Hello everyone our paper is on affect recognition using psychophysiological
correlates in high intensity VR exergaming. Optimal play experience is
desirable because it leads to increased motivation which results in better
exercise adherence. The optimal play experience should be engaging enough to
keep the player interested without being overly exerting. Therefore it is very
important to detect the play experience which is reflected by their affective
state to adapt the game accordingly to achieve optimal player experience.
According to the American College of Sports Medicine adults need at least 150
minutes of moderate intensity exercise or 75 minutes of high intensity exercise
per week. However forty to sixty five percent of people who enrol themselves
for physical activity regimes typically quit within the first three to six
months and don't meet the exercise requirements. Lack of time and motivation
are the most commonly cited barriers to exercise adherence. High intensity VR
exergames require only half the time commitment requirement of moderate
intensity exercise protocols. They only require 75 minutes of time commitment
per week and they improve motivation to exercise. Studies generally rely on
tedious self-reported user experience questionnaires given at the end of the
experiment to detect player experience. This could be useful to get an overall
feedback but they lack the capacity to give genuine and unadulterated reactions
to different events in the game. Furthermore they redundant feedback in a
sense as they cannot be used to dynamically adapt the VR exergame during
the session. Experience sampling involves collecting information as it is directly
perceived in a particular moment by enquiring the player. Although it
provides instantaneous feedback it could potentially disrupt the fragile gameplay
experience. This is because cognitive effort is
necessary to express emotional experience. The recognition of facial
expressions is difficult because the players face is partly covered by the VR
headset and it is affected by excessive panting as a result of exercising.
Affectively adaptive video games have been extensively studied and they use
various neuropsychophysiological measurements such as heart rate
variability, facial electromyography, and skin conductivity to recognize affect.
Using these sensors in the context of playing an exergame imposes many
challenges because they can be very sensitive to extensive movement and
perspiration. This is because variations in psychophysiological parameters might
not be an autonomic response but due to the physical activity performed
therefore it's important to identify sensors that are compatible with high
intensity VR exergaming. Another problem associated with affect
recognition using psychophysiological correlates such as skin conductivity is
that they can only indicate the intensity of the emotional states and
not its valence. We present two experiments that investigate the use of
different sensors for affect recognition in a high intensity VR exergame. Our first
research question is how do affective responses differ between sedentary
gaming, exergaming, conventional exercise, and rest. Our second research question is
which psychophysiological senses are the most suited for determining affect in
high-intensity VR exergaming. Our third research question is what are the
psychophysiological correlates of positive and negative affect in high
intensity VR exergaming. The first experiment compares the impact of
physical exertion and gamification on psycho physiological measurements during
rest, conventional exercise, VR exergaming, and sedentary VR gaming
using a within participants design. They recorded skin conductance and blink rate
during each of the four conditions. I'd like to show you a video of the
conditions. The VR exergaming and conventional exercise conditions follow
the high intensity protocol in which they alternate between low intensity
phases and high intensity sprints. The sedentary VR game is identical to the VR
exergame condition with the only difference being that it is controlled
by a hand pedal attached to the handlebar on the bike. For the conditions
rest and conventional exercise we used a VR environment in which the background
is the average color of the VR gaming environments to prevent confounding
factors.
We screened the participants using the physical activity readiness
questionnaire and excluded participants with health risks. We used the IMI
interest or enjoyment subscale of the intrinsic motivation inventory
questionnaire. The results of our first experiment show that the skin
conductivity and blink rate are suitable to use in the context of high intensity
VR exergaming. The second experiment compares the affective responses to
underwhelming, overwhelming, and optimal VR exergaming scenarios using a within
participants design. The underwhelming scenario is designed to evoke boredom by using
unappealing aesthetics and lack of gamification elements like points and
competitor. The optimal condition has a high tempo music track and optimally
challenging gamification elements. The overwhelming condition has annoying
sound effects like loud honking, blaring sirens and frustratingly challenging
gamification elements we recorded skin conductivity pupil dilation, blink rate,
gaze fixations, and performance. We used experience sampling to collect ground
truth values about the player's affective state by seamlessly integrating it into
the exergame. Players are asked to choose a number from the affective scale
ranging from minus 2 to plus 2 by using their hand pedal based on their current
affective state. We considered the average of all experience sampling measures
measured in a condition as the outcome variable called "Affect". I'd like to show
you a video of the conditions. Players are asked to choose a number from the
affective scale that appears during the game ranging from minus 2 to plus 2 by
using their hand pedal based on their current affective state. The
underwhelming scenario is plain without any sound effects or gamification
elements like points or competitor. The optimal condition has a motivational
music track and gamification elements like points and an optimally
challenging competitor.
The overwhelming condition has annoying sound effects and an unbeatable competitor.
Our manipulation check shows that the optimal, overwhelming, and underwhelming
conditions were successful in eliciting significantly different levels of affect
which is necessary in order to analyze the correlations of affect with the
psychophysiological variables. We conducted repeated measures correlation
analysis of the psychophysiological measurements with the affective state
ground truth values and successfully identified the positive and
negative correlates of affect in VR exergaming. This is a plot of linear
prediction model of affective predictor using gaze fixations, pupil dilation and skin
conductivity versus measured affect. We have individual regression lines for
each participant. Our findings provide guidelines for researches of affective
high-intensity VR exergames. The accuracy of linear model could be further
investigated using larger and longer studies. Our participants were mostly in
their 20s and they were mostly male which may limit the generalizability of
the results. Another potential problem is that personality traits such as
competitiveness may have influenced the results. Our findings can be applied in
the development of affectively adaptive exergames and they can also be applied
in non-exergaming and non-VR applications
I'm Soumya. I'm a Marie Curie FIRE PhD researcher. Michael, Eamonn and Christof
are co-authors on the paper. I would like to thank Dan and Crescent for the
contributions to the paper. Thank you and happy exergaming