Abstract
In recent years, non-traditional input devices for digital games and applications such as wearable sensors have become increasingly available and affordable. Electromyography (EMG) promises some unique advantages over traditional input devices such as keyboards or gamepads by collecting input data directly at a person’s muscle. As long as the corresponding muscle is intact, EMG can be used even when physical movement is not possible, for example when a person is injured or has an amputated limb. It also allows for unique wearable positioning on the body, potentially allowing for a larger freedom of movement.
In this paper, we examine whether an EMG-based input device is feasible to control an in-game character in a digital game. In order to do so, we first assess different EMG-related technologies and available EMG devices. Based on this assessment, we develop an EMG-based input device that can be connected to a computer. We develop a side scrolling game which can be connected to the EMG-based input device and allows for the player to switch between keyboard- and EMG-based controls. Lastly, we evaluate our developed system empirically and discuss the feasibility of EMG-based game controllers based on observed practical and theoretical limitations of the technology.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
https://wiki.seeedstudio.com/Grove-EMG_Detector/ - Last visited on 03.07.2020.
- 2.
https://www.sparkfun.com/products/13723 - Last visited on 03.07.2020.
- 3.
https://www.vdc-fellbach.de/leistungen/technikbewertung-var/thalmic-labs-myo-gesture-control-armband/ - Last visited on 03.07.2020.
- 4.
https://www.cometasystems.com/products/mini-wave - Last visited on 03.07.2020.
- 5.
https://www.delsys.com/trigno/research/ - Last visited on 03.07.2020.
- 6.
https://www.delsys.com/bagnoli/ - Last visited on 03.07.2020.
- 7.
https://unity.com/ - Last visited on 04.07.2020.
References
Ackerman, E.: Myo Armband Provides Effortless Gesture Control of Robots, Anything Else - IEEE Spectrum, June 2020. https://spectrum.ieee.org/automaton/robotics/robotics-hardware/thalmic-myo-armband-provides-effortless-gesture-control-of-robots. Library Catalog: spectrum.ieee.org
Ahmed, S.F., et al.: Mobility assistance robot for disabled persons using electromyography (EMG) sensor. In: 2018 IEEE International Conference on Innovative Research and Development (ICIRD), pp. 1–5. IEEE (2018)
Alves, N., Chau, T.: The design and testing of a novel mechanomyogram-driven switch controlled by small eyebrow movements. J. NeuroEng. Rehabil. 7(1), 22 (2010). https://doi.org/10.1186/1743-0003-7-22. ISSN 1743–0003
Armiger, R.S., Vogelstein, R.J.: Air-Guitar Hero: a real-time video game interface for training and evaluation of dexterous upper-extremity neuroprosthetic control algorithms. In: 2008 IEEE Biomedical Circuits and Systems Conference, pp. 121–124 (2008)
Borisov, I.I., Borisova, O.V., Krivosheev, S.V., Oleynik, R.V., Reznikov, S.S.: Prototyping of EMG-controlled prosthetic hand with sensory system. IFAC-PapersOnLine 50(1), 16027–16031 (2017)
Islam, A., Sundaraj, K., Ahmad, B., Ahamed, N.U., Ali, A.: Mechanomyography sensors for muscle assessment: a brief review. J. Phys. Ther. Sci. 24(12), 1359–1365 (2012)
Khushaba, R.N., Kodagoda, S., Takruri, M., Dissanayake, G.: Toward improved control of prosthetic fingers using surface electromyogram (EMG) signals. Expert Syst. Appl. 39(12), 10731–10738 (2012)
Konrad, P.: EMG-Fibel. - Eine praktische Einführung in die kinesiologische Elektromyographie, January 2011
Krivosheev, S., Borisov, I., Olejnik, R., Reznikov, S.: First Experiments and Results, Various Control Strategies for the Artificial Hand Using Surface EMG Sensors (2016)
Latif, S., Javed, J., Ghafoor, M., Moazzam, M., Khan, A.A.: Design and development of muscle and flex sensor controlled robotic hand for disabled persons. In: 2019 International Conference on Applied and Engineering Mathematics (ICAEM), pp. 1–6. IEEE (2019)
Oppenheim, H., Armiger, R.S., Vogelstein, R.J.: WiiEMG: a real-time environment for control of the Wii with surface electromyography. In: Proceedings of 2010 IEEE International Symposium on Circuits and Systems, pp. 957–960 (2010)
Pai, Y.S., Dingler, T., Kunze, K.: Assessing hands-free interactions for VR using eye gaze and electromyography. Virtual Real. 23(2), 119–131 (2019). https://doi.org/10.1007/s10055-018-0371-2. ISSN 1434–9957
Pizzolato, S., Tagliapietra, L., Cognolato, M., Reggiani, M., Müller, H., Atzori, M.: Comparison of six electromyography acquisition setups on hand movement classification tasks. PLOS One 12(10), e0186132 (2017). https://doi.org/10.1371/journal.pone.0186132. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0186132. ISSN 1932–6203
Prahm, C., Vujaklija, I., Kayali, F., Purgathofer, P., Aszmann, O.C.: Game-based rehabilitation for myoelectric prosthesis control. JMIR Serious Games 5(1),e3 (2017). https://doi.org/10.2196/games.6026. http://www.ncbi.nlm.nih.gov/pubmed/28183689. ISSN 2291–9279
von Rosenberg, H.: Identifikation von Willkürsignalen zur Bewegungskontrolle einer Beinprothese (2012)
Talib, I., Sundaraj, K.,Lam, C.K.: Choice of mechanomyography sensors for diverse types of muscle activities. J. Telecommun. Electron. Comput. Eng. (2018, accepted for publication)
Weitz, M.: Messung und Analyse myoelektrischer Signale. Ph.D. thesis, Diplomarbeit. Universität Kassel, Kassel (2006)
Wheeler, K.R.: Device control using gestures sensed from EMG. In: Proceedings of the 2003 IEEE International Workshop on Soft Computing in Industrial Applications, SMCia/03, pp. 21–26. IEEE (2003)
Wu, J., Sun, L., Jafari, R.: A wearable system for recognizing American sign language in real-time using IMU and surface EMG sensors. IEEE J. Biomed. Health Inform. 20(5), 1281–1290 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Müller, P.N. et al. (2020). Flex Your Muscles: EMG-Based Serious Game Controls. In: Ma, M., Fletcher, B., Göbel, S., Baalsrud Hauge, J., Marsh, T. (eds) Serious Games. JCSG 2020. Lecture Notes in Computer Science(), vol 12434. Springer, Cham. https://doi.org/10.1007/978-3-030-61814-8_18
Download citation
DOI: https://doi.org/10.1007/978-3-030-61814-8_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-61813-1
Online ISBN: 978-3-030-61814-8
eBook Packages: Computer ScienceComputer Science (R0)