Skip to main content
Log in

The Impact of a Custom Electromyograph (EMG) Controller on Player Enjoyment of Games Designed to Teach the Use of Prosthetic Arms

  • Published:
The Computer Games Journal

Abstract

Using electromyography (EMG) for physical therapy is not a new field, but applying it to the game based training for kids who need prosthetic arms to train both use and muscle strength is. The ability to bring fun training games to this demographic of disability gamers is potentially life changing. In an effort to support the training of these children a number of training games were developed. These initial games replace traditional button presses with flex controls using a custom game controller developed specifically for this task. Due to cost, and other factors, kids are often left without prosthetics until they are adults and the rejection rates for adults can be quite high, so the need for these games to not only train but to also be fun and engaging is paramount. This research explores the impact of using a custom EMG controller in place of a keyboard on the usability and user experience of an entertaining training game. Initial user sessions with child users of prosthetics indicate usability scores in a range of 75–85 for most games and moderately high user experience scores (GUESS scores of 40–55). Further comparisons conducted with undergraduate students suggest significantly higher GUESS scores for games where the flex controller is used to control the arms of the player avatar. While mixed, the results of this study indicate a mostly positive impact from the novel nature of using a custom flex controller, while there are indications that sound game design and supportive narrative still matters when developing custom controllers for training or entertainment purposes. Future games and game design for these controllers will utilize the successful design strategies applied by the games tested in this study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Anderson, M. L. (2003). Embodied cognition: A field guide. Artificial Intelligence, 149(1), 91–130.

    Article  MathSciNet  Google Scholar 

  • Anderson, F., & Bischof, W. F. (2014). Augmented reality improves myoelectric prosthesis training. International Journal on Disability and Human Development, 13(3), 349–354.

    Article  Google Scholar 

  • Aung, Y. M., & Al-Jumaily, A. (2011). Development of augmented reality rehabilitation games integrated with biofeedback for upper limb. In Proceedings of the 5th international conference on rehabilitation engineering & assistive technology (p. 51). Singapore Therapeutic, Assistive & Rehabilitative Technologies (START) Centre.

  • Bangor, A., Joseph, K., Sweeney-Dillon, W., Stettler, G., & Pratt, J. (2013). Using the SUS to help demonstrate usability’s value to business goals. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 57(1), 202–205. https://doi.org/10.1177/1541931213571045.

    Article  Google Scholar 

  • Bidiss, E. A., & Chau, T. T. (2007). Upper limb prosthesis use and abandonment: A survey of the last 25 years. Prosthetics and Orthotics International, 31(3), 236–257.

    Article  Google Scholar 

  • Bitzer, S., & Van Der Smagt, P. (2006). Learning EMG control of a robotic hand: towards active prostheses. Robotics and automation, 2006. ICRA 2006. Proceedings 2006 IEEE international conference on (pp. 2819–2823).

  • Brooke, J. (1996). SUS-A quick and dirty usability scale. In B. W. Thomas, B. Weerdmeester, & I. L. McClelland (Eds.), Usability evaluation in industry (pp. 189–194). London: Taylor & Francis.

    Google Scholar 

  • Brooke, J. (2013). SUS: A retrospective. Journal of Usability Studies, 8(2), 29–40. Retrieved October 15, 2015, from http://uxpajournal.org/wp-content/uploads/pdf/JUS_Brooke_February_2013.pdf.

  • Conati, C., Chabbal, R., & Maclaren, H. (2003). A study on using biometric sensors for monitoring user emotions in educational games. In Workshop on assessing and adapting to user attitudes and affect: Why, when and how.

  • Converse, H., Ferraro, T., Jean, D., Jones, L., Mendhiratta, V., Naviasky, E., et al. (2013). An EMG biofeedback device for video game use in forearm physiotherapy. In SENSORS, 2013 IEEE (pp. 1–4). IEEE.

  • Dombrowski, M., Smith, P., & Buyssens, R. (2016). Utilizing digital game environments for training prosthetic use. In International conference on virtual, augmented and mixed reality (pp. 481–489).

  • Ekvall, S., & Kragic, D. (2005). Grasp recognition for programming by demonstration. Robotics and automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE international conference on (pp. 748–753).

  • Hazlett, R. L. (2006). Measuring emotional valence during interactive experiences: boys at video game play. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 1023–1026). ACM.

  • Kirsh, D. (2013). Embodied cognition and the magical future of interaction design. ACM Transactions on Computer-Human Interaction (TOCHI), 20(1), 3.

    Article  MathSciNet  Google Scholar 

  • Kuikkaniemi, K., Laitinen, T., Turpeinen, M., Saari, T., Kosunen, I., & Ravaja, N. (2010). The influence of implicit and explicit biofeedback in first-person shooter games. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 859–868). ACM.

  • Limbitless Solutions. (2017). About Us. Retrieved Apr 06, 2017 from http://limbitless-solutions.org/about-us/.

  • Lyons, G. M., Sharma, P., Baker, M., O’Malley, S., & Shanahan, A. (2003). A computer game-based EMG biofeedback system for muscle rehabilitation. In Engineering in medicine and biology society, 2003. Proceedings of the 25th annual international conference of the IEEE (Vol. 2, pp. 1625–1628). IEEE.

  • Michalski, M. H., & Ross, J. S. (2014). The shape of things to come: 3D printing in medicine. JAMA, 312(21), 2213–2214.

    Article  Google Scholar 

  • Mirza-Babaei, P., Long, S., Foley, E., & McAllister, G. (2011). Understanding the contribution of biometrics to games user research. In DiGRA conference.

  • Nacke, L. E., & Mandryk, R. L. (2010). Designing affective games with physiological input. In Workshop on multiuser and social biosignal adaptive games and playful applications in fun and games conference (BioS-Play).

  • Phan, M. H., Keebler, J. R., & Chaparro, B. S. (2016). The development and validation of the game user experience satisfaction scale (GUESS). Human Factors, 58(8), 1217–1247.

    Article  Google Scholar 

  • Rani, P., Sarkar, N., & Liu, C. (2005). Maintaining optimal challenge in computer games through real-time physiological feedback. In Proceedings of the 11th international conference on human computer interaction (Vol. 58, pp. 22–27).

  • Saponas, T. S., Tan, D. S., Morris, D., & Balakrishnan, R. (2008). Demonstrating the feasibility of using forearm electromyography for muscle-computer interfaces. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 515–524). ACM.

  • Schleenbaker, R. E., & Mainous, A. G. (1993). Electromyographic biofeedback for neuromuscular re-education in hemiplegic stroke patients: a meta-analysis. Archives of Physical Medicine and Rehabilitation, 74, 1301–1304.

    Article  Google Scholar 

  • Schuurink, E. L., Houtkamp, J., & Toet, A. (2008). Engagement and EMG in serious gaming: Experimenting with sound and dynamics in the Levee Patroller training game. In Fun and games (pp. 139–149). Berlin: Springer.

  • Shusong, X., & Xia, Z. (2010). EMG-driven computer game for post-stroke rehabilitation. In Robotics automation and mechatronics (RAM), 2010 IEEE conference on (pp. 32–36). IEEE.

  • Tanaka, K. S., & Lightdale-Miric, N. (2016). Advances in 3D-printed pediatric prostheses for upper extremity differences. Journal of Bone and Joint Surgery. American Volume, 98(15), 1320–1326.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Peter A. Smith.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

All editorial decisions for this article, including selection of reviewers and the final decision, were made by guest editor Dr. Michael Heron.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Smith, P.A., Dombrowski, M., Buyssens, R. et al. The Impact of a Custom Electromyograph (EMG) Controller on Player Enjoyment of Games Designed to Teach the Use of Prosthetic Arms. Comput Game J 7, 131–147 (2018). https://doi.org/10.1007/s40869-018-0060-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40869-018-0060-0

Keywords

Navigation