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Increasing Voluntary Myoelectric Training Time through Game Design

Lookup NU author(s): Dr Christian Garske, Dr Matthew DysonORCiD, Dr Sigrid DupanORCiD, Professor Graham MorganORCiD, Professor Kianoush Nazarpour



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


In virtual prosthetic training research, serious games have been investigated for over 30 years. However, few game design elements are used and assessed for their effect on the voluntary adherence and repetition of the performed task. We compared two game-based versions of an established myoelectric-controlled virtual prosthetic training task with an interface without game elements of the same task (for video, see [1]). Twelve able-bodied participants were sorted into three groups of comparable ability and asked to perform the task as long as they were motivated. Following the task, they completed a questionnaire regarding their motivation and engagement in the task. The investigation established that participants in the game-based groups performed the task significantly longer when more game design elements were implemented in the task (medians of 6 vs. 9.5 vs. 14 blocks for groups with increasing number of different game design elements). The participants in the game-based versions were also more likely to end the task out of fatigue than for reasons of boredom or frustration, which was verified by a fatigue analysis of the myoelectric signal. We demonstrated that the utilization of game design methodically in virtual myoelectric training tasks can support adherence and duration of a virtual training, in the short-term. Whether such short-term enhanced engagement would lead to long-term adherence remains an open question.

Publication metadata

Author(s): Garske C, Dyson M, Dupan S, Morgan G, Nazarpour K

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Neural Systems and Rehabilitation Engineering

Year: 2022

Volume: 30

Pages: 2549-2556

Online publication date: 02/09/2022

Acceptance date: 23/08/2022

Date deposited: 03/10/2022

ISSN (print): 1534-4320

ISSN (electronic): 1558-0210

Publisher: IEEE


DOI: 10.1109/TNSRE.2022.3202699

PubMed id: 36054389


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Funder referenceFunder name
DS-2017-015Leverhulme Trust, The