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. 2025 Jun 17:6:1520184.
doi: 10.3389/fresc.2025.1520184. eCollection 2025.

Effects of game design characteristics of a virtual reality serious game for upper-limb prosthesis control training on motor learning

Affiliations

Effects of game design characteristics of a virtual reality serious game for upper-limb prosthesis control training on motor learning

Jack Tchimino et al. Front Rehabil Sci. .

Abstract

Introduction: Rehabilitation outcomes of hand prosthesis control training generally benefit from an early start in the rehabilitation regimen as well as the use of modern technologies, like serious games, in lieu of more conventional methods. In this study, we tested a virtual reality based myoelectric prosthesis training serious game, specifically how the game design elements affected different aspects of motor control and training.

Methods: Ten able-bodied participants were asked to execute a series of tasks by controlling an LDA-controlled 1-DoF virtual hand prosthesis within a virtual reality environment (VRE) serious game. The tasks included grasping and manipulating virtual objects and controlled force modulation, the latter facilitated by artificial feedback communicated to participants in the VRE.

Results: The results indicated that the game physics affected the way that the participants completed the tasks, while the tasks themselves appeared to be approached and executed in different ways by the participants. Contrary to expectations, however, the force feedback did not influence the participants' ability to precisely modulate the grasping force applied with the virtual prosthesis.

Discussion: Based on these results, it can be concluded that users can be trained within the proposed framework to develop motor skills that might be translated into the use of a real prosthesis, in a more engaging and timely manner.

Keywords: EMG control; motor rehabilitation; prosthesis control; prosthesis training; serious games; virtual reality.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
(A) A participant wearing the complete setup. (B) Schematic of the 4-channel EMG signal generation by the forearm muscles recorded by the active EMG cuff electrodes, used as an input to the classifier, which, in turn, controls the opening and closing of the virtual prosthesis in the game.
Figure 2
Figure 2
Representative screenshots from the VR game. The colors in the pictures have been partly desaturated to highlight the relevant elements. (a) View of the coffee machine, with a latte cup placed on it, (b) view of the spawning area, with latte and cappuccino cups visible, as well as the force feedback bar over the prosthesis, (c) view of the tray with a full latte cup, the bell, and the order slip.
Figure 3
Figure 3
Schematic of the virtual reality game arena. The spawning area is located on the left of the coffee machine, while the tray, bell and order slip are located on the right. The participants had to transfer cups from the spawning area to the coffee machine, brew the correct beverage and transfer the filled cups to the tray. The types of beverages that had to be brewed were shown on the order slip.
Figure 4
Figure 4
Representation of the complete preparation of a beverage. The two parts of the task are displayed, as well as the definitions of the grasp and transfer duration for each of the two parts. The cessation of muscle contractions is not shown in the figure, as it is not relevant to the calculation of the performance metrics.
Figure 5
Figure 5
The main effects of the grasp duration. (A) Cup Type, (B) Session, and (C) Task Phase. Lines and asterisks denote significantly different pairs. (CM stands for Coffee Machine).
Figure 6
Figure 6
The main effects of the transfer duration. (A) Cup Type, (B) Session, and (C) Task Phase. Lines and asterisks denote significantly different pairs. (CM stands for Coffee Machine).
Figure 7
Figure 7
(A) The glass cup crush rate of each participant over the five training sessions. Each colored line corresponds to a different participant. (B) The glass cup crush rate distribution in the first and last training sessions.
Figure 8
Figure 8
(A,B) The number of submovements when grasping a glass cup from the spawning area (A) and the coffee machine (B) in the five training sessions. Each colored line corresponds to a different participant. (C,D) Boxplots presenting the number of submovements distribution in the first and last sessions for grasping from the spawning area (C) and the coffee machine (D) Statistically significant pairs are denoted by asterisks (*p < 0.05).

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