Hi, I’m wenge, from Xi’an Jiaotong-Liverpool University. I’m glad to present our paper Effect of
Gameplay Uncertainty, Display Type, and Age on VR exergames. This work is done with Hai-Ning,
Kangyou, and Nilufar from Massey University.
Uncertainty is widely acknowledged as an engaging element in games. Uncertainty sources include, but
are not limited to, hidden information, performative uncertainty, player unpredictability.
Age-related declines are common in older and middle-aged adults, but there has been
limited attention given to middle-aged adults. Given the recent rapid development of VR HMDs,
our research explores the effect of uncertain elements and display type on two main player
groups of exergames, young and middle-aged adults. In the next five slides, I'll present the
uncertain elements used in our game and two versions of the exergame.
There is a 20% chance that the monster would perform a false-attack to trick the player
into performing a defense move.
There is a 10% chance that the player’s or monster’s attack could be regarded as
a miss, even if it hits the opponent.
There is a 10% chance that the player’s or monster’s attack could be a critical
hit, which would deal 50% more damage than a normal attack.
This is the TV version of our exergame.
This is the VR version of our exergame.
We conducted a 2×2 within-subjects experiment with 32 participants.
The first factor is display type, the second factor is game condition.
For each condition, players had to play the game GestureFit. They needed first to complete
a training session, where they must have successfully performed each gesture twice.
Then, they needed to complete a game phase, where they would need to kill the monster
three times.
For game performance, we measured completion time on each of the three lives of the monster;
success rate of each move; and the total number of gestures performed grouped in types.
Game experience was measured by a game experience questionnaire and simulator sickness was measured by
the simulator sickness questionnaire. For exertion, we used a Polar OH1 to measure
average HR% and calories burned during gameplay. We used the Borg RPE 6-20 questionnaire to
measure perceived exertion.
We employed a three-way mixed ANOVA with the game condition and display type as the within-subjects
variables and age as the between-subjects variable.
Here, we summarize the results. For more details please refer to our paper.
Overall, the performance of middle-aged adults was worse than young adults.
Young adults were more immersed in the game and had a
higher positive game experience, but also experienced a more negative game experience.
Middle-aged adults had a higher avgHR% and burned more calories than young adults but
gave a lower perceived exertion rating.
We found participants had a better performance in VR than Large Display.
We found participants had a higher exertion level in the uncertain conditions.
To summarize, for the type of exergame like ours,
VR could improve game performance while maintaining the same level of sickness as large displays.
Uncertain elements like those used in our exergame might not help enhance the overall
game experience, but are instrumental in increasing exertion levels.
Exergames for middle-aged adults should be carefully designed with consideration to age-related
declines.
Our contributions are
An empirical evaluation of the effects of display type and game condition on exergame
performance, experience, and exertion between young and middle-aged adults;
A set of uncertain elements that can help increase the exertion level for motion-based exergames;
Two recommendations that can help frame the
design of motion-based exergames that can incorporate uncertain gameplay elements and
how to motivate middle-aged and older adults to engage with exergames.
Thanks for watching!