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Clinical Trial
. 2013 Jul 26;8(7):e69471.
doi: 10.1371/journal.pone.0069471. Print 2013.

An impact study of the design of exergaming parameters on body intensity from objective and gameplay-based player experience perspectives, based on balance training exergame

Tien-Lung Sun  1 , Chia-Hsuan Lee
Affiliations
Clinical Trial

An impact study of the design of exergaming parameters on body intensity from objective and gameplay-based player experience perspectives, based on balance training exergame

Tien-Lung Sun et al. PLoS One. .

Abstract

Kinect-based exergames allow players to undertake physical exercise in an interactive manner with visual stimulation. Previous studies focused on investigating physical fitness based on calories or heart rate to ascertain the effectiveness of exergames. However, designing an exergame for specific training purposes, with intensity levels suited to the needs and skills of the players, requires the investigation of motion performance to study player experience. This study investigates how parameters of a Kinect-based exergame, combined with balance training exercises, influence the balance control ability and intensity level the player can tolerate, by analyzing both objective and gameplay-based player experience, and taking enjoyment and difficulty levels into account. The exergame tested required participants to maintain their balance standing on one leg within a posture frame (PF) while a force plate evaluated the player's balance control ability in both static and dynamic gaming modes. The number of collisions with the PF depended on the frame's travel time for static PFs, and the leg-raising rate and angle for dynamic PFs. In terms of center of pressure (COP) metrics, significant impacts were caused by the frame's travel time on MDIST-AP for static PFs, and the leg-raising rate on MDIST-ML and TOTEX for dynamic PFs. The best static PF balance control performance was observed with a larger frame offset by a travel time of 2 seconds, and the worst performance with a smaller frame and a travel time of 1 second. The best dynamic PF performance was with a leg-raising rate of 1 second at a 45-degree angle, while the worst performance was with a rate of 2 seconds at a 90-degree angle. The results demonstrated that different evaluation methods for player experience could result in different findings, making it harder to study the design of those exergames with training purposes based on player experience.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Balance game with Wii Balance Board (Billis et al., 2010).
Figure 2
Figure 2. Diagram of the posture frame.
(a)Posture frame with larger width. (b) Posture frame with smaller width.
Figure 3
Figure 3. Diagram of the frame width.
Figure 4
Figure 4. Diagram of the design of posture frame travel time to the avatar.
(a) A raising angle of 45 degrees. (b) A raising angle of 90 degrees.
Figure 5
Figure 5. Diagram of the design of leg-raising angle.
Figure 6
Figure 6. Virtual scene of the exergame for one-leg stand balance training and partial side view.
Figure 7
Figure 7
(a) Diagram of skeletal data collected by OpenNI. (b) Name and position of each articulation point. (Reference source: http://kheresy.wordpress.com/2011/01/28/detecte_skeleton_via_openni_part1/).
Figure 8
Figure 8. Scripts for matching skeletal information of the avatar and diagram of avatar control via Kinect by the player.
Figure 9
Figure 9. Flow chart of the experiment.
Figure 10
Figure 10. Schematic diagram of COP (Zhuo, 2007).
Figure 11
Figure 11. Diagram of COP sway trajectory (left), resolved AP component of the sway trajectory (upper right) and resolved ML component of the sway trajectory (lower right).
Figure 12
Figure 12. Detection of collisions between the avatar and the posture frame.
See this image and copyright information in PMC

References

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