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© author(s) of these slides including research results from the KOM research network and TU Darmstadt; otherwise it is specified at the respective slide
7-Nov-14
Prof. Dr.-Ing. Ralf Steinmetz
KOM - Multimedia Communications Lab
ACMM2014___Challenge_in_Exergames___Sandro_Hardy___v0.3.pptx
What Makes Games Challenging?
Considerations on How to Determine the “Challenge”
Posed by an Exergame for BalanceTraining
Source: http://www.sycor-asia.com/opencms/as/products_services/complementary_services/Telecommunication/
Sandro Hardy, M.Sc.
Sandro.Hardy@kom.tu-darmstadt.de
KOM – Multimedia Communications Lab 2
Motivation
Today
Lack of exercise health risks [WHO10, EC10]
Sports reduce physical ailments [WHO10-1, ACSM11]
Challenge
Exergames have small effects [BBC+08, KW10]
Objective scientific methodologies [IQWiG11]
Health technology assessment (HTA)
Idea
Real-time “in game”- measurement
Real-time “In game”- adaptation
Image Sources: Child Playing Video Game: EinsLive, Femoral Neck Fracture: KH Schwarzach
KOM – Multimedia Communications Lab 3
RQ1: How can we
assure the motivation
of the players?
RQ2: How can we
increase the training
effects of Exergames?
Research Questions
RQ1 RQ2
KOM – Multimedia Communications Lab 4
State of the Art
Game Theory Attractivity [Malo82, YHL06]
Flow [Csik75], Gameflow [SW05]
Dual Flow [SHM07]
Elderly [GeSM10, GLN+12]
Sport Games Wii Fit, DDR [BBC+08]
Balance [KW10]
Interfaces & Sensors Cardio Training [SGYR09]
Gait Rehab, Balance [GHS+11]
Feedback [MHAE11]
Game Experience (abbr. GX) [Nac09]
Vital Parameters [SHM07, SGYR09]
Stroke Rehabilitation [AHJS09]
Dual Flow, [SHM07]
KOM – Multimedia Communications Lab 5
Software
• Gaming
• Training
Software
• Gaming
• Training
Vital Sensors
Physiology
• Vital Status
• Performance
Psychology
• Attractiveness
• Effectiveness
Hardware
• Electronics
• Mechanics
Sta
tic
Adap
tive
System User
Concept: Adaptation Model for Exergames
Publications: [HGG+11]
Adaption Fields
Hardware / Physis
Game Experience
Training
Software
Focus
Adaptive Software
Gaming
Training
Vital Status
KOM – Multimedia Communications Lab 6
Act Modification Adaptation Analyze Measure
Training
UX
Physis
Training / Playing
• Enjoyment • Motivation • Fun
UX-Measure
• Questionnaire • Video Analysis • BCI / EEG
Data Analysis
• UX Calcul.
Game Adaptation
• Challenge • Curiosity • Arousal
Gameplay Modification
• Game Type • Graphics • Style
Training / Playing
• Strength • Movements
Data Analysis
• Initial Setup
Calculation
Training Settings
• Control
Parameters
Gameplay Modification
• Hardware
Performance/ Test
• Force • Endurance
Training / Playing
• Vital
Parameters
Performance Sensors
• Power • Movement • Heart Rate
Data Analysis
• Intensity • Difficulty • Fitness
Training Adaptation
• Parameter
Adaptation
Gameplay Modification
• Actuators • Game Objects • Game Control
Publications: [WH13]
Concept: Adaptation Layers
Act Modification Adaptation Measure
Training
Game Experi- ence
Physis/ Hardware
Training / Playing
• Enjoyment • Motivation • Fun
Game Experience
Measurement
• Questionnaire • Video Analysis • BCI / EEG
Data Analysis
• Game Experience
• Metrics
Game Adaptation
• Challenge • Curiosity • Arousal
Gameplay Modification
• Game Type • Graphics • Style
Training / Playing
• Strength • Movements
Data Analysis
• Initial Setup
Calculation
Training Settings
• Control
Parameters
Setting Modification
• Hardware
Performance Test
• Force • Endurance
Training / Playing
• Vital
Parameters
Performance Measurement
• Power • Movement • Heart Rate
Data Analysis
• Intensity • Difficulty • Fitness
Training Adaptation
• Parameter
Adaptation
Gameplay Modification
• Actuators • Game Objects • Game Control
KOM – Multimedia Communications Lab 7
Concept: Conditions and Metric
Conditions
Game Experience Models
Training Plans
Metric
Keep Game Experience
Improve Training Effects
Concept
Adaptation
Training Guidelines
GX Theories
Training / Playing
UX Measure
Data Analysis
Game Adap- tation
Game- play
Modi- fication
Training / Playing
Perfor- mance
Sensors
Data Analysis
Training Adap- tation
Game- play Modi
fication
Training Load/
GX
Conditions Metric Potential
KOM – Multimedia Communications Lab 8
Concept: Formal Hypothesis
Training Guidelines
GX Theory
Performance Metrics
GX Assessment
Conditions Metric Interdependencies
Cardio Training Heart Rate …
Fall Prevention Stability …
Cardio Traing Interval …
Fall Prevention Balance …
Fall Risk
Health Status
UX Rating Fun …
Usage Freqency &
Duration
Dual Flow Attractivity …
Parameter Relation Output
Adaptation Measurement
a = Attributes of a single game
c, e, p = Effects of one attribute (cognitive, emotional, physical)
M = Motivational effects (positives affects, correlate with usage)
T = Training effects
Q = Quality (achievements of objectives)
𝑎𝑖 𝑐𝛽1, 𝑒𝛽2, 𝑝𝛽3 = 𝑀 ∗ 𝑇 = 𝑄
𝑛
𝑖=1
KOM – Multimedia Communications Lab 9
• GXQ • Mimic • EMG • EEG • GSR • Respiration • ECG • Kinect • ArToolkit • Move • Razor
Hydra • Balance
Board • VO2max • …
Concept: Parameters
Physis
Training / Playing
• Strength • Movements
Data Analysis
• Initial Setup
Calculation
Training Settings
• Control
Parameters
Gameplay Modification
• Hardware
Performance/ Test
• Force • Endurance
Training Guidelines
GX Theory
Performance Metrics
GX Assessment
Conditions Metric Interdependencies
Cardio Training Heart Rate …
Fall Prevention Stability …
Cardio Traing Interval …
Fall Prevention Balance …
Fall Risk
Health Status
GX Rating Fun …
Usage Freqency &
Duration
Dual Flow Attractivity …
• Flow • Challenge • Workload • Clear Goals • Focus • Single Task • Control • Empowerment • Immersion • Awareness
• Training
Load • Exertion • Range • Speed • Resistance • Reaction • …
• Emotional Feeling
• Cognitive Load
• Physical Performance
• …
Parameter Relation Output
Adaptation Measurement
KOM – Multimedia Communications Lab 10
Concept: Parameters
[Nacke]
[Masek]
[Hingston]
[Sinclair]
Physis
Training / Playing
• Strength • Movements
Data Analysis
• Initial Setup
Calculation
Training Settings
• Control
Parameters
Gameplay Modification
• Hardware
Performance/ Test
• Force • Endurance
• GXQ
• Mimic • Iris • VO2max • EMG • EEG • GSR • Respiration • ECG • Kinect • ArToolkit • Move • Razor
Hydra • Balance
Board • …
Training Guidelines
GX Theory
Performance Metrics
GX Assessment
Conditions Metric Interdependencies
Cardio Training Heart Rate …
Fall Prevention Stability …
Cardio Traing Interval …
Fall Prevention Balance …
Fall Risk
Health Status
GX Rating Fun …
Usage Freqency &
Duration
Dual Flow Attractivity …
• Clear Goals • Focus • Single Task • Feedback • Immersion
• Control
• Challenge Training Load
• Skills:
Flexibility Speed Strength Coordination Endurance
• Emotional Feeling
• Cognitive Load
• Training Success Physical Performance
Parameter Relation Output
Adaptation Measurement
KOM – Multimedia Communications Lab 11
A: Asset Configuration Configuration of objects and interactions
C: Control Adaptation Relation between physiological measurements and control of the game
D: Difficulty Adaptation Adaptation of the game environment
Estimation of user behavior
Concept: Adaptation & Personalization
• GXQ
• Mimic • Iris • VO2max • EMG • EEG • GSR • Respiration • ECG • Kinect • ArToolkit • Move • Razor
Hydra • Balance
Board • …
Interdependencies
• Clear Goals • Focus • Single Task • Feedback • Immersion
• Control
• Challenge Training Load
• Skills:
Flexibility Speed Strength Coordination Endurance
• Emotional Feeling
• Cognitive Load
• Training Success Physical Performance
Parameter Relation Output
Adaptation Measurement
A
C D
KOM – Multimedia Communications Lab 12
Object Types Player
Target
Enemy
Game Environment Obstacles
Design Graphics
Sound
Interaction Position/Speed
Physics/AI
Concept: Asset Configuration
x
y
KOM – Multimedia Communications Lab 13
Interaction Position/Movement
Physics/AI
Control Physiological Reaction
Sensor (S)
Signals (s) e.g. Heart Rate, Force, Speed
𝐴 = 𝐼 𝑠
Reactions e.g. Height (h), Speed, Acceleration
Concept: Control Adaptation
y
Time [s]
Sig
na
l
h
S
T
O
E
O
x,t
h1
h2
KOM – Multimedia Communications Lab 14
Game Objects Area (A)
Start (S) Player‘s Position
Target (T)
Enemies (E)
Obstacles (O)
Ground (G)
Distance (D)
Paths (P)
Game Structure
𝐴 =
𝑎00 ⋯ 𝑎𝑚0⋮ ⋱ ⋮𝑎0𝑛 ⋯ 𝑎𝑚𝑛
∀𝑎𝑚𝑛: 𝑎𝑚𝑛 ∈ 𝑆, 𝑇, 𝐸, 𝑂, 𝐺 ;𝑚, 𝑛 ∈ ℕ0 ∃! 𝑎𝑥𝑦: 𝑎𝑥𝑦 = 𝑆
∃! 𝑎𝑥𝑦: 𝑎𝑥𝑦 = 𝑇
𝐷 𝑎𝑥𝑦 , 𝑎𝑢,𝑣 = 𝑥 − 𝑢 2 + 𝑦 − 𝑣 2 𝑆𝑥𝑦 → 𝑆𝑥′𝑦′: (𝑥
′= 𝑥)∨(y′=y)
Strategies Shortest Path (P1)
Avoid Enemies (P2)
Easiest Path (P3)
Concept: Difficulty Adaption
KOM – Multimedia Communications Lab 15
Metrics Center of Pressure 𝐶𝑂𝑃 = 𝑥, 𝑦 = {
𝐹2 + 𝐹4 − (𝐹1 + 𝐹3)
∑𝐹𝑖;𝐹1 + 𝐹2 − (𝐹3 + 𝐹4)
∑𝐹𝑖}
Anterior-Posterior Stability Index 𝐴𝑃𝑆𝐼 =
∑ 0 − 𝑌 2
|𝑆𝑎𝑚𝑝𝑙𝑒𝑠|
Medio-Lateral Stability Index
𝑀𝐿𝑆𝐼 =∑ 0 − 𝑋 2
|𝑆𝑎𝑚𝑝𝑙𝑒𝑠|
Overall Stability Index
𝑂𝑆𝐼 =∑ 0 − 𝑌 2 + ∑ 0 − 𝑋 2
|𝑆𝑎𝑚𝑝𝑙𝑒𝑠|
Area of Sway 𝐴𝑆 = 𝑥𝑚𝑎𝑥 − 𝑥𝑚𝑖𝑛 ∗ (𝑦𝑚𝑎𝑥 − 𝑦𝑚𝑖𝑛)
Sway Path 𝑆𝑃 = ∑ 𝑥𝑖+1 − 𝑥𝑖
2 + 𝑦𝑖+1 − 𝑦𝑖 2 𝑛−1
𝑖=1
⇒ |𝑝 𝑖 − 𝑝 𝑖+1|
𝑛−1
𝑖=1
Difficulty Adaption: Balance Training
KOM – Multimedia Communications Lab 16
Prototype BalanceFit
Experience Low initial skills sensitivity
Low initial performance
Safety standing frame
Physical ailments
Visual accessibility
Risk of social exclusion
Long term usage
Publications: [GHS+11]
KOM – Multimedia Communications Lab 17
BalanceFit: Asset Configuration
Hypothesis:
The emotional design of the
environment is reflected in ther
Game Experience Rating
Setting
Two games, same gameplay,
different emotional design. I.E.
friendly vs. melancholy.
Outcome
planned
prove effects for exergames
KOM – Multimedia Communications Lab 18
Hypothesis: New levels (curiosity) increase
perceived game experience
Setting 10 Level, 50 Level
Exclusion of simple levels (time limit)
Outcome Elderly are curious for new game
elements
Curiosity is important to keep a game challenging
How can we realize automatic difficulty adaptation?
BalanceFit: Difficulty Adaptation
Publications: [HGWS12], [HGS13]
KOM – Multimedia Communications Lab 19
Experimental Setting
Hypothesis 1: Level features influence motivation.
Hypothesis 2: Level features influence the perceived difficulty.
Hypothesis 3: Level features influence performance.
Hypothesis 4: Goal setting influences motivation, perceived
difficulty and performance.
Independent Variables The length of the shortest path
The number of orientation changes
The number of bottlenecks
The length of open curbs
KOM – Multimedia Communications Lab 20
Experimental Setting
Dependent Variables Motivation (subjective) Motivation
Questionnaire (FAM, Rheinberg, Vollmeyer & Burns, 2001)
Performance (objective): needed time to reach the goal
Control Variables Subjectivly perceived level difficulty
(„subjective mental effort questionnaire“ SMEQ, Zijlstra & Van Doorn, 1986)
Change of affects after each single level („Self-Assessment Manikin“ SAM, Bradley & Lang, 1994)
Technology-Acceptance („Technology-Acceptance-Model“ TAM, Davis, 1985) n=47
Participants age: 18-42 Years (M=24,13, SD=5,48)
33 Students of Psychology, 9 Students of Psychology in IT
KOM – Multimedia Communications Lab 21
Motivation Difficulty Performance
Pre Post Pre Post
Shortest Path o o *** - **
Orientation
Changes *** ** *** *** ***
Bottlenecks o o o *** * (-)
Open Curbs ** o *** ** *
Results
*:= p<=.1; **:= p<=.01; ***:= p<=.001; o:= p>.01.
KOM – Multimedia Communications Lab 22
Criticis
Selected Levels Features and Definitions
Number of investigated levels
Characteristics of Levels
High Standard Deviation maybe an „individualized“ view is better
Discussion
26.11.2013| Aktueller Stand| Modul : FP1-1 | A. Kern, N. Kolb, A.-L. Meimbresse, S. Merkel, J. Schwan, V. Schochlow, H. L. Spieske | Seite 22
KOM – Multimedia Communications Lab 23
Assumption
Challenge is related to difficulty
Difficulty depends on the possible tracks
Dificulty depends on the selected tracks
Approaches
Teleological vs. Ontogenetic
Personalisation
Shortest path
Avoid holes
Prefer walls
Results
Complexity
Number of different levels
Difficulty precision
Maze Generation
Shortest Path Avoid Holes Prefer Walls
Teleological Ontogenetic
KOM – Multimedia Communications Lab 24
Number of Different Levels
Runtime Comparison
Evaluation: Difficulty Adaptation
0
1000
2000
3000
4000
5000
6000
7000
8000
9x9 17x9 17x17 25x17
Grid
Binary Space Partition
Room Combine
Set-Holes
Evolutionary
0
200
400
600
800
1000
1200
9x9 17x9 17x17 25x17
Grid
Binary SpacePartition
Room Combine
Set-Holes
Evolutionary
Method/Size 9x9 17x9 17x17 25x17
Grid <1 <1 <1 <1
BS Partition <1 <1 <1 <1
Room Combine - <1 <1 <1
Set-Holes 3 30 242 817
Evolutionary 332 1086 3554 7554
Method/Size 9x9 17x9 17x17 25x17
Grid 48 737 993 1000
BS Partition 18 264 988 1000
Room Combine 0 24 96 895
Set-Holes 534 995 1000 1000
Evolutionary 1000 1000 1000 1000
KOM – Multimedia Communications Lab 25
Difficulty Metrics
Loss rate depends on the selected path
Same values for instability (𝒑𝒘𝒂𝒍𝒍 = 𝟎. 𝟗𝟗, 𝒑𝒇𝒓𝒆𝒆 = 𝟎. 𝟓)
Path 1 (left): Loss rate 69.4%
Path 2 (center): Loss rate 26.5%
Path 3 (right): Loss rate 7.1%
𝑤𝑚𝑎𝑥 = 100, 𝑓𝑑𝑒𝑐𝑟 = 0.7, 𝑑𝑚𝑎𝑥 = 2
𝑤𝑚𝑎𝑥 = 100, 𝑓𝑑𝑒𝑐𝑟 = 0.7, 𝑑𝑚𝑎𝑥 = 2, 𝑓𝑤𝑎𝑙𝑙 = 0.1
No terrain weights
KOM – Multimedia Communications Lab 27
Questions & Contact
KOM – Multimedia Communications Lab 28
References 1
[ACSM11] American College of Sports Medicine. Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory, Musculoskeletal, and Neuromotor Fitness in Apparently Healthy Adults: Guidance for Prescribing Exercise. Medicine and Science in Sports and Exercise, 43 (7), 1334- 1359.
[AHJS09] Atif Alamri, Heung-Nam Kim, Jongeun Cha, Abdulmotaleb El Saddik, Serious Games for Rehabilitation of Stroke Patients with Vibrotactile Feedback. International Journal of Computer Science in Sport, Volume 9/Special Issue, IACSS, 2009
[BBC+08] Kirk A. Brumels, Troy Blasius, Tyler Cortright, Daniel Oumedian, and Brent Solberg. Comparison of efficacy between traditional and video game based balance programs. Clinical Kinesiology: Journal of the American Kinesiotherapy Association, 62(4), December 2008.
[BBTB08] Tom Baranowski, Richard Buday, Debbe I. Thompson, and Janice Baranowski. Playing for real: Video games and stories for health-related behavior change. American Journal of Preventive Medicine, 34(1):74 – 82.e10, 2008.
[BHK+12] Michael Brach, Klaus Hauer, Oliver Korn, Robert Konrad, Sven Unkauf, Sandro Hardy, Stefan Göbel: Motivotion60+: Entwicklung eines computeranimierten Systems zum Kraft- und Balancetraining für Senioren. In: VDE-Verlag: AAL-Kongress 2012, Tagungsband, January 2012.
[BR08] Helmut Bonney and Joachim Rosenkranz. ADHS – Kritische Wissenschaft und therapeutische Kunst, chapter Training von Aufmerksamkeit und Impulskontrolle: Ein Baustein der multimodalen Behandlung von Grundschulkindern mit ADHS. Pilotstudie zur Prüfung der Anwendungseffekte einer Non-go-Lernsoftware, pages 228–244. Carl-Auer-Systeme Verlag, Heidelberg, 2008.
[Csik75] Mihaly Csikszentmihalyi : Beyond Boredom and Anxiety. Jossey-Bass: San Francisco, CA, 1975[EC10] European Commission. Special Eurobarometer 334 / Wave 72.3 – TNS Opinion & Social: Sport and Physical Activity. Technical report, March 2010.
[GeSM10] Gerling, K. M., Schild, J., & Masuch, M. (2010). Exergame Design for Elderly Users : The Case Study of SilverBalance, 66–69.
[GLN+12] Gerling, K. M., Livingston, I. J., Nacke, L. E., & Mandryk, R. L. (2012). Full-Body Motion-Based Game Interaction for Older Adults 1, 1873–1882.
KOM – Multimedia Communications Lab 29
References 2
[GGH13] Stefan Göbel, Michael Gutjahr, Sandro Hardy: Evaluation of Serious Games. In: Bredl, K. & Bösche, W. (ed. in preparation). , vol. Serious Digital Games, MUVE and MMORPG in Adult Education and Health Care: Research, Reviews, Case Studies, and Lessons Learned, IGI-Global, February 2013.
[GHS+11] Stefan Göbel, Sandro Hardy, Ralf Steinmetz, Jongeun Cha, Abdulmotaleb El Saddik: Serious Games zur Prävention und Rehabilitation. In: 4. Deutscher AAL-Kongress, 25.-26.01.2011 in Berlin: Demographischer Wandel - Assistenzsysteme aus der Forschung in den Markt, VDE Verlag GmbH, Berlin und Offenbach, January 2011. ISBN 978-3-8007-3323-1.
[GHW+10] Stefan Göbel, Sandro Hardy, Viktor Wendel, Florian Mehm, Ralf Steinmetz: Serious Games for Health - Personalized Exergames. In: Proceedings ACM Multimedia 2010, p. 1663-1666, October 2010. ISBN ISBN: 978-1-60558-933-6.
[HEGS11] Sandro Hardy, Abdulmotaleb El Saddik, Stefan Göbel, Ralf Steinmetz: Context Aware Serious Games Framework for Sport and Health. In: Medical Measurements and Applications Proceedings (MeMeA), 2011 IEEE International Workshop on, p. 248 -252, May 2011. ISBN 978-1-4244-9336-4.
[HGG+11] Sandro Hardy, Stefan Göbel, Michael Gutjahr, Josef Wiemeyer, Ralf Steinmetz:Adaptation Model for Indoor Exergames (accepted for publication). In: International Journal of Computer Science in Sport, Vol. 10, Special edition: Serious Games – Theory, Technology & Practice , November 2011.
[HGS13] Sandro Hardy, Stefan Göbel, Ralf Steinmetz: Adaptable and Personalized Game-based Training System for Fall Prevention (Technical Demo Paper). In: ACM New York, NY, USA ©2013 : MM '13 Proceedings of the 21st ACM international conference on Multimedia , p. 431-432 , October 2013. ISBN 978-1-4503-2404-5.
[HGWS12] Sandro Hardy, Stefan Göbel, Josef Wiemeyer, Ralf Steinmetz: Adaption und Personalisierung von digitalen spielerischen Trainingssystemen für die Sturzprävention. In: R. Byshko, T. Dahmen, M. Gratkowski, M. Gruber, J. Quintana, D. Saupe, M. Vieten, A. Woll: Sportinformatik 2012 : 9. Symposium der Sektion Sportinformatik der Deutschen Vereinigung für Sportwissenschaft vom 12.-14. Sept. 2012 in Konstanz : extended abstracts., KOPS Institutional Repository University of Konstanz, September 2012.
[HWHG14] Katrin Hoffmann, Josef Wiemeyer, Sandro Hardy, Stefan Göbel: Personalized adaptive control of training load in exergames from a sport-scientific perspective (accepted for publication). In: Gamedays2014, Proceedings of, Springer, LNCS, April 2014.
KOM – Multimedia Communications Lab 30
References 3
[KCBP08] Pamela M. Kato, Steve W. Cole, Andrew S. Bradlyn, and Brad H. Pollock. A video game
improves behavioral outcomes in adolescents and young adults with cancer: A randomized trial.
Pediatrics, 122(2):305–317, 2008.
[KW10] Annika Kliem and Josef Wiemeyer. Comparison of a traditional and a video game based balance
training program. International Journal of Computer Science in Sport, 9/ Special Edition:80–91, 2010.
[Malo82] T. W. Malone, Heuristics for designing enjoyable user interfaces: Lessons from computer games.
In Proceedings of the 1982 conference on human factors in computing systems, Gaithersburg, Maryland,
United States, 1982.
[MHAE11] Kazi Masudul Alam, Sandro Hardy, Aysha Akther, Abdulmotaleb El Saddik: SMS Text Based
Affective Haptic Application. In: Proceedings of Virtual Reality International Conference (VRIC 2011),
April 2011.
[MHGS11] Florian Mehm, Sandro Hardy, Stefan Göbel, Ralf Steinmetz: Collaborative Authoring of Serious
Games for Health. In: MM '11 Proceedings of the 19th ACM international conference on Multimedia , p.
807-808, ACM New York, NY, USA, December 2011. ISBN 978-1-4503-0616-4.
[Nac09] Lennart Nacke, Scientific Measurement of User Experience in Interactive Entertainment Blekinge
Institute of Technology School of Computing., 2009
[SHM07] J. Sinclair, P. Hingston, and M. Masek: Considerations for the design of exergames. In
Proceedings of the 5th international Conference on Computer Graphics and interactive Techniques in
Australia and Southeast Asia (Perth, Australia, December 01 - 04, 2007). GRAPHITE '07. ACM, New
York, NY, 289-295, 2007.
KOM – Multimedia Communications Lab 31
References 4
[SGYR09] T. Stach, T. C. Graham, J. Yim, R. E. Rhodes:. Heart rate control of exercise video games. In Proceedings of Graphics interface 2009 (Kelowna, British Columbia, Canada, May 25 - 27, 2009). ACM International Conference Proceeding Series, vol. 324. Canadian Information Processing Society, Toronto, Ont., Canada, 125-132, 2009.
[SW05] P. Sweetser, P. Wyeth: GameFlow: A Model for Evaluating Player Enjoyment in Games, ACM Computers in Entertainment, Vol. 3, No. 3, July 2005.
[WH13] Josef Wiemeyer, Sandro Hardy: Serious Games and motor learning - concepts, evidence, technology. In: Bredl, K. & Bösche, W. (ed. in preparation), vol. Serious Digital Games, MUVE and MMORPG in Adult Education and Health Care: Research, Reviews, Case Studies, and Lessons Learned, chap. Serious Digital Games, MUVE and MMORPG in Adult Education and Health Care: Research, Reviews, Case Studies, and Lessons Learned, IGI-Global, February 2013.
[WHGS10] Viktor Wendel, Sandro Hardy, Stefan Göbel, Ralf Steinmetz: Adaption und Personalisierung von Exergames. In: J. Wiemeyer, D. Link, R. Angert, B. Holler, A. Kliem, N. Roznawski, D. Schöberl, M. Stroß: Sportinformatik trifft Sporttechnologie: Abstractband zur Tagung der dvs-Sektion Sportinformatik und der deutschen interdisziplinären Vereinigung für Sporttechnologie, p. 97-99, Institut für Sportwissenschaft der Technischen Universität Darmstadt, September 2010.
[WHO10] Carissa Etienne and Anarfi Asamoa-Baah. The world health report: health systems financing: the path to universal coverage. WHO Press, 2010.
[WHO10-1] World Health Organisation, Global Recommendations on Physical Activity for Health, SBN: 9789241599979, 210
[YHL06] G. N. Yannakakis, J. Hallam, H. H. Lund: Comparative Fun Analysis in the Innovative Playware Game Platform. In Proceedings of the 1st World Conference for Fun’n Games, Preston, England, 2006
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