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Energy Cost and Game Flow of 5 Exer-games in Trained Players

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  • ADAM Center

Abstract and Figures

To determine energy expenditure and player experience in exer-games designed for novel platforms. Energy cost of 7 trained players was measured in 5 music-based exer-games. Participants answered a questionnaire about "game flow," experience of enjoyment, and immersion in game play. Energy expenditure during game play ranged from moderate to vigorous intensity (4 - 9 MET). Participant achieved highest MET levels and game flow while playing StepMania and lowest MET levels and game flow when playing Wii Just Dance 3(®) and Kinect Dance Central™. Game flow scores positively correlated with MET levels. Physiological measurement and game flow testing during game development may help to optimize exer-game player activity and experience.
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Am J Health Behav.™ 2013;37(3):369-380 369
Exer-games, or active video games, may pro-
vide effective alternatives to standard exer -
cise to meet recommended physical activity
(PA) levels as well as provide positive reinforcement
for continued PA.1,2 Game play has the potential
to provide enjoyment, task mastery, and social in-
teraction, which have been linked to greater exer-
cise adherence.3-5 Exer-games may also enhance
an internalization of motivation that results in in-
creased exercise self-efcacy.6
Activity guidelines for exercise programs in gen-
eral recommend a minimum of 150 min/wk of
moderate-intensity aerobic PA (3 6 metabolic
equivalents or MET, similar to walking at ~ 3.3
mph) or 75 min/wk of vigorous-intensity activity
(> 6 MET, like jogging ~ 6.3 mph) to achieve health
benets.7,8 Some of the barriers to increasing PA
are cited as time, access, and environment.9 In
comparisons of exer-games to treadmill walking
and cycling, participants reported that traditional
exercise was not fun.2,10-12
In contrast, exer-games are thought to have the
potential to alleviate boredom through player en-
gagement via game ow, the experience of enjoy-
ment and immersion in an activity.13 Flow theory
relates to the optimal experience of enjoyment re-
gardless of the activity, context, or culture.13 Game-
ow components include clear goals, concentra-
tion, merging of action and awareness, transfor-
mation of time, direct and immediate feedback,
balance between ability level and challenge, sense
of personal control over the situation or activity,
and intrinsically rewarding activity so there is an
effortlessness of action.14 When presented with a
“game,” people may be more apt to be engaged. Be-
fore implementing larger studies investigating the
effect of playing exer-games on cardiorespiratory
tness and exercise self-efcacy, it is important to
ascertain whether exer-games offer adequate phys-
iologic training and tenents of internal motivation
such as positive ow experience that will keep us-
ers engaged and more likely to continue exercising
using exer-games. If it is possible to identify which
exer-games are most effective in allowing individu-
als to achieve their energy exertion goals while pro-
viding enjoyable experiences, these games can be
selected for further study on exercise self-efcacy,
adherence, and their role as gatekeepers to other
forms of PA.
Current statistics from polling of over 2000 na-
tionally representative households indicate that
72% of American households play video games.15
An online survey conducted in 2010 with 2284
respondents reported that 29% of adults between
25 and 55 years played exer-games.16 People who
played active video games were more active than
nongamers. Specically, 34% of active-play gam-
ers engaged in 30 min of exercise 5 or more days/
wk compared to only 23% of nongamers. Further-
more, 89% of people who played active video games
Shaw Bronner, Director; Russell Pinsker, Lab Assistant; and
J. Adam Noah, Technical Director, ADAM Center, Long Island
University, Brooklyn, NY.
Correspondence Dr Bronner; sbronner@liu.edu
Energy Cost and Game Flow of 5 Exer-games
in Trained Players
Shaw Bronner, PhD, PT, OCS; Russell Pinsker; J. Adam Noah, PhD
Objectives: To determine energy ex-
penditure and player experience in ex-
er-games designed for novel platforms.
Methods: Energy cost of 7 trained play-
ers was measured in 5 music-based ex-
er-games. Participants answered a ques-
tionnaire about “game ow,” experience
of enjoyment, and immersion in game
play. Results: Energy expenditure during
game play ranged from moderate to vig-
orous intensity (4 – 9 MET). Participant
achieved highest MET levels and game
ow while playing StepMania and lowest
MET levels and game ow when playing
Wii Just Dance 3® and Kinect Dance Cen-
tral™. Conclusions: Game ow scores
positively correlated with MET levels.
Physiological measurement and game
ow testing during game development
may help to optimize exer-game player
activity and experience.
Key words: energy expenditure, heart
rate, metabolic equivalent, MET, exer-
cise video games
Am J Health Behav. 2013;37(3):369-380
DOI: http://dx.doi.org/10.5993/AJHB.37.3.10
Energy Cost and Game Flow of 5 Exer-games in Trained Players
370
said that “exercise” was more fun. Among respon-
dents who played active video games, 68% report-
ed they became more physically active overall. Of
those, 58% started a new tness activity like walk-
ing, playing tennis, or jogging.16 Therefore, active
video games may provide effective and enjoyable
alternatives to standard exercise methods to meet
and sustain recommended PA levels and provide a
gateway to other types of PA.
Over the last 2 decades, many exer-games have
been developed. These include classic video games
such as Dance Dance Revolution™; newer games
designed for the WiiTM (eg, Wii Sports, Wii Fit™, Wii
Just Dance 2™, Just Dance 3®); EA Sports Active 2™
designed for the WiiTM, Xbox 360®, and PlayStation
3TM; multiple games designed for the Sony EyeToy®
and PlayStation Move®; and, most recently, a num-
ber of games for the Microsoft KinectTM including
Dance Central™, Just Dance 3®, Your Shape: Fit-
ness Evolved™ and Kinect Adventures. In descrip-
tive studies, researchers demonstrated that active
games such as Wii Fit and Wii Sports™, Sony
EyeToy®, and Dance Dance Revolution™ elicit light
to moderate PA levels.17-29 Although light to mod-
erate energy exertion was reported for the major-
ity of these games, other researchers reported that,
with effective training, energy expenditure of Dance
Dance Revolution™ is commensurate with vigor-
ous activity.26,30,31 Furthermore, exit questionnaires
provided by Dance Dance Revolution players who
trained for 30 hrs indicated an immersive game ow
experience when played at the advanced level.30
The purpose of this study was to investigate phys-
iological and psychological reactions to 5 current-
generation exercise video games in experienced
players. If we anticipate that the consumer will con-
tinue to play these games, it is important to know
about player experience with prolonged exposure
to the games. We hypothesized that games that re-
ected the greatest energy expenditure would also
provide the most optimal enjoyment and game ow
experience. We tested these hypotheses on 5 mu-
sic-based dance rhythm games, using 3 platforms.
Music-based exer-games were chosen because mu-
sic has been shown to be motivational, entraining,
can enhance exertion during physical activity, and
improves performance.32-35 The games included (1)
StepMania Endless, 2) Dance Dance Revolution™
“Hottest Party” using the WiiTM console, (3) Just
Dance 3® on the Xbox 360® console and Kinect ac-
cessory, (4) Just Dance 3® on the WiiTM console, and
(5) Dance Central™ using the Xbox 360® console
and Kinect accessory.
METHODS
Participants
Participants were recruited from students and
faculty members of an urban university who played
video games. They were healthy nonsmokers and
free from any cardiovascular, musculoskeletal, or
neurological condition that would preclude them
from performing a maximal exercise test or train-
ing session. They also were willing to devote the
time necessary to complete the training required
for our protocol. An a priori power analysis for
a one group, within subject, repeated measures
design with a moderate effect size (f = .05) and
power (1 – b error probability) = .80, determined
that sample size of 7 subjects was necessary.
Training on 5 different games to advanced levels
required an extensive time commitment on the
part of our participants. Although we had greater
interest than our nal 7 participants, several in-
terested people did not have the time to complete
their training in a timely manner. Therefore, our
sample was small.
Instrumentation
Participants were outtted with an indirect
calorimeter (portable gas analysis system; K4b2
Cosmed Inc, Rome, Italy) comprising a small met-
abolic analyzer, battery pack, and face mask and
a chest strap heart rate (HR) monitor (Nike, Bea-
verton, OR). The face mask was attached to a tur-
bine ow-meter that allowed for real-time collec-
tion of VO2 values. The K4b2 unit (~925 grams) was
strapped to the participant’s shoulders and torso
using the manufacturer’s harness throughout the
testing period. Prior to testing, the oxygen and car-
bon dioxide analyzers were calibrated according to
the manufacturer’s instructions, and the ow tur-
bine was calibrated using a 3-L syringe. The K4b2
has been validated previously.36-38 During testing,
VO2 (mL·kg-1·min-1), VCO2 (mL·kg-1·min-1), and
HR (beats·min-1) were measured continuously and
recorded using the K4b2 breath-by-breath analysis.
During StepMania Endless (StepMania) game
play, participants played on a Dance Dance Revo-
lution (DDR) metal dance pad (DDR Game, South
El Monte, CA, www.ddrgame.com), connected to
a computer running Microsoft Windows 7 and a
large (50-inch) video monitor. We used the more
robust metal pads because the soft, exible pads
tend to move around and rip as players progress
to playing at high skill levels. Experienced DDR
players frequently purchase these metal pads as
a durable alternative for home use. For Dance
Dance Revolution™ “Hottest Party” (Konami Digi-
tal Entertainment, Los Angeles, CA) on the WiiTM
platform (Nintendo of America, Inc, Redmond, WA)
(Wii-DDR), participants played on the same metal
pad connected to a WiiTM console and the same
video monitor. To play Dance Central™ (Harmonix,
Music Systems, Cambridge, MA) (K-DC) and Just
Dance 3® (Ubisoft Entertainment, Montreuil sous
Bois, France) (K-JD3), participants used an Xbox
360® (Microsoft Corp, Redmond, WA) with a Kinect
accessory attached to the same video monitor, in
a roughly 2 x 2 m space (area in which the Kinect
infrared camera detects participant movement).
Participants also played Just Dance 3® (Ubisoft
Entertainment, Montreuil sous Bois, France) on
the WiiTM platform (Nintendo of America, Inc, Red-
mond, WA) (Wii-JD3).
Bronner et al
Am J Health Behav.™ 2013;37(3):369-380 371 DOI: http://dx.doi.org/10.5993/AJHB.37.3.10
Protocol
Each subject performed a Bruce maximal exer -
cise treadmill test protocol to volitional fatigue39 on
a motor-driven Trackmaster® treadmill (TMX425C,
Newton, KA) controlled by a Welch Allyn Cardio-
Perfect™ Workstation (Skaneateles Falls, NY). Pri-
or to conducting the test, participants rested for 10
min to obtain baseline measures. The speed and
grade settings of each 3-min segment of the pro-
tocol were identical to those of the standard Bruce
protocol [eg 3 min: 2.74 km/hr, (1.7 mi/hr), 10%
grade]. Heart rate measurements were obtained
during the last 5 seconds of every minute and at
peak exercise from the cardiopulmonary exercise
system. During each test, the participant was ver-
bally encouraged to continue exercising until ex-
hausted. Queries for rating of perceived exertion
were made during the last 5 seconds of each min-
ute and immediately after the test (ie, peak rating
of perceived exertion). Criteria for termination were
if a participant achieved any 2 of the nal criteria:
HR > 95% of predicted maximal HR (based on the
formula: 220 – age), RER > 1.0 for 3 consecutive
readings, plateau in VO2peak values, or volitional
signs of fatigue.
Participants were tested on separate days for
each exer-game in a pseudo-randomized order. We
selected 6 songs for each game ranging in tempo
from 101 to 192 beats·min-1 (Table 1). When pos-
sible, we tested the same songs on each platform.
We compared the same 6 songs on StepMania End-
less (StepMania) mode and Dance Dance Revolu-
tion “Hottest Party” on the WiiTM (Wii-DDR). A
different set of 6 songs from Just Dance 3® were
compared on the WiiTM (WiiJ-D3) and Xbox 360®
Kinect (K-JD3) platforms. Dance Central™ (K-DC)
did not share any common songs with the other
games. All games were played on the highest level
of difculty possible to maximize the workout (eg
heavy on StepMania, expert on Wii-DDR, normal
on Wii-JD3 and K-JD3, and hard on K-DC).
During exer-game testing, participants wore
comfortable workout attire and played in socks or
bare feet, as they preferred. Prior to beginning game
play, participants rested for 10 min. For each exer-
game, the game was turned on and cued up to the
initial game menu. To mark key temporal features
of game play, the manual K4b2 event marker was
used, which places a visual indicator of the marker
time in the exported data. The beginning and end
of the pretest rest period, beginning of the start
menu, and beginning and end of each game song
were marked. Immediately following testing of each
game, participants answered a 14-question video
game training effect questionnaire and were inter-
viewed about their experience playing that game.
The Video Game Training Effect Questionnaire
contains questions based on a survey validated
on DDR developed by Höysniemi40 as well as ques-
tions about the 8 components of ow validated ex-
tensively in the sports and game literature.13,14,41-44
Our questionnaire uses a 5-point Likert scale (1 =
Strongly disagree, 2 = Disagree, 3 = Neither agree
nor disagree, 4 = Agree, 5 = Strongly agree).
Data Analyses
Data recorded from the K4b2 for the treadmill
exercise test and each video game test were ex-
ported as a .csv text le into Microsoft Excel 2010
for participant and group analyses. The following
variables were calculated for the treadmill exercise
test: baseline pre-exercise resting HR and VO2, VO-
2max, and HRmax. Baseline HR and VO2 were deter -
mined by averaging the nal minute of rest. VO2max
and HRmax were determined by averaging the 2 con-
secutive highest measurements of each variable.
Oxygen uptake reserve (VO2R) was calculated as
the difference between resting and maximal oxy-
gen levels.
During game play, there was a small amount
of variability in the duration of games and songs
across participants due to the manual nature of
the K4 event marker. To accommodate for these
differences, individual song and game play time
durations were averaged to determine the length
of time it took to run through the menu to initi-
ate play for the rst song (eg, start menu), song
length, and length of time between songs. Mean
±SD for VO2 mL·kg-1·min-1, respiratory exchange
ratio (RER), HR beats·min-1, energy expenditure
(EE kcal·min-1), and MET levels were calculated
from the game start menu through 6 songs of game
play. Game-play variables as a percentage of peak
treadmill exercise values, VO2R and HRmax, were
then calculated to ascertain the relative level of
workout for each game.
Likert scores of the 14 game ow questions
were entered into Excel, with answers grouped by
game. A total score was determined for each game
questionnaire for each participant by calculating
a percent total. To determine whether there was
a correlation between physiological measures and
a participant’s perception of game play, game ow
scores were correlated to mean game play VO2 and
MET values using Pearson’s product moment cor-
relation coefcients.
Differences between exer-game variables were
compared using GLM repeated measures for with-
in-subjects factor with 5 levels. Greenhouse-Geiss-
er corrections were made if sphericity was violated.
Post hoc pairwise comparisons were made as ap-
propriate. All analyses were conducted using SPSS
(SPSS 16.0, IBM SPSS, Inc, Chicago, IL), with an
a level of .05.
RESULTS
Participants
Seven participants, 4 males, 3 females (mean age
29 ± 9.34 years, height 170.29 ± 10.48 m, mass
26.43 ± 11.90 kg, BMI 24.93 ± 5.53), trained on
each game until they could unlock advanced lev-
els and achieved the competency to reach targeted
game skills based on game scores. Participants
reected the demographic diversity of the urban
Energy Cost and Game Flow of 5 Exer-games in Trained Players
372
Table 1
Exer-game Temporal Parameters
Game
(total time) Song (Artist) Beats·min-1 Level Song Length (min)
StepMania Clocks (T.R. Masters MC) 145 Heavy 01:29 ±00:01
(10:16 ±00:19) Blue Monday (Wg) 131 Heavy 01:34 ±00:01
You Spin Me Round (M.A.N.) 160 Heavy 01:27 ±00:03
Rhythm Is a Dancer (Spots) 153 Heavy 01:36 ±00:01
Call on Me (2000’s Stars) 170 Heavy 01:32 ±00:03
Red Balloons
(M-Crew Project) 192 Heavy 01:25 ±00:05
Mean 158.50
Total 09:03 ±00:08
% Game Time 88.18% ±2.34
Wii DDR
(14:19 ±00:15)
Clocks (T.R. Masters MC) 145 Expert 01:31 ±00:04
Blue Monday (Wg) 131 Expert 01:36 ±00:01
You Spin Me Round (M.A.N.) 160 Expert 01:29 ±00:03
Rhythm Is a Dancer (Spots) 153 Expert 01:39 ±00:05
Call on Me (2000’s Stars) 170 Expert 01:34 ±00:03
Red Balloons
(M-Crew Project) 192 Expert 01:28 ±00:02
Mean 158.50
Total 09:17 ±00:08
% Game Time 64.86% ±1.49
Kinect Just Dance 3 Apache (The Sugarhill Gang) 139 Normal 04:06 ±00:01
25:50 ±01:29 I’m So Excited (Pointer Sisters) 183 Normal 03:49 ±00:03
Land of 1,000 Dancers (Wilson Pickett) 185 Normal 02:24 ±00:04
No Limit (2 Unlimited) 141 Normal 03:26 ±00:02
Pump It (The Black Eyed Peas) 133 Normal 03:33 ±00:02
Take on Me (A-ha) 170 Normal 03:35 ±00:02
Mean 158.50
Total 20:54 ±00:07
% game time 81.10% ±4.07
Wii Just Dance 3 Apache (The Sugarhill Gang) 139 Normal 04:07 ±00:02
24:11 ±00:32 I’m So Excited (Pointer Sisters) 183 Normal 03:49 ±00:08
Land of 1,000 Dancers (Wilson Pickett) 185 Normal 02:26 ±00:03
No Limit (2 Unlimited) 141 Normal 03:29 ±00:04
Pump It (The Black Eyed Peas) 133 Normal 03:34 ±00:02
Take on Me (A-ha) 170 Normal 03:36 ±00:04
Mean 158.50
Total 21:01 ±00:13
% game time 86.94% ±1.83
(continued on next page)
Bronner et al
Am J Health Behav.™ 2013;37(3):369-380 373 DOI: http://dx.doi.org/10.5993/AJHB.37.3.10
campus (ethnicity: 3 black, 1 Chinese, 1 Indian,
and 2 white), a wide age range from 18 to 53, and
participated in moderate to vigorous levels of phys-
ical activity prior to this study. Generally, partici-
pants trained for one hr per session for 10 – 15
hrs/game over a period of 4 to 6 weeks to achieve
the required advanced competency. When players
reached this competency, they were then tested on
that game.
Effect of Game Play on Energy Expenditure
From the indirect calorimetry data, we compared
energy costs in the 5 exer-games (Table 2). Mean
game play HR differed across exer-games [F(4,24)
Table 1 (continued)
Exer-game Temporal Parameters
Game
(total time) Song (Artist) Beats·min-1 Level Song Length (min)
Kinect Dance Central Poker Face (Lady Gaga) 120 Hard 02:15 ±00:01
(19:50 ±01:19) I Know You Want Me (Pitbull) 128 Hard 02:13 ±00:04
Evacuate the Dance Floor (Cascada) 140 Hard 01:55 ±00:05
Galang ’05 (M.I.A.) 101 Hard 02:20 ±00:02
Can’t Get You Out of My Head (Kylie
Minogue) 126 Hard 02:03 ±00:02
Move Ya Body (Nina Sky) 128 Hard 02:05 ±00:18
Mean 123.83
Total 12:50±00:20
% Game Time 64.94% ±4.12
Note.
Abbreviations: Min, minutes; DDR, Dance Dance Revolution
Table 2
Physiological Measurements During Gameplay
StepMania Wii-DDR K-JD3 Wii-JD3 K-DC
VO2 mL·kg-
1·min-1 31.72 (4.02) 20.05 (1.37) 23.71 (2.22) 14.69 (2.59) 14.64 (3.64)
range 27 - 38 18 - 23 20 - 27 10.0 - 17.0 10.0 - 21.0
RER 0.94 (0.04) 0.94 (0.08) 0.90 (0.03) 0.87 (0.03) 0.88 (0.06)
range 0.87 - 1.00 0.78 - 1.04 0.85 - 0.93 0.84 - 0.90 0.79 - 0.99
HR beats·min-1 152.66 (14.69) 126.18 (14.54) 136.32 (17.75) 112.53 (15.76) 106.61 (8.68)
range 135 - 174 111 - 145 119 - 170 90 - 131 95 - 121
EE Kcal·min-1 11.08 (2.52) 7.37 (2.21) 8.69 (2.99) 5.42 (2.29) 5.35 (2.16)
range 8.3 - 14.4 4.7 - 10.0 5.2 - 12.4 2.5 - 9.2 2.5 - 8.6
MET 9.06 (1.15) 5.73 (0.39) 6.77 (0.63) 4.20 (0.74) 4.18 (1.04)
range 7.7 - 10.8 5.2 - 6.4 5.8 - 7.6 2.8 - 5.0 2.8 - 5.9
Note.
Wii-DDR, Wii Dance Dance Revolution; K-JD3, Kinect Just Dance 3; Wii-JD3, Wii Just Dance 3; K-DC, Kinect Dance
Central; VO2, volume of oxygen consumption; RER, respiratory exchange ratio; HR, heart rate; EE, energy expenditure;
MET, metabolic equivalent
Energy Cost and Game Flow of 5 Exer-games in Trained Players
374
= 91.751, p = .000]. In post hoc pairwise compari-
sons, HR was highest during StepMania (152.66 ±
14.68 beats·min-1) compared to the other games
(p < .011). K-JD3 (136.32 ± 17.75) and Wii-DDR
(126.18 ± 14.54) also exceeded Wii-JD3 (112.53 ±
15.76) and K-DC (106.61 ± 8.69) (p < .020). To-
tal game play MET levels were highest when play-
ing StepMania (9.06 ± 1.15) [F(4,24) = 78.594, p =
.000; post hoc pairwise comparisons: StepMania v
Wii-DDR, Wii-JD3, and K-DC, p < .003]. Next high-
est MET levels were K-JD3 (6.77 ± .63) and Wii-
DDR (5.73 ± .39 MET). They exceeded the 2 lowest,
Wii-JD3 (4.19 ± .74 MET) and K-DC (4.18 ± 1.04
MET) (p < .039). Mean energy expenditure and VO2
results displayed similar patterns.
Maximal Exercise Test and Relative Workout
Mean ±SD resting VO2max were 3.05 ± .55 mL/
kg/min (Table 3). Resting HR were 69.11 ± 6.90
beats·min-1. All participants were able to com-
plete most of Stage 4 of the Bruce protocol. Mean
±SD VO2max and HRmax were 45.25 ± 12.50 mL·kg-
1·min-1 and 183.88 ± 14.60 beats·min-1 respec-
tively. Mean VO2R were 42.20 ± 12.82 mL·kg-
1·min-1. Mean video-game workout relative to
maximal exercise values revealed a range of 81 to
Figure 1
Exer-game VO2 Relative to VO2 Reserve
Table 3
Resting and Maximal Treadmill Test Results
_____________________________________________________________________
VO2 Rest
mL·kg-1·min-1
HR Rest
beats·min-1
VO2max
mL·kg-1·min-1
HRmax
beats·min-1
VO2 Reserve
mL·kg-1·min-1
Males 2.87 (0.60) 67.09 (7.20) 48.04 (14.41) 183.25 (14.53) 45.17 (14.76)
Females 3.29 (0.45) 71.80 (6.78) 41.54 (11.02) 184.71 (17.91) 38.255 (11.20)
Total 3.05 (0.55) 69.11 (6.90) 45.25 (12.50) 183.88 (14.60) 42.20 (12.82)
_____________________________________________________________________
Note.
VO2, volume of oxygen consumption; Rest, resting; HR, heart rate; VO2max, maximal VO2; HRmax, maximal heart rate
Bronner et al
Am J Health Behav.™ 2013;37(3):369-380 375 DOI: http://dx.doi.org/10.5993/AJHB.37.3.10
37% of VO2R and 83 to 58% of HRmax (Figures 1
and 2). Mean game play % VO2R differed across
exer-games [F(4,24) = 52.635, p = .000]. In post
hoc pairwise comparisons, StepMania, at 81%
VO2R, exceeded all other games (p < .008) with the
exception of K-JD3 (61% VO2R). K-JD3 and Wii-
DDR both exceeded Wii-JD3 and K-DC (p < .035).
There were no differences between Wii-JD3 and
K-DC. Similarly, mean game play % HRmax also dif-
fered across exer-games [F(4,24) = 196.652, p =
.000]. StepMania, at 83% HRmax, exceeded all oth-
er games (p < .008) in post hoc pairwise compari-
sons. Wii-DDR and K-JD3 also exceeded Wii-JD3
and K-DC (p < .020). There were no differences
between Wii-JD3 and K-DC.
Temporal Parameters
Due to the distinct differences between exer-
games in energy cost, we calculated the tempo-
ral parameters of each game. Mean ± SD song
beats·min-1 for all games were 151.57 ± 15.50
(Table 1). Songs in 4 of the games averaged 158.50
beats·min-1 (StepMania, Wii-DDR, K-JD3, and
Wii-JD3), whereas K-DC songs averaged 123.83
beats·min-1 (Table 1). During StepMania game
play, total game time, from onset of the start menu
to the end of the sixth game song, was 10:16 min.
Participants spent 88% of their time in active play
and 12% in downtime waiting for software to load
or moving through menu selections. In Wii-DDR,
in which participants played the same songs as in
StepMania, total play time from onset of the start
menu to the end of the sixth game song was 14:19
min. However, participants spent only 65% of their
time in active play and 35% in downtime. Songs in
StepMania and Wii-DDR ranged from 1:25 to 1:39
min. During Just Dance 3, total play time from on-
set of the start menu to the end of the sixth game
song was 25:50 and 24:11 min for the Kinect and
Wii respectively. The range of song lengths was
2:24 – 4:07 min. Participants spent 81% of their
time in active play and 19% in downtime when
playing on the Kinect platform (K-JD3) versus 87%
in active play and 13% in downtime when play-
ing on the Wii platform (Wii-JD3). K-DC total game
time was 19:50 min. The range of song length was
1:55 – 2:20, and range of time between songs was
1:10 – 1:26 min. Participants spent 65% of their
time in active play and 35% in downtime.
Game Flow Questionnaire and Player Experience
Video Game Training Effect Questionnaire
scores differed across exer -games [F(4,24) = 8.763,
p = .025]. Post hoc pairwise comparisons were not
signicant. The highest game ow scores, indicat-
ing a positive experience, were found for StepMa-
nia (93.88 ± 3.05%) and lowest for K-DC (74.90 ±
21.62%) and Wii-JD3 (60.00 ± 22.42%) (Figure 3).
There was a moderate positive correlation between
game ow and VO2 values as well as game ow and
MET values (r = .57 and r = .59 respectively).
In follow-up interviews, players reported frustra-
tion with game usability features such as excessive
layers of menu feature selections, unresponsive
controls, and load times. They considered these
features to affect a game’s playability and be de-
Figure 2
Exer-game Heart Rates Relative to HRmax
Energy Cost and Game Flow of 5 Exer-games in Trained Players
376
terrents for their willingness to continue playing
that game. This was particularly the case for K-DC.
DISCUSSION
Exer-games can be appealing to those with time
constraints and may help individuals of all ages
achieve moderate or vigorous levels of activity.8
However, there is a need to examine the efcacy
of playing exer-games to meet PA guidelines. Pre-
vious research has focused on the exercise re-
sponse to exer-games in novice players.45 This
study describes the efcacy of a variety of dance
exer-games to meet PA levels when players are well
trained and which games provided a positive game
ow experience.
Game Play and Energy Expenditure
We found a range of physiologic values in the 5
games we tested, from moderate-intensity activity
during Wii-DDR, Wii-JD3, and K-DC to vigorous-
intensity levels during StepMania and K-JD3. Step-
Mania and K-JD3, with vigorous-intensity MET
levels, represent a game that required jumping on
a sensor pad (StepMania) and a full-body move-
ment game (K-JD3). Yet a variation of the same
game that required jumping on a sensor pad, Wii-
DDR, resulted in only moderate-intensity MET lev-
els. Similarly, the game, JD3, displayed very differ-
ent results depending on the platform upon which
it was played. Played on the Kinect, participants
attained vigorous-intensity PA levels, whereas
when played with the Wii controller, participants
attained only moderate-intensity PA levels.
To ascertain whether group calculations masked
specic subject physiological measures, we calcu-
lated workout relative to VO2R and HRmax for each
of the 7 participants. Participants’ game play in-
tensity ranged from 83 to 58% of HRmax and 81
to 37% of VO2R. The American College of Sports
Medicine ofcially recommends that optimal exer -
cise intensity to improve cardiovascular tness be
between 70% and 74% of HRmax and between 50
and 85% VO2R (the difference between maximal
oxygen uptake and resting oxygen uptake).46 Only
StepMania and K-JD3 were within both of these
recommended ranges.
The physiologic values found in this study may
be higher than those previously reported for sev-
eral reasons. First, the low level of energy expen-
diture recorded during many games suggests that
some games are not capable of getting players to
consistently move in a way that reects adequate
energy expenditure. This may stem from players’
having little training to play the games when their
energy exertion was tested.17,19,26,47,48 Additionally,
some games may suggest full-body motions but,
in actuality, require only small movements such
as wrist icks to achieve the highest game score.
We found this to be the case in Wii-JD3 game play.
Game Play and Temporal Parameters
What caused the large differences between
games in physiological measures? The same 6
Figure 3
Video Game Training Effect Questionnaire Score
Bronner et al
Am J Health Behav.™ 2013;37(3):369-380 377 DOI: http://dx.doi.org/10.5993/AJHB.37.3.10
game songs were played during StepMania and
Wii-DDR, at the same tempo. When we considered
song tempo (beats·min-1), length of game songs,
and length of game play, we found that differenc-
es in game design can produce large differences
in workout energy expenditure. StepMania game
play was 10:16, whereas Wii-DDR was 14:18 min
in length. The difference lay in menu loading and
selection time. This resulted in a drop in overall
energy cost during Wii-DDR game play. However,
K-JD3 and Wii-JD3 had relatively similar lengths
of game play (more than twice that of StepMania)
while playing the same 6 songs, and these songs
had a mean tempo that was similar to those in
StepMania and Wii-DDR. The drastic drop in en-
ergy cost between K-JD3 and Wii-JD3 is attributed
to the different controllers that affected how par -
ticipants played the game. During K-JD3, the Ki-
nect requires whole-body movements in order to
score well during game play. However, only suf-
cient arm movement of the Wii device was required
to score well. It was observed that participants
who initially danced with whole-body movements
during Wii-JD3 game play did not score as well
as those who focused on one-armed wrist icks.
All players quickly learned to modify and curtail
their movements in order to maximize their game
scores.
During K-DC, participants played for a longer
period than during StepMania and Wii-DDR but
shorter than K-JD3 and WiiJ-D3. The K-DC is a
full-body game played on the Kinect platform, sim-
ilar to K-JD3. However, song tempos were slower,
and menu loading and selection times were pro-
longed. This resulted in the lowest workout energy
expenditure.
Game Play and Player Engagement
The second goal of this study was to evalu-
ate the interaction of metabolic expenditure and
player engagement across dance exer-games us-
ing several types of hardware platforms and in-
teractive devices. It is important to understand
this relationship as the development of interactive
motion-based video games has shown promise in
introducing moderate to vigorous exercise to the
increasing numbers of individuals leading seden-
tary lifestyles. To determine the extent of this re-
lationship, we evaluated the human-computer in-
teractions of play and perceived experience with a
game ow questionnaire.
The ow experience is dependent upon the per-
ception of the individual, and can be a powerful
motivator to continue or return to the activity.
Flow theory as applied to sports suggests a posi-
tive association between ow state and peak per -
formance. 49 What distinguishes active games and
sports from general exercise is the challenge and
competition of a score. What further differentiates
the exer-games in this study from most sports is
music. Synchronous music, employed in these
games, has been demonstrated to increase psycho-
motor arousal levels, reduce ratings of perceived
exertion, and enhance positive feeling states as
well as increase the length of PA.35 The motivating
factor of dance exer-games, that the participant
perceives that he or she is “dancing” or “playing”
not “exercising,” may inuence the intensity and
energy expended during game play.
Flow is less well studied in movement-based hu-
man-computer interfaces. With the increasing va-
riety of movement-based input systems, we felt it
would be useful to compare metabolic results to a
game ow questionnaire that included statements
related to each of the 8 ow elements. Results
from the game ow questionnaire indicated that
the most positive game ow experience occurred
during StepMania game play whereas the least
positive player experiences occurred during K-DC.
Interestingly, the more positive the game ow ex-
perience, the greater the mean energy expenditure
was measured. This indicated possible frustration
with games that have more downtime when the
player has to move through multiple selection op-
tions to reach the next song game or is waiting for
software to load.
Another consideration in game ow and immer-
sive game play experiences is whether the amount
of movement correlates to the amount of engage-
ment.50 We found moderate correlations between
game ow and VO2 and MET values, suggesting
that this may be the case. Studies using motion-
capture quantication of movement are currently
underway to test this hypothesis further.
The negative game ow ndings associated with
K-DC and Wii-JD3 suggest that not all game move-
ments have the ability to promote engagement, so-
cial interaction, and further movement. The sec-
ond lowest game ow scores reected disrupted
playability during K-DC, the game with the longest
wait time. The combined duration of noninterac-
tive game time present at the beginning and end
of each game song dramatically decreased the ra-
tio of active to nonactive game play resulting in
35% downtime. Furthermore, users did not have
a full understanding or appreciation of the free-
style portion of the dance sequences. There was
no feedback of what users should do during these
times. Players tended to stand and watch them-
selves rather than continue to move, which also
led to inactivity. K-DC freestyle did not contribute
to game scores, so with no challenge most players
opted out. Additionally, the noninteractive posing
by the screen avatar at the end of a game song in
K-DC contributed at least 20s of downtime, which
the user was not able to skip. The ratio of move-
ment to nonmovement not only impacted the MET
and HR associated with the workout component of
the game, but also appeared to contribute to the
negative ow associations with the game.
The negative game ow ndings associated with
Wii-JD3 (slightly less wait time than K-JD3) did
not appear to reect disrupted playability. Instead,
based on questionnaire answers and interviews,
Energy Cost and Game Flow of 5 Exer-games in Trained Players
378
players appeared frustrated about the mismatch
between the dance movements and controller con-
trol. Players complained of wrist pain, did not have
fun, and reported an overall lack of immersion. Six
out of 7 said they would not be willing to continue
to play this game as a workout and would prefer a
different exer-game.
The lowest game ow scores, found in Wii-JD3,
also reected the lowest mean MET values. This
was a case in which players learned that full-body
movements were unnecessary to achieve high
scores. Five out of 7 players reported that the game
did not give the right amount of challenge. Both
proprioceptive feedback and mimicry of move-
ments affect immersion in movement-based video
games.51 The lack of natural whole-body move-
ments necessary to play Wii-JD3 as well as the un-
natural proprioceptive feedback of the Wii control-
ler (jerky movements of the right wrist and hand
were rewarded more than full dancing) may have
contributed to the low game ow scores. In sum-
mary, lowest game ow scores were split between
2 types of controllers, the Wii and Kinect, and 2
different games, K-DC and Wii-JD3. Interestingly,
Wii-DDR and K-JD3, also on 2 different platforms,
reected much higher scores. Therefore, we sur-
mise there must be an interaction between plat-
form technology and game design features that re-
ect the immersion of the player.
Pasch et al suggested that movement-based game
design should focus on creating a balance between
challenge and skill.51 Although this is important,
our ndings about the interruption of game ow
immersion by nonplay elements such as software
loading time, layers of menu selection, and game
scores that do not reect the dance movements
portrayed on the screen, suggest other key areas
must be considered in optimal exer-game design.
Limitations
There were several limitations in this study. Al-
though our sample size was small, participants
reected a broad ethnic, gender, and age sample.
However, these results cannot be generalized to
children.
We studied only 3 platforms. The game engine
and platform environments of the game inuenced
load times. However, we selected commonly used
platforms, the WiiTM and Xbox consoles, that repre-
sent 2 of the current best-selling game consoles.52
The same songs were not selected across games
due to the available play lists. However, we were
able to compare the same songs on 2 different
pairs of games.
The length of testing for the 5 games varied
widely due to song length and menu loading times.
Although players played 6 songs per game, Step-
Mania game play and testing lasted only 10 min,
whereas JD3 game play lasted up to 25 min. Gen-
erally, these players played each game for 60 min/
session while training. Therefore, playing StepMa-
nia offers a substantially better workout with more
calories burned than in any of the other games.
Future Exer-game Considerations
Exer-games potentially offer an engaging experi-
ence.1,16,50 Even so, designing games that provide
a balance of challenge, immersion, and engage-
ment simultaneously is a difcult task. Although
this study limited analyses to 5 games, usability
elements such as software loading and menu se-
lection times had a dramatic effect on the work-
out and game ow experience. The incorporation
of physiological and psychological testing during
game development can help to enhance the work-
out and player experience.
Exer-games offer workout alternatives in the win-
ter or extreme weather, when outdoor activities are
curtailed. However, to avoid player boredom, it is
important to have a broad number of game song
options to provide new and increased challenges.
As one of the original dance exer-games, DDR now
has hundreds of game songs to choose from. The
open source StepMania has enabled DDR players
to assemble their own game songs and choreogra-
phy, which adds thousands more. Additional game
songs will undoubtedly be issued for the newer plat-
forms for consumers to combat player boredom.
Conclusion
Vigorous workout levels were achieved with 2
of the 5 exer-games studied. Players also found
these games to be most engaging. These results
will assist in the selection of effective and enjoy-
able workout and play options. However, interface
elements can interfere with an optimal workout,
ow experience, and, potentially, the motivation
of the player to return to play again. Physiological
measurement and game ow testing during game
development may help to optimize the exer-game
player activity and experience. Video games are
mainstream. They are now included in the Com-
pendium of Physical Activities: from sedentary
video games to exer-games.53 As more games are
released, it will be challenging to keep this up to
date. More recently, the President’s challenge has
added playing active video games to the list of PA
to achieve the challenge in the Presidential Active
Lifestyle Awards (PALA+). Game developers may
wish to include information about the MET poten-
tial of their games for the consumer.
Human Subjects Statement
The experiments in this research comply with
the ethical standards, current laws, and regula-
tions of the country in which they were performed
and were approved by the university institutional
review board.
Conict of Interest
The authors have no nancial relationships
with the organization that sponsored this re-
search or other conicts relevant to this article
to disclose.
Bronner et al
Am J Health Behav.™ 2013;37(3):369-380 379 DOI: http://dx.doi.org/10.5993/AJHB.37.3.10
Acknowledgments
The authors thank Rutika Naik, Alex West, and
Zawadi Williams-Murray for their help in data
processing. This project was partially funded by
a Health Games Research grant from the Robert
Wood Johnson Foundation Pioneer Portfolio.
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... However, both Bronner et al. (2013) and Stroud et al. (2010) argued playing video games contains measures of physical exertion based upon measurements of an individual's basal metabolic rate (MET). According to the American College of Sports Medicine (2014), METs are a useful, convenient, and standardised way to measure the intensity of physical activities. ...
... Based upon these definitions, Bronner et al. (2013) found individuals participating in video games involving dancing saw between a 4-9 METs increase, which is similar to sports like golf and bowling. Stroud et al. (2010) found players using Nintendo Wii controllers were able to raise their METs to qualify between light and moderate activity levels. ...
... However, both Bronner et al. (2013) and Stroud et al. (2010) argued playing video games contains measures of physical exertion based upon measurements of an individual's basal metabolic rate (MET). According to the American College of Sports Medicine (2014), METs are a useful, convenient, and standardised way to measure the intensity of physical activities. ...
... Based upon these definitions, Bronner et al. (2013) found individuals participating in video games involving dancing saw between a 4-9 METs increase, which is similar to sports like golf and bowling. Stroud et al. (2010) found players using Nintendo Wii controllers were able to raise their METs to qualify between light and moderate activity levels. ...
... Υπάρχουν κάποιες λίγες εξαιρέσεις όπως διαγωνισμοί χορού μέσω βιντεοπαιχνιδιών, στους οποίους ερευνητές εντόπισαν ότι οι παίκτες είχαν παρόμοιες μετρήσεις οξυγόνου και ρυθμό μεταβολισμού με ανθρώπους που εκτελούσαν ασκήσεις γυμναστικής (e.g. Bronner et al., 2013). Μία άλλη έρευνα σύγκρινε τα επίπεδα κορτιζόλης, μίας ορμόνης που θεωρείται η κατεξοχήν ορμόνη του στρες, μεταξύ pro gamers των esports και κορυφαίων παικτών σε κλασσικά sports. ...
Thesis
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H εργασία αυτή έχει ως σκοπό να χρησιμοποιήσει «φακούς» που θα μπορέσουν να αναδείξουν νέα στοιχεία και οπτικές των βιντεοπαιχνιδιών. Ένας «φακός» είναι η πολιτιστική βιομηχανία όπως ορίστηκε από τη σχολή της Φρανκφούρτης. Ένας ακόμα σημαντικός «φακός» είναι τα έργα του Φουκώ κυρίως αυτά που συσχετίζονται με τον νεοφιλελευθερισμό. Με αυτούς τους φακούς το «βλέμμα» μας μπορεί να εντοπίσει τα στοιχεία και τις δυνάμεις που σχηματίζουν και κινούν τον κόσμο και την κουλτούρα των βιντεοπαιχνιδιών. Αυτά τα στοιχεία με τη σειρά τους ανατροφοδοτούν τις κοινωνικές επιστήμες και προσφέρουν χρήσιμες πληροφορίες για την ανάλυση του σύγχρονου κόσμου. Η εργασία περιέχει μία σύντομη περιγραφή της βιομηχανίας των video games, της έννοιας του νεοφιλελευθερισμού και της εξουσίας κατά Φουκώ ενώ παράλληλα παρουσιάζεται η έννοια της πολιτιστικής βιομηχανίας όπως έχει οριστεί από τη σχολή της Φρανκφούρτης. Στην συνέχεια χρησιμοποιούνται οι παραπάνω έννοιες ώστε να γίνει μία ανάλυση της πολιτιστικής βιομηχανίας των βιντεοπαιχνιδιών. Η ανάλυση αυτή επικεντρώνεται στα e-sports και στην συμμετοχική κουλτούρα που διέπει τον κόσμο των video games. Προσπαθώντας λοιπόν στα πλαίσια αυτής της εργασίας να γνωρίσουμε και να κατανοήσουμε την πολιτιστική βιομηχανία των βιντεοπαιχνιδιών καταλήγουμε τελικά να αντιληφθούμε και να εξηγήσουμε τους μηχανισμούς της σύγχρονης κοινωνίας και των υποκειμένων.
... For instance, Sweetser and Wyeth [1] proposed the GameFlow model of player enjoyment for the flow analysis. Previous research studies have extensively used this model in the design and evaluation phase of serious games (e.g., [2,3]) and other types of games (e.g., [4]). Other techniques for the flow analysis include using flow scales such as Flow State Scale-2 and Dispositional Flow Scale-2, which are based on the flow dimensions initiated by Csikszentmihalyi [5]. ...
Conference Paper
Game flow analysis has been widely used to examine the player’s enjoyment in a game. In this paper, we presented the game flow results of ARTé: Mecenas by adopting the EGameFlow scale. We adapted questions in the questionnaire from the EGameFLow scale, which formed six game flow factors – Concentration, Goal Clarity, Challenge, Autonomy, Immersion, and Knowledge Improvement. From our findings, the students overall enjoyed the game. They were able to concentrate on the learning tasks in the game. They received clear goals at the beginning of the game and each game level. The challenges in the game tasks improved their understandings of the content knowledge. Their senses of controlling the game continuously increased during the gameplay. The students increased their content knowledge after the gameplay, though they could not decide if they were emotionally involved. In addition, we found that the content knowledge in the game, game levels and visuals could influence the player’s game experience.
... Game experience consists of several components, including flow, a state in which there is a balance between the difficulty of the task and the skills that the players possess. Video gaming is one of the best ways to induce the sense of flow (Sherry, 2006), and is positively related to physiological parameters like higher energy expenditure (Bronner et al., 2013). Game flow may increase intrinsic motivation (Plummer et al., 2017), and with the occurrence of flow, players become immersed in the game. ...
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We studied how usability and playability of sport exergames affect future intentions of participation in physical activity or actual sport. We employed questionnaires to measure participants’ enjoyment, usability, game-experience, and future intentions of physical activity and real sport. We compared the outcomes based on players’ gender, previous real-swimming, and exergame experience. Psychological parameters were not different between groups but players without exergame experience enjoyed the game more. Physical activity intentions increased for all participants but not swimming intentions. The limitations of current gaming systems and their effects on players’ gaming experience and intentions are discussed.
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The purpose of this study was to quantify the misapplication and misinterpretation of the current American College of Sports Medicine (ACSM) exercise intensity guidelines for cardiorespiratory fitness. A literature review (January 2000 to January 2007) was completed identifying studies conducted on the effects of aerobic exercise training on cardiorespiratory fitness in healthy adults. Studies (N=15) were identified in which exercise intensity was prescribed by a percentage of maximal oxygen uptake (%VO2max) rather than a percentage of oxygen uptake reserve (%VO2R) (a misapplication). Eight instances of misinterpretation were identified; referencing the current ACSM guidelines, but citing intensity in terms of %VO2max. Recent research demonstrating that percentage of heart rate reserve (%HRR) is more closely aligned to %VO2R, not %VO 2max, prompted a change in the ACSM exercise intensity guidelines in 1998. Despite the ACSM's recommendation of the use of %VO2R, present findings suggests the frequent use of %VO2max (misapplication) in the methodology of aerobic training studies. The ACSM exercise prescription recommendations are the most recognizable guidelines for exercise professionals, and it is the responsibility of authors and reviewers to ensure correct interpretation and reporting in future publications. Continued use of exercise intensity prescribed by %VO2max perpetuates an out-of-date recommendation and results in unequal training stimuli for individuals with dissimilar fitness levels. We recommend exercise professionals integrate the current intensity guidelines into both research and practice.
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Empirical studies have validated that basic needs satisfaction supported by video game play predicts motivation and engagement outcomes. However, few studies specifically manipulated game features for each of the three basic needs specified in the self-determination theory (SDT) to examine how the game features impact players' need satisfaction and game experience. The current study employed an in-house developed exergame and manipulated the game features in a 2 (autonomy-supportive game features: on vs. off) × 2 (competence-supportive game features: on vs. off) experiment to predict need satisfaction, game enjoyment, motivation for future play, effort for gameplay, self-efficacy for exercise using the game, likelihood of game recommendation, and game rating. The manipulated game features led to the corresponding need satisfaction. Manipulated autonomy-supportive and competence-supportive game features had main effects on most motivation and engagement outcomes. Need satisfaction of autonomy and need satisfaction of competence were both found to be mediators for the relationships between the game features and the motivation and engagement outcomes. The findings add evidence to support the underlying mechanism postulated by SDT for media enjoyment and motivation as well as the emerging entertainment research conceptualizing enjoyment as need satisfaction. The findings also have practical implications for intervention effort that intends to capitalize the motivational pull of video games.
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Physical inactivity is a risk factor for heart disease, diabetes, and obesity. Efforts to increase physical activity can include active video games. While many active video games demonstrate exertion levels commensurate with light to moderate exercise, it is unclear whether these games can meet requirements for vigorous activity. The purpose of this study was to determine whether the active video game, Dance Dance Revolution (DDR), can provide vigorous exercise in a wide range of adults. Twelve adults (18 to 53 yrs, BMI 18 to 37) were studied while playing DDR at an advanced level. Metabolic measures were collected during a 30 min game-play protocol at the advanced "Heavy" level of difficulty. Mean values achieved were the following: 8 METs, heart rate 157 beats·min -1, and energy expenditure 9 kcal·min -1. DDR is played similarly to that of interval type exercise where each game-song is followed by a brief rest period. Subjects reported that DDR is fun, and that the competitive nature of playing with others is enjoyable. This study found that DDR is effective in meeting vigorous physical activity requirements for improving or maintaining physical fitness.
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