Health and Technology

, Volume 2, Issue 1, pp 17–31 | Cite as

Towards an avatar mentor framework to support physical and psychosocial treatments

  • P. FergusEmail author
  • A. El Rhalibi
  • C. Carter
  • S. Cooper
Original Paper


The clinical care of patients with chronic life-limiting conditions and terminal illness has improved. However, intense treatment regimens make patients feel isolated, particularly among young children and adolescents who require psychosocial care. Failure to address this issue can leave patients feeling depressed and isolated. Social networking and digital entertainment have helped to address some of these issues, particularly for house bound and long stay patients in a hospital. It has allowed patients to remain in contact with family and friends, express how they feel and find information about their condition. Nevertheless, these kinds of solutions are too general to support the specific psychosocial needs of patients. This paper builds on these technologies and explores the idea of improving communications between medical practitioners and patients using avatars (digital characters that have controllable expressions, animations and speech) in computer games to guide and encourage patients to comply with treatments, provide support, and elicit information about their well-being. We have successfully developed several prototype systems to evaluate the applicability of our approach.


Online games Avatar Home healthcare Data processing Measurement and monitoring Psychosocial care e-Health Wireless communications 



The authors would like to thank the anonymous reviewers for providing highly constructive reviews, without which the paper would not have reached its current form. The authors would especially like to thank Dr Kevin Southern and Dr Claire Glasscoe from Liverpool Alder Hey Children’s hospital and Prof. Alexandra Quittner from the University of Miami, for their valuable expertise and generous input into making this paper possible. The authors would also like to thank Lorna Bracegirdle for reading the paper and making valuable suggestions.


  1. 1.
    Miroballi Y, Garber E, Jia H, Zhou JJ, Alba L, Quittell LM, Angst D, Cabana M, Saiman L. “Infection control knowledge, attitudes, and practices among cystic fibrosis patients and their families,” Pediatric Pulmonology (Publicised Online First), 2011.Google Scholar
  2. 2.
    Rokach A, Parvini M. Experience of Adults and Children in Hospitals. Early Child Development and Care. 2011;181(5):707–15.CrossRefGoogle Scholar
  3. 3.
    Stein MB, Stein DJ. Social anxiety disorder. Lancet. 2008;371(9618):1115–25.CrossRefGoogle Scholar
  4. 4.
    Fleischman KM, Hains AA, Davies WH. Practitioner perceptions of peer relationships in adolescents with chronic pain. Journal of Child Health Care. 2011;15(1):50–8.CrossRefGoogle Scholar
  5. 5.
    Larsson G, Mattsson E, von Essen L. Aspects of quality of life, anxiety, and depression among persons diagnosed with cancer during adolescence: A long-term follow-up study. Eur J Cancer. 2010;46(6):1062–8.CrossRefGoogle Scholar
  6. 6.
    Stewart M, Letourneau N, Masuda JR, Anderson S, Cicutto L, McGhan S, Watt S. “Support Needs and Preferences of Young Adolescents With Asthma and Allergies: “Just No One Really Seems to Understand”,” Journal of Pediatric Nursing (Published Online First), 2011.Google Scholar
  7. 7.
    Ernst MM, Johnson MC, Stark LJ. Developmental and Psychosocial Issues in Cystic Fibrosis. Child and Adolescent Psychiatric Clinics in North America. 2010;19(2):263–83.CrossRefGoogle Scholar
  8. 8.
    Gold E. “Children’s Palliative Care in the Hospice and the Community,” in Palliative Nursing: Wiley-Blackwell, 2009, pp. 277–288.Google Scholar
  9. 9.
    Clark K, Bardwell WA, Arsenault T, DeTeresa R, Loscalzo M. Implementing touch-screen technology to enhance recognition of distress. Psycho-Oncology. 2009;18(8):822–30.CrossRefGoogle Scholar
  10. 10.
    Bill NS. Mobile computing: Looking to the future. Computer. 2011;44(5):28–9.CrossRefGoogle Scholar
  11. 11.
    Pempek TA, Yermolayeva YA, Calvert SL. College students’ social networking experiences on Facebook. J Appl Dev Psychol. 2009;30(3):227–38.CrossRefGoogle Scholar
  12. 12.
    Stenros J, Paavilainen J, Mayra F. Social Interaction in games. International Journal of Arts and Technology. 2011;4(3):342–58.CrossRefGoogle Scholar
  13. 13.
    Merabti M, Fergus P, Abuelma’atti O, Yu H, Judice C. Managing distributed networked appliances in home networks. Proc IEEE. 2008;96(1):166–85.CrossRefGoogle Scholar
  14. 14.
    Gregory R, Scott S, Donald W. Household demand for broadband internet service. Commun ACM. 2011;54(2):29–31.CrossRefGoogle Scholar
  15. 15.
    Istepanian RSH, Jovanov E, Zhang YT. Guest editorial introduction to the special section on M-Health: Beyond seamless mobility and global wireless health-care connectivity. IEEE Trans Inf Technol Biomed. 2004;8(4):405–14.CrossRefGoogle Scholar
  16. 16.
    Sixsmith A, Meuller S, Lull F, Klein M, Bierhoff I, Delaney S, Savage R, Mokhtari M, Khalil I, Bauchet J, Zhang D, Nugent C. “SOPRANO: An Ambient Assisted Living System for Supporting Older People at Home”, vol. 5597, Lecture Notes in Computer Science: Springer Berlin: Heidelberg, 2009, pp. 233–236.Google Scholar
  17. 17.
    Dwyer TJ, Elkins MR, Bye PT. The role of exercise in maintaining health in cystic fibrosis. Current Opinion in Pulmonary Medicine. 2011;17(6):455–60.Google Scholar
  18. 18.
    Staiano AE, Calvert SL. The promise of exergames as tools to measure physical health. Entertainment Computing. 2011;2(1):17–21.CrossRefGoogle Scholar
  19. 19.
    Weightman A, Preston N, Levesley M, Holt R, MonWilliams M, Clarke M, Cozens A, Bhakta B. Home-based computer-assisted upper limb exercise for young children with cerebral palsy: A feasibility study investigating impact on motor control and functional outcome. Journal of Rehabilitation Medicine. 2011;43(4):359–63.CrossRefGoogle Scholar
  20. 20.
    Council on Clinical Information Technology. Health information technology and the medical home. Journal of the American Academy of Pediatrics. 2011;127(5):978–82.Google Scholar
  21. 21.
    Fergus P, Taylor M, Haggerty J, Bracegirdle L, Merabti M. “Next Generation Body Area Networks and Smart Environments for Healthcare,” in Smart healthcare Applications and Services: Developments and Practices, C. Rocker and M. Ziefle, Eds.: IGI, 2011, pp. 46–74.Google Scholar
  22. 22.
    Lee M, Kang S. “Multimedia Room Gateway for Integration and Management of Distributed Medical Devices,” presented at Workshop on High Confidence Medical Device Software and Systems. Philadelphia, PA, USA: University of Pennsylvania; 2005.Google Scholar
  23. 23.
    Stange K, Nutting P, Miller W, Jaen C, Crabtree B, Flocke S, Gill J. Defining and measuring the patient-centered medical home. Journal of General Internal Medicine. 2011;25(6):601–12.CrossRefGoogle Scholar
  24. 24.
    Nicholas DB, Lach L, King G, Scott M, Boydell K, Sawatzky BJ, Reisman J, Schippel E, Young NL. “Contrasting internet and face-to-face groups for children with chronic health conditions: Outcomes and participant experiences”. International Journal of Qualitative Methods. 2010;9(1):106–21.Google Scholar
  25. 25.
    Sanders C, Rogers A, Gardner C, Kennedy A. Managing ‘difficult emotions’ and family life: exploring insights and social support within online self-management training. Chronic Illness. 2011;7(2):134–46.CrossRefGoogle Scholar
  26. 26.
    Lin K, Lu H. Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Comput Hum Behav. 2011;27(3):1152–61.CrossRefGoogle Scholar
  27. 27.
    Livingstone S. Taking risky opportunities in youthful content creation: teenagers’ use of social networking sites for intimacy, privacy and self-expression. New Media and Society. 2008;10(3):393–411.CrossRefGoogle Scholar
  28. 28.
    ITU, “The World in 2010: Facts and Figures,” ITU, Statistical Report October 2010.Google Scholar
  29. 29.
    Davis MA, Quittell AL, Stack CM, Yang MCK. Controlled evaluation of the STARBRIGHT CD-ROM program for children and adolescents with cystic fibrosis. Journal of Pediaric Psychology. 2004;29(4):259–67.CrossRefGoogle Scholar
  30. 30.
    Marciel KK, Saiman L, Quittell LM, Dawkins K, Quittner AL. Cell phone intervention to improve adherence: Cystic fibrosis care team, patient, and parent perspectives. Pdeiatr Pulmonol. 2010;45(2):157–64.CrossRefGoogle Scholar
  31. 31.
    Frost J, Massagli M. PatientsLikeMe the case for a data-centered patient community and how ALS patients use the community to inform treatment decisions and manage pulmonary health. Chronic Respiratory Disease. 2009;6(4):225–9.Google Scholar
  32. 32.
    Metzger MJ, Flanagin AJ. Using Web 2.0 Technologies to Enhance Evidence-Based Medical Information. J Heal Commun. 2011;16(1):45–58.CrossRefGoogle Scholar
  33. 33.
    Allen D, Lollar DJ, Andresen EM. Disability and Maternal and Child Health Public Health Perspectives on Disability. New York: Springer; 2011. p. 151–61.CrossRefGoogle Scholar
  34. 34.
    Shrank WH, Choudhry NK, Swanton K, Jain S, Greene JA, Harlam B, Patel KP. Variations in Structure and Content of Online Social Networks for Patients With Diabetes. Arch Intern Med. 2011;171(17):1589–91.CrossRefGoogle Scholar
  35. 35.
    Dannecker KL, Petro SA, Melanson EL, Browning RC. Accuracy of fitbit activity monitor to predict energy expenditure with and without classification of activities. Medicine & Science in Sports & Exercise. 2011;43(5):62.CrossRefGoogle Scholar
  36. 36.
    Smith JM. “The doctor will see you ALWAYS,” Spectrum. IEEE. 2011;48(10):56–62.Google Scholar
  37. 37.
    Stuckey M, Fulkerson R, Read E, Russell-Minda E, Munoz C, Kleinstiver P, Petrella R. Remote Monitoring Technologies for the Prevention of Metabolic Syndrome: The Diabetes and Technology for Increased Activity (DaTA) Study. Journal of Diabetes Science and Technology. 2011;5(4):936–44.Google Scholar
  38. 38.
    Williams RE, Bauman WA, Spungen AM, Vinnakota RR, Farid RZ, Galea M, Korsten MA. “SmartPill technology provides safe and effective assessment of gastrointestinal function in persons with spinal cord injury (Published First Online),” Spinal Cord, 2011.Google Scholar
  39. 39.
    Chin-Teng L, Kuan-Cheng C, Chun-Ling L, Chia-Cheng C, Shao-Wei L, Shih-Sheng C, Bor-Shyh L, Hsin-Yueh L, Ray-Jade C, Yuan-Teh L, Li-Wei K. An intelligent telecardiology system using a wearable and wireless ECG to detect atrial fibrillation. IEEE Trans Inf Technol Biomed. 2010;14(3):726–33.CrossRefGoogle Scholar
  40. 40.
    Fairclough SH. Fundamentals of physiological computing. Interacting with Computers. 2009;21(1–2):133–45.CrossRefGoogle Scholar
  41. 41.
    Kwon H, Cho J, Lee E. EEG asymmetry analysis of the left and right brain activities during simple versus complex arithmetic learning. J Neurother. 2009;13(2):109–16.CrossRefGoogle Scholar
  42. 42.
    Burns A, Doheny EP, Greene BR, Foran T, Leahy D, O’Donovan K, McGrath MJ. “SHIMMER: An extensible platform for physiological signal capture,” in The IEEE Conference on Engineering in Medicine and Biology Society (EMBC). Buenos Aires: IEEE Computer Society; 2010. p. 3759–62.Google Scholar
  43. 43.
    Postolache O, Girao PS, Ribeiro M, Guerra M, Pincho J, Santiago F, Pena A. “Enabling telecare assessment with pervasive sensing and Android OS smartphone,” in IEEE International Workshop on Medical Measurements and Applications Proceedings (MeMeA) Lisbon. Portugal: IEEE Computer Society; 2011. p. 288–93.Google Scholar
  44. 44.
    Sarasohn-Kahn J. “How Smartphones are changing Health Care for Consumers and Providers,” California Healthcare Foundation White Paper 2010.Google Scholar
  45. 45.
    Dwyer T, Alison JA, McKeough ZJ, Daviskas E, Bye PTP. “Effects of exercise on respiratory flow and sputum properties in cystic fibrosis (Published Online First),” Chest, 2010.Google Scholar
  46. 46.
    Morton AR, Fitch KD. Australian association for exercise and sports science position statement on exercise and asthma. Journal of Science and Medicine in Sport. 2011;14(4):312–6.CrossRefGoogle Scholar
  47. 47.
    Roberts J. Patient compliance: New media tools to help patients take their medications. The Journal of the European Medical Writers Association. 2009;18(4):218–20.Google Scholar
  48. 48.
    van den Noort J, Harlaar SJ. Evaluation of clinical spasticity assessment in Cerebral palsy using inertial sensors. Gait & Posture. 2009;30(2):138–43.CrossRefGoogle Scholar
  49. 49.
    Zhang SHJ, Zhou H. An interactive Internet-based system for tracking upper limb motion in home-based rehabilitation. Medical and Biological Engineering and Computing. 2008;46(3):241–9.CrossRefGoogle Scholar
  50. 50.
    Rosenhahn B, Brox T, Seidel H. “Scaled Motion Dynamics for Markerless Motion Capture,” in IEEE Conference on Computer Vision and Pattern Recognition. Hyatt Regency Hotel, Minneapolis, Minnesota: IEEE Computer Society; 2007. p. 1–8.Google Scholar
  51. 51.
    Sundaresan A, Chellappa R. “Markerless motion capture using multiple cameras,” in IEEE Conference on Computer Vision for Interactive and Intelligent Environments. Lexington, Kentucky, USA: IEEE Computer Society; 2005. p. 15–26.Google Scholar
  52. 52.
    Zhou H, Stone T, Hu H, Harris N. Use of multiple wearable inertial sensors in upper limb motion tracking. Medical Engineering & Physics. 2008;30(1):123–33.CrossRefGoogle Scholar
  53. 53.
    Brostrom E, Hagelberg S, Haglund-Akerlind Y. Effect of joint injections in children with Juvenile Idiopathic Arthritis: evaluation by 3D-Gait Analysis. Acta Paediatrica. 2004;93(7):906–10.CrossRefGoogle Scholar
  54. 54.
    Zheng H, Black ND, Harris ND. Position-sensing technologies for movement analysis in stroke rehabilitation. Medical and Biological Engineering and Computing. 2005;43(4):413–20.CrossRefGoogle Scholar
  55. 55.
    Zhou H, Hu H. Human motion tracking for rehabilitation—A Survey. Biomedical Signal Processing and Control. 2007;3(1):1–18.CrossRefGoogle Scholar
  56. 56.
    Hermann C. Psychological interventions for chronic pediatric pain: state of the art, current developments and open questions. Pain Management. 2011;1(5):473–83.CrossRefGoogle Scholar
  57. 57.
    Finkelstein J, Cabrera MR, Hripcsak G. Internet-Based Home Asthma Telemonitoring: Can patients handle the technology. Chest. 2000;117(1):148–55.CrossRefGoogle Scholar
  58. 58.
    Watt PM, Clements B, Devadason SG, Chaney GM. Funhaler spacer: improving adherence without compromising delivery. Arch Dis Child. 2003;88(7):579–81.CrossRefGoogle Scholar
  59. 59.
    Burgess SW, Sly PD, Cooper DM, Devadason SG. Novel spacer device does not improve adherence in childhood asthma. Pediatr Pulmonol. 2007;42(8):736–9.CrossRefGoogle Scholar
  60. 60.
    Lacey G, Donncha R, Derek C, Derek Y. Mixed-Reality Simulation of Minimally Invasive Surgeries. IEEE Multimedia Magazine. 2007;14(4):76–87.CrossRefGoogle Scholar
  61. 61.
    Laganiere R, Gilbert S, Roth G. Robust object pose estimation from feature-based stereo. IEEE Trans Instrum Meas. 2006;55(4):1270–80.CrossRefGoogle Scholar
  62. 62.
    Riva G, Bacchetta M, Cesa G, Conti S, Molinari E. The use of VR in the treatment of Eating Disorders. Stud Health Technol Inform. 2004;99:121–63.Google Scholar
  63. 63.
    Riva G, Botella C, Castelnuovo G, Gaggioli A, Mantovani F, Molinari E. Cybertherapy in Practice: The VEPSY Updated Project. Stud Health Technol Inform. 2004;99:3–14.Google Scholar
  64. 64.
    Riva G, Gaggioli A, Villani D, Preziosa A, Morganti FF, Strambi L, Corsi R, Faletti G, and Vezzadini L. “An Open-Source virtual reality platform for clinical and research applications,” presented at Human-Computer Interaction International, Beijing International Convention Center, Beijing, P.R. China, 2007.Google Scholar
  65. 65.
    Kostanski M, Gullone E. The Impact of Teasing on Children’s Body Image. J Child Fam Stud. 2007;16(3):307–19.CrossRefGoogle Scholar
  66. 66.
    Harari D, Furst M, Kiryati N, Caspi A, Davidson M. A computer-based method for the assessment of body-image distortions in Anorexia-Nervosa Patients. IEEE Trans Inf Technol Biomed. 2001;5(4):311–9.CrossRefGoogle Scholar
  67. 67.
    Riva G, Bacchetta M, Baruffi M, Molinari E. Virtual-reality-based multidimensional therapy for the treatment of body image disturbances in binge eating disorders: A preliminary controlled study. IEEE Trans Inf Technol Biomed. 2002;6(3):224–34.CrossRefGoogle Scholar
  68. 68.
    Hilton D, Cobb S, Pridmore T, Gladman J, Edmans J, Brahnam S, and Jain L. “Development and evaluation of a mixed reality system for stroke rehabilitation advanced computational intelligence paradigms in healthcare 6. Virtual reality in psychotherapy, rehabilitation, and assessment,” vol. 337, Studies in Computational Intelligence: Springer Berlin / Heidelberg, 2011, pp. 193–228.Google Scholar
  69. 69.
    Riva G. The key to unlocking the virtual body: Virtual reality in the treatment of obesity and eating disorders. Journal of Diabetes Science and Technology. 2011;5(2):283–92.Google Scholar
  70. 70.
    Modahl M. “Tablets set to change medical practice,” Quantia Communications Inc. 15 June 2011.Google Scholar
  71. 71.
    El-Rhalibi A, Merabti M, Carter C, Dennet S, Cooper S, Arif Sabri M, Fergus P. 3D Java web-based games development and deployment. International Journal on Communication Technologies. 2009;2(3–4):221–30.Google Scholar
  72. 72.
    Carter C, El Rhalibi A, Merabti M, Price M. “Homura and Net-Homura: The creation and web-based deployment of cross-platform 3D games,” in International Conference on Ultra Modern Telecommunications & Workshops, 2009 ICUMT ’09. Liverpool, UK: IEEE Computer Society; 2009. p. 1–8.Google Scholar
  73. 73.
    Kucklich J. “Precarious Playbour: Modders and the Digital Games Industry,” International Journal on Fibreculture, 2005;1(5).Google Scholar
  74. 74.
    Fergus P, Llewellyn-Jones D, Merabti M, El Rhalibi A. “Infinitely Adaptable Gaming: Harnessing the Power of Distributed Network Environments and Component Reuse,” presented at Forth Annual International Conference in Computer Game Design and Technology (GDTW 2006). Liverpool: FACT Center; 2006.Google Scholar
  75. 75.
    Ortega-Rodriguez P. “How is disbelief suspended?” Journal of Film-Philosophy, 2003;7(46).Google Scholar
  76. 76.
    Freud S. Jokes and their relation to the unconscious Volume 1960, Part 1, vol. 1960: Norton, 1908/1960.Google Scholar
  77. 77.
    Carter C, Cooper S, El Rhalibi A, and Merabti M. “The application of MPEG-4 compliant animation to a modern games engine and animation framework,” in Motion in Games, vol. 6459, Lecture Notes in Computer Science: Springer Berlin / Heidelberg, pp. 326–338.Google Scholar
  78. 78.
    Carter C, El Rhalibi A, Merabti M. “Networking Middleware and Online-Deployment Mechanisms for Java-Based Games,” presented at the 6th International Conference in Computer Game Design and Technology. UK: Liverpool; 2008.Google Scholar
  79. 79.
    Schroder M, Trouvain J. The German Text-to-Speech Synthesis System MARY: A Tool for Research, Development and Teaching. International Journal of Speech Technology. 2003;6:365–77.CrossRefGoogle Scholar
  80. 80.
    Rosis FD, Pelachaud C, Poggi I, Carofiglio V, Carolis BD. From Greta’s mind to her face: modelling the dynamics of affective states in a conversational embodied agent. Int J Hum Comput Stud. 2003;59(1–2):81–118.CrossRefGoogle Scholar
  81. 81.
    Koray B. “Xface: MPEG-4 based open source toolkit for 3D Facial Animation,” in Proceedings of the working conference on Advanced visual interfaces. Gallipoli, Italy: ACM; 2004.Google Scholar
  82. 82.
    Wiskott L, Fellous JM, Kruiger N, von der Malsburg C. Face recognition by elastic bunch graph matching. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1997;19(7):775–9.CrossRefGoogle Scholar
  83. 83.
    Wright J, Yang AY, Ganesh A, Sastry SS, Yi M. Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2009;31(2):210–27.CrossRefGoogle Scholar
  84. 84.
    Li Z, Horain P, Pez A, Pelachaud C. “Statistical Gesture Models for 3D Motion Capture from a Library of Gestures with Variants,” in Gesture in Embodied Communication and Human-Computer Interaction. Bielefeld, Germany: Springer; 2010.Google Scholar
  85. 85.
    Merabti M, Fergus P, Abuelma’atti O, Yu H, Judice C. Managing distributed networked appliances in home networks. Proceedings of the IEEE Journal. 2008;96(1):166–85.CrossRefGoogle Scholar
  86. 86.
    Cloete T, and Scheffer C. “Repeatability of an off-the-shelf, full body inertial motion capture system during clinical gait analysis,” presented at Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE.Google Scholar
  87. 87.
    Klein M. XML, RDF, and Relatives. IEEE Intell Syst. 2001;16(2):26–8.CrossRefGoogle Scholar
  88. 88.
    Bizer C, Heath T, Berners-Lee T. Linked Data—The Story So Far. International Journal on Semantic Web and Information Systems. 2009;5(3):1–22.CrossRefGoogle Scholar
  89. 89.
    Bratko I. Prolog: Programming for Artificial Intelligence, 2nd ed: Addison Wesley, 1994.Google Scholar
  90. 90.
    Barbieri DF, Braga D, Ceri S, Della Valle E, Grossniklaus M. C-SPARQL: A Continuous Query Language for RDF Data Streams. International Journal of Semantic Computing. 2010;4(1):3–25.zbMATHCrossRefGoogle Scholar
  91. 91.
    Clifford GD, Azuaje F, and McSharry P. Advanced Methods And Tools for ECG Data Analysis, 1st ed: Artech House Publishers, 2006.Google Scholar
  92. 92.
    Della Valle E, Ceri S, van Harmelen F, Fensel D. It’s a Streaming World! Reasoning upon Rapidly Changing Information. IEEE Intell Syst. 2009;24(6):83–9.CrossRefGoogle Scholar
  93. 93.
    Barvieri DF, Braga D, Ceri S, Della Valle E, Huang Y, Tresp V, Rettinger A, Wermser H. Deductive and inductive Stream Reasoning for Semantic Social Media Analytics. IEEE Intell Syst. 2010;25(6):32–41.CrossRefGoogle Scholar
  94. 94.
    Della Valle E, Ceri S, van Harmelen F, Fensel D. It’s a Streaming World! Reasoning Upon Rapidly Changing Information. IEEE Intelligent Systems vol. 2009;24(6):83–9.CrossRefGoogle Scholar
  95. 95.
    Homura A high level game development tool and framework, Accessed: 21st of November 2011
  96. 96.
    Carter C, El Rhalibi A, Merabti M, Price M. Networking Middleware and Online-Deployment Mechanisms for Java-based Games. Transactions on Edutainment II. 2009;5660(2):19–32.CrossRefGoogle Scholar
  97. 97.
    Carter C, El Rhalibi A, Merabti M, Taleb-Bendiab A. “NHUGS: Towards scalability testing for MMOGs within an extensible, open architecture,” in The 11th Annual Postgraduate Symposium on The Convergence of Telecommunications, Networking and Broadcasting. Liverpool: Liverpool John Moores University; 2010.Google Scholar
  98. 98.
    El Rhalibi A, Carter C, Cooper S, Merabti M, Price M. Charisma: High Performance Web Based MPEG-4 Compliant Animation Framework. ACM Comput Entertain. 2010;8(2):8.Google Scholar
  99. 99.
    Fergus P, Kifayat K, Cooper S, Merabti M, El Rhalibi A. “A Framework for Physical Health Improvement using Wireless Sensor Networks and Gaming,” presented at The 3rd International Conference on PervasiveHealth. UK: London; 2009.Google Scholar
  100. 100.
    Fergus P, Kifiyat K, Merabti M, Taleb-bendiab A, El Rhalibi A. “Remote Physiotherapy Treatments using Wireless Body Sensor Networks,” presented at The 5th International Wireless Communications and Mobile Computing Conference. Germany: Leipzig; 2009.Google Scholar
  101. 101.
    Carter C. MSc Thesis: The development of a Networking Middleware and Online Deployment Mechanism for Java Based Games: Liverpool John Moores University, 2008.Google Scholar
  102. 102.
    Dennett C. MSc Thesis: Development of a High Level Game Development Environment: Liverpool John Moores University, 2007.Google Scholar
  103. 103.
    Carter C. PhD Thesis: An Extensible Test bed Architecture and Topological Analysis of the Scalability of Hybrid-P2P Massively Multiplayer Online Games: Liverpool John Moores University, 2011.Google Scholar
  104. 104.
    Cooper S. PhD Thesis: DISE: A Game Technology-based Digital Interactive Storytelling Framework: Liverpool John Moores University, 2011.Google Scholar
  105. 105.
    Arshad F, Partington L, El Rhalibi A. “GAC—Gaming Assessment for Children,” in International Conference on Multidisciplinary Information Sciences and Technology. Spain: Merida; 2006.Google Scholar
  106. 106.
    Fergus P, and Arshad F. “Evaluating remote mobile technology,” HiNOW, 2009;4(2).Google Scholar
  107. 107.
    Fergus P, Hanley P, Taylor M, Haggerty J, and Bracegirdle L. “A wireless body sensor platform to detect progressive deterioration in the musculoskeletal systems,” Liverpool John Moores University 2011.Google Scholar
  108. 108.
    Duarte R, El Rhalibi A, Carter C, Merabti M, Cooper S. “An MPEG-4 Compliant Quadric-Based Surface Adaptive LOD,” in The 12th Annual Post Graduate Symposium on the Convergence of Telecommunications, Networking and Broadcasting (PGNet2011). Liverpool: Liverpool John Moores University; 2011.Google Scholar
  109. 109.
    Liu G, Xu M, Pan Z, and El Rhalibi A. “Human motion generation with multifactor models,” Journal of Computer Animation and Virtual Worlds, 22(4):351–359.Google Scholar
  110. 110.
    Xiang N, Zhou X, Xu M, El Rhalibi A, Zhang M, Wu Y. UEGM: Uncertain Emotion Generator under Multi-Stimulus. Journal of Computer Animation and Virtual Worlds. 2011;22(1–2):141–9.CrossRefGoogle Scholar
  111. 111.
    Fergus P, Haggerty J, Taylor M, and Bracegirdle L. “Towards a whole body sensing platform for healthcare applications” in Whole Body Interaction, D. England, Ed.: Springer, 2011, pp. In Press.Google Scholar
  112. 112.
    Merabti M, Fergus P, Abuelma’atti O, Heather Y, Judice C. Managing distributed networked appliances in home networks. Proc IEEE. 2008;96(1):166–85.CrossRefGoogle Scholar

Copyright information

© IUPESM and Springer-Verlag 2012

Authors and Affiliations

  • P. Fergus
    • 1
    Email author
  • A. El Rhalibi
    • 1
  • C. Carter
    • 1
  • S. Cooper
    • 1
  1. 1.School of Computing and Mathematical SciencesLiverpool John Moores UniversityLiverpoolUK

Personalised recommendations