Exploring the Feasibility of EMG Based Interaction for Assessing Cognitive Capacity in Virtual Reality

Wirth M, Gradl S, Poimann D, Richer R, Ottmann J, Eskofier B (2018)

Publication Type: Conference contribution

Publication year: 2018

Journal

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society

Publisher: Institute of Electrical and Electronics Engineers Inc.

Book Volume: 2018-July

Pages Range: 4953-4956

Conference Proceedings Title: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Event location: Honolulu, HI, USA

ISBN: 9781538636466

DOI: 10.1109/EMBC.2018.8513213

Abstract

With the growth and aging of the world population, the prevalence of cognitive diseases and disabilities like dementia and mild cognitive impairments increases. To determine the influence of such diseases, find therapeutic effects and further improve quality of life, cognitive assessment and training is required. This can be done with the application of high immersive technologies like virtual reality.In this paper we evaluate the feasibility of an electromyography (EMG) arm muscle-motion based interaction technique for controlling a VR cognitive performance diagnostic and training environment. Therefore, we compared the state-of-theart controller input to our EMG based approach in terms of presence and user experience.Results show significant differences in terms of Novelty and Dependability. Since there are only few significant differences regarding presence and user experience, the advantage of applying a more demanding physical motion interaction approach (EMG), seems to be a promising method with the potential of having a positive effect on the cognitive training progress. This is mainly caused by the fact that the implemented gesture interaction reinforces the connection between decision making and action execution.

Authors with CRIS profile

Markus Wirth Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Stefan Gradl-Trautvetter Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Dino Poimann Lehrstuhl für Sportbiologie und Bewegungsmedizin Robert Richer Sonderforschungsbereich 1483/1 Empathokinästhetische Sensorik – Sensortechniken und Datenanalyseverfahren zur empathokinästhetischen Modellbildung und Zustandsbestimmung Jenny Ottmann Lehrstuhl für Informatik 1 (IT-Sicherheitsinfrastrukturen) Björn Eskofier Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics)

How to cite

APA:

Wirth, M., Gradl, S., Poimann, D., Richer, R., Ottmann, J., & Eskofier, B. (2018). Exploring the Feasibility of EMG Based Interaction for Assessing Cognitive Capacity in Virtual Reality. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 4953-4956). Honolulu, HI, USA: Institute of Electrical and Electronics Engineers Inc..

MLA:

Wirth, Markus, et al. "Exploring the Feasibility of EMG Based Interaction for Assessing Cognitive Capacity in Virtual Reality." Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, HI, USA Institute of Electrical and Electronics Engineers Inc., 2018. 4953-4956.

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