Digital Entertainment Laboratory 

 Overview

 

What we see and hear influence how we feel, think, and act

 

Digital technologies today are driven by entertainment applications.  Each new generation of digital technology brings paradigm shifting digital entertainment experiences and also reduces the costs, thus enabling their application into other domains.  Applications abound not only in entertainment, but education, business, health (especially mental health), and commerce. 

The digital entertainment laboratory uses media, interactive media (including video games and virtual reality), and robotics to understand the mind – body relationship and create engaging and transformative experiences.  Towards this end, the laboratory includes real-time biometric analysis including heart-rate variability, galvanic skin response, and electroencephalogram (EEG) to better understand how interactive media experiences influence psychophysiology.  By designing media that engages the mind, and observing conscious and subconscious responses, we can better understand a person’s worldview and customize experiences that facilitate greater self-awareness and insight.

 

In addition to digital media forms, the laboratory also specializes in social robotics, internet of things, and immersive multimedia environments such as ambisonic sound.  The Lab has its origins in the Multimedia Innovation Centre, a leading-edge think tank and research center focused on digital entertainment established in 1999.  Since inception, the laboratory has received over $50M HKD in research funding and consultancy projects. 

  

Team Members

  • Gino Yu, Lab leader

  • Anthony Kong, Co-leader

  • Johan Hoorn, Co-leader

  • William Liang, Co-leader

  • Stephan Wang, Co-leader

  • Giovanni Lion, Research Assistant

  • Tesfa Yohannes, Research Assistant

 

Research and Design Outputs

​2021

  • Huang, I. S, & Hoorn. J. F. (2021). Does the robot show empathy with me? Talking vs. musical robot. 9th Congress of the International Association of Societies of Design Research (IASDR ’21), June 15 – 17, 2021, Hong Kong SAR.

  • Portegies, T. C., Konijn, E. A., & Hoorn, J. F. (2021). How embodied robots can achieve better self-help adherence than screen-based iCBT. Technology, Mind, and Society, APA Conference 2021. Abstract ID Number: 268

  • Duan, E. Y., Yoon, J. M., Liang, E. Z., & Hoorn, J. F. (2021). Self-disclosure to a robot: Only for those who suffer the most. Preprints 2021, preprints-42978 (doi: 10. 1)

  • Hoorn, J. F., Huang, I. S., Konijn, E. A., & Van Buuren, L. (2021). Robot tutoring of multiplication: over one-third learning gain for most, learning loss for some. Robotics, 10(1), 16. doi: 10.3390/robotics10010016

  • Duan, E. Y., Yoon, J. M., Liang, E. Z., & Hoorn, J. F. (2021). Self-disclosure to a robot: Only for those who suffer the most. Robotics. Accepted for publication.

  • Van Kemenade, M. A. M., Konijn, E. A., & Hoorn, J. F. (2021). Can we leave care to robots? An explorative investigation of the attitudes of care professionals regarding healthcare robots. COJ Robotics and Artificial Intelligence, 1(3), COJRA.000514.2021.

  • Kong, P. K., Oh, J., & Lam, W. M. T. (2021). Face Mask Effects During COVID-19: Perspectives of Managers, Practitioners, and Customers in the Hotel Industry. International Hospitality Review, Special Issue. https://doi.org/10.1108/IHR-07-2020-0025

  • Oh, J., & Kong, P. K. (2021) VR and Nostalgia: Using animation in theme parks to enhance visitor engagement, Journal of Promotion Management  (Accepted/In press)

  • Wang, K., Yap, L. W., Gong, S., Wang, R., Wang, S. J. & Cheng, W., 1 Feb 2021, Nanowire‐Based Soft Wearable Human-Machine Interfaces for Future Virtual and Augmented Reality Applications, In: Advanced Functional Materials. p. 1-27 27 p., 2008347. (OPUS listed, IF: 18.808)

  • Kumar, P.A., Lee, K.P., Wang, S.J., 2021. Eco Design for Medical Devices - Barriers, Opportunities and Principles of Eco-Effective Design. Cleaner Production (IF: 7.246, Major Revision)

  • Feng, H.M., Ma, Y., Li, Z.J., Zhang, S.J., Wang, X., Wang, S.J., Lee, K.P., 2021. The correlation between microstructure and mechanics of the adult cervical articular process area through micro-finite element model evaluations. Journal of the Mechanical Behavior of Biomedical Materials (IF: 3.902, Minor Revision)

  • Feng, H.M., Wang, S.J., Zhang, S.J., Ma, Y., Li, Z.J., 2021. The correlation of regional microstructure and mechanics of the cervical articular process in adults. Biomaterials (IF: 7.09, Minor Revision)

  • He, Z.J., Qi, Z., Liu, H.C., Wang, K.Y., Roberts, L., Liu, J.Z., Liu, Y.L., Wang, S.J., Cook, M.J., Simon, G.P., Qiu, L., and Li, D., 2021. Highly stretchable ultrasoft graphene cellular network for mechanical detection of skeletal muscle activities. National Science Review (IF: 16.693, Under Review)

  • Xie, H. A., Ho, J. C. F. & Wang, S. J., Apr 2021, Data City: Leveraging Data Embodiment Towards Building the Sense of Data Ownership (Best paper award), Interactivity and Game Creation - 9th EAI International Conference, ArtsIT 2020, Proceedings. Brooks, A., Brooks, E. I. & Jonathan, D. (eds.). Switzerland: Springer Nature Switzerland AG, p. 365-378 14 p. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; vol. 367 LNICST)

  • Arun Kumar, P. & Wang, S. J., Apr 2021, The Design Intervention Opportunities to Reduce Procedural-Caused Healthcare Waste Under the Industry 4.0 Context – A Scoping Review, Interactivity and Game Creation - 9th EAI International Conference, ArtsIT 2020, Proceedings. Brooks, A., Brooks, E. I. & Jonathan, D. (eds.). Springer Nature Switzerland AG, p. 446-460 15 p. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; vol. 367 LNICST)

  • Galdon, F., Hall, A., Wang, S.J., 2021. Designing trust in highly automated virtual assistants: A taxonomy of levels of autonomy.Artificial Intelligence in Industry 4.0: A Collection of Innovative Research Case-studies. Springer. (Published, not included in OPUS records)

2020

  • Hoorn, J. F. (2020a). Theory of robot communication: I. The medium is the communication partner. International Journal of Humanoid Robotics, 17(6), 2050026. doi: 10.1142/S0219843620500267

  • Hoorn, J. F. (2020b). Theory of robot communication: II. Befriending a robot over time. International Journal of Humanoid Robotics, 17(6), 2050027. doi: 10.1142/S0219843620500279

  • Konijn, E. A., & Hoorn, J. F. (2020). Differential facial articulacy in robots and humans elicit different levels of responsiveness, empathy, and projected feelings. Robotics, 9(4), 92. doi: 10.3390/robotics9040092

  • Konijn, E. A., & Hoorn, J. F. (2020). Robot tutor and pupils’ educational ability: Teaching the times tables. Computers & Education, 157, 103970. doi: 10.1016/j.compedu.2020.103970

  • Konijn, E. A., & Hoorn, J. F. (2020). Use of communication robots in healthcare. In J. van den Bulck, E. Scharrer, D. Ewoldson, & M.-L. Mares (Ed.), The international encyclopedia of media psychology (pp. 1879-1886). New York: Wiley. doi: 10.1002/9781119011071.iemp0317

  • Hoorn, J. F. & Portegies, T. C. (2020). iCBT Robot (Tech. Rep.). Amsterdam: Vrije Universiteit. Hong Kong: The Hong Kong Polytechnic University

  • Huang, I. S., & Hoorn, J. F. (2020). Bioloid Robot Teaching Multiplications (Tech. Rep.). Hong Kong: The Hong Kong Polytechnic University

  • Chapman, D., and Wang, S.J., 2020. Individual Trace in Knowledge Space-A Novel Design Approach for Human-Systems Interaction. In 2nd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET-AI 2020, pp. 219-224. Springer, 2020. (Published, not included in OPUS records)

  • Yu, G., The Eastern and Western Framing of Reality and Resulting Responses to COVID-19, International Meaning Conference, July 25, 2020

  • G. Yu,  Goertzel B., Suárez-Madrigal A., (2020) Guiding Symbolic Natural Language Grammar Induction via Transformer-Based Sequence Probabilities. In: Goertzel B., Panov A., Potapov A., Yampolskiy R. (eds) Artificial General Intelligence. AGI 2020. Lecture Notes in Computer Science, vol 12177. Springer, Cham. https://doi.org/10.1007/978-3-030-52152-3_16