.72 22.28

96 13.72 22.42 14.78 22.32

97 13.79 22.71 14.81 22.43

98 13.79 22.99 14.86 22.58

99 13.84 23.03 14.86 22.72

100 13.96 23.1 14.91 22.86

101 14.09 24.06 15.02 22.86

113 102 14.32 24.31 15.1 22.96

103 14.5 24.66 15.27 23.22

104 14.66 24.98 15.42 23.4

105 14.82 25.09 15.63 23.81

106 15.02 25.18 15.72 24.46

107 15.25 25.26 15.8 24.56

108 15.25 25.39 15.99 24.77

109 15.33 25.39 16.1 24.87

110 15.41 25.43 16.1 25.11

111 15.52 25.78 16.19 25.32

112 15.75 25.96 16.2 25.48

113 15.89 26.43 16.24 25.56

114 16.01 26.57 16.28 25.72

115 16.08 26.71 16.41 26.01

116 16.15 26.87 16.54 26.28

117 16.18 27.01 16.66 26.44

118 16.3 27.12 16.74 26.75

119 16.43 27.4 16.78 26.86

120 16.54 27.53

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