Male dance moves that
catch a woman’s eye
Nick Neave1,*, Kristofor McCarty1,
Jeanette Freynik2, Nicholas Caplan1,
¨nekopp1and Bernhard Fink2
School of Life Sciences, Northumbria University, Newcastle upon Tyne
NE1 8ST, UK
Department of Sociobiology/Anthropology, Institute of Zoology and
Anthropology, University of Go
*Author for correspondence (email@example.com).
Male movements serve as courtship signals in
many animal species, and may honestly reﬂect
the genotypic and/or phenotypic quality of the
individual. Attractive human dance moves, par-
ticularly those of males, have been reported to
show associations with measures of physical
strength, prenatal androgenization and sym-
metry. Here we use advanced three-dimensional
motion-capture technology to identify possible
biomechanical differences between women’s
perceptions of ‘good’ and ‘bad’ male dancers.
Nineteen males were recorded using the ‘Vicon’
motion-capture system while dancing to a basic
rhythm; controlled stimuli in the form of avatars
were then created in the form of 15 s video clips,
and rated by 39 females for dance quality. Initial
analyses showed that 11 movement variables were
signiﬁcantly positively correlated with perceived
dance quality. Linear regression subsequently
revealed that three movement measures were
key predictors of dance quality; these were varia-
bility and amplitude of movements of the neck
and trunk, and speed of movements of the right
knee. In summary, we have identiﬁed speciﬁc
movements within men’s dance that inﬂuence
women’s perceptions of dancing ability. We
suggest that such movements may form honest
signals of male quality in terms of health,
vigour or strength, though this remains to be
Keywords: movement; courtship signal; dance quality;
In 1859, Charles Darwin proposed that certain male
traits evolved owing to sexual selection via female
mate choice . Since then much emphasis has been
placed on conspicuous male secondary sexual orna-
ments and associations between such ornaments and
female mate preferences . However, such orna-
ments are not present in all mammalian species, and
some authors have suggested that females may evaluate
males largely on the quality of their movements,
especially those movements that contain elements of
vigour and/or skill, because these are most likely to
indicate health and genetic quality . Evidence
from birds, ungulates and crustaceans demonstrates
that females detect subtle variations in male motor per-
formance during ritualized courtship displays, and
base subsequent reproductive decisions upon such
differences [4–6]. In humans, dance is a set of inten-
tional, rhythmic, culturally inﬂuenced, non-verbal
body movements that are considered to be an impor-
tant aspect of sexuality and courtship attraction;
indeed, dancing often forms part of courtship and
marriage celebrations [7,8]. Dancing ability, particu-
larly that of men, may serve as a signal of male mate
quality in terms of physical strength , prenatal
androgenization  and symmetry , and thus
affect women’s perceptions of men’s attractiveness
(for review see Hugill et al.).
Identifying the characteristics of attractive dance in
natural settings is difﬁcult because of the confounding
effects of facial attractiveness , height , cloth-
ing and socioeconomic status , dominance ,
body morphology and shape . Previous studies
assessing women’s perceptions of male dancing ability
have attempted to control for these factors using
blurred video clips [9,18] or simple motion-capture
avatars . Here, we improve this methodology
further using more realistic three-dimensional avatars
from which precise biomechanical measurements can
be extracted. To our knowledge, no previous studies
have actually identiﬁed speciﬁc movement components
within a dance that may inﬂuence perceived dance
quality, a gap we aimed to ﬁll in our study. Males
danced for 30 s to the same basic drum rhythm and
their movements were mapped onto computer-generated
avatars, which females rated for dance quality.
Biomechanical analysis allowed the amplitude, speed,
duration and variability of body movements to be calcu-
lated. Analysis was concentrated on three body regions:
legs (ankle, hip and knee), arms (shoulder, elbow and
wrist) and the central body (neck and trunk).
2. MATERIAL AND METHODS
An initial sample of 30 men aged 18 –35 (mean ¼22.72, s.d. ¼4.37)
took part in the investigation, none of whom were professional dan-
cers, or had any physical injuries or current health problems which
could have affected their movements. Body height and mass were
measured, in addition elbow, ankle and wrist widths were measured,
as well as leg lengths in order to accurately calculate angle data in
A 12-camera optical motion-capture system (Vicon 612, Vicon,
Oxford) was used, running Vicon workstation v.4.6 software. Each
camera captured at a constant rate of 100 Hz. Thirty-eight 14 mm
reﬂective markers were attached to each participant in accordance
with the Vicon Plug-In-Gait marker set to capture all the major struc-
tures of the body. Participants were requested to perform one static
drum beat to eliminate music likeability as a possible confound. Partici-
pants were not given any prior instruction on how they should dance.
For avatar construction, it is vital that all the markers should be
recognized, and that all optical data are complete and does not con-
tain any gaps. Often, the reﬂective markers become detached, or are
occluded by arm movements. If this occurs to any marker during a
trial, the necessary joint angles cannot be calculated. Eleven partici-
pants were thus excluded from the study owing to incomplete marker
capture, leaving 19 male dancers. Their motion-capture data were
used to animate a virtual character (an avatar), using Autodesk
MotionBuilder, 2010. The avatar chosen was a featureless, gender-
neutral humanoid character that was included in the software
package in order to put maximum emphasis on the biological
movement (ﬁgure 1).
Using these avatars, 37 heterosexual women aged 18– 35
(mean ¼22.30, s.d. ¼6.22) rated dance quality for all 19 male
dancers in a serial, randomized order based on a 15 s episode
(middle section of each dance) shown in an 800 600 pixel
window centred on a 15.4 inch laptop screen (1440 900 pixel
Electronic supplementary material is available at http://dx.doi.org/
10.1098/rsbl.2010.0619 or via http:// rsbl.royalsocietypublishing.org.
Received 7 July 2010
Accepted 18 August 2010 This journal is q2010 The Royal Society
resolution) using MEDIALAB v. 1.33 (Empirisoft Inc., New York, NY,
USA). The core audio track was not presented to raters. Immediately
after each presentation of a dancer, participants made a judgement of
dance quality on a seven-point Likert-type scale (from 1 ¼extremely
bad dancer to 7 ¼extremely good dancer). After each rating, the
participant was prompted to move on to the next rating segment. Sub-
sequent analyses were based on mean ratings (M¼3.7, s.d. ¼0.8,
A kinematic model (Plug-In-Gait, Vicon, Oxford) was used to
generate three-dimensional joint angles for the knees, hips, trunk,
neck, shoulders and wrists. Ankle angle was calculated in two dimen-
sions (ﬂexion/extension and internal/external rotation) and for the
elbow in one dimension (ﬂexion/extension). Each joint angle was ﬁl-
tered using a second-order Butterworth low-pass ﬁlter with a cut-off
frequency of 10 Hz. Simple visual inspection of the angles showed
that they ﬂuctuated in magnitude in a series of unidirectional move-
ments. The amplitude and duration of each unidirectional movement
were calculated as the angular displacement and time, respectively,
between successive reversals in direction. The mean speed of each
angular movement between direction reversals was calculated as
the amplitude divided by the duration. The change in the magnitude
of each joint angle from the mean joint position for the entire trial
(angular offset) was determined at each movement reversal. Move-
ment variability was then calculated as the standard deviation of all
angular offsets for each joint angle. Because of the large number of
joint angles produced (n¼38), movement amplitude, duration,
speed and variability were each grouped by body region, after ensur-
ing that the variance in variables within each body segment was
similar. Three body regions were generated, including the legs
(ankles, knees and hips), arms (shoulders, elbows and wrists) and
central body (trunk and neck).
Kolmogorov– Smirnov tests were used to check for
normal distribution of each movement variable both
for combined body regions and their constituent
parts. For variables with normal distribution, two-
tailed Pearson product–moment correlations were
performed between mean ratings of dance quality
and each of the three body regions for movement
amplitude, movement variability, movement speed
and movement duration. For variables that were not
normally distributed, Spearman’s rank correlations
were used. If a signiﬁcant correlation was found for
any one body region, a further correlation was per-
formed between ratings of dance quality and the
constituent parts of that body region. A 95 per cent
conﬁdence level was used throughout. A summary of
the signiﬁcant correlations is presented in table 1.
For movement amplitude, all variables were nor-
mally distributed. We found signiﬁcant positive
correlations between dance ratings and the central
body region. Key components comprised of: neck ﬂex-
ion/extension (head nodding), trunk ﬂexion/extension
(forward/backward bending) and trunk abduction/
adduction (sideways bending).
For movement variability, all three body regions
were normally distributed, although seven of their 38
constituent parts were not. We found signiﬁcant posi-
tive correlations between dance ratings and central
body region variability with all components being
important, these were: neck ﬂexion/extension; neck
abduction/adduction (head sideways tilting); neck
internal/external rotation (head shaking); trunk ﬂex-
ion/extension; trunk adduction/abduction; and trunk
internal/external rotation (twisting).
Finally, for movement speed, all data were normally
distributed. We found a signiﬁcant positive relationship
between speed of the legs and dance ratings, the rel-
evant components being speed of right knee ﬂexion/
extension (bending) and speed of right knee internal/
external rotation (twisting).
When the signiﬁcant constituent parts were fed into
a stepwise linear regression to predict dance ratings,
neck internal/external rotation variability (
trunk adduction/abduction variability (
and right knee internal/external rotation speed (
0.38) contributed to the ﬁnal model (F
p,0.001), which accounted for 79 per cent of the
variance in the mean dance ratings.
By using cutting-edge motion-capture technology, we
have been able to precisely break down and analyse
speciﬁc motion patterns in male dancing that seem to
inﬂuence women’s perceptions of dance quality. We
ﬁnd that the variability and amplitude of movements
in the central body regions (head, neck and trunk)
and speed of the right knee movements are especially
important in signalling dance quality. A ‘good’ dancer
thus displays larger and more variable movements in
relation to bending and twisting movements of their
head/neck and torso, and faster bending and twisting
movements of their right knee. As 80 per cent of indi-
viduals are right-footed , greater movements of
the right knee in comparison with the left are perhaps
to be expected. In comparative research, there is exten-
sive literature on the signalling capacities of movement
(see Byers et al.). Researchers have suggested that
females prefer vigorous and skilled males; such cues
are derived from male motor performance that provides
a signal of his physical condition [3–6].
Our data indicate that in humans, certain aspects of
movement amplitude, speed and variability are also
important for female perceptions of male dancing abil-
ity. We suggest that human male movements could also
form honest signals of traits such as health, ﬁtness,
genetic quality and developmental history [9–12],
though this remains to be conﬁrmed. By uncovering
some speciﬁc movement parameters used in the assess-
ments of dance quality, we are now in a much stronger
position to further research the possible signalling
Figure 1. Examples of an avatar created for the rating pur-
poses. (a) Static pose, while (b) shows an avatar ‘dancing’.
2N.Neaveet al. Perception of male dance
mechanisms of dance in humans. Future studies
should systematically manipulate the dance moves
that we have identiﬁed as being most important, and
assess the effects of such manipulations on female
perceptions of dance quality.
We thank Alistair Ewen for his assistance in operating the
Vicon system and three anonymous reviewers for their
helpful comments. This research was supported by the
German Research Foundation (DFG). B.F. is currently
funded by an Emmy-Noether Fellowship of the DFG.
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movement amplitude movement variability movement speed
arms r ¼0.45; p¼0.051 r¼0.44; p¼0.057 r¼0.34; p¼0.153
right shoulder ﬂexion/extension n.a. n.a. n.a.
right shoulder abduction/adduction n.a. n.a. n.a.
right shoulder internal/external rotation n.a. n.a. n.a.
right elbow ﬂexion/extension n.a. n.a. n.a.
right wrist ﬂexion/extension n.a. n.a. n.a.
right wrist abduction/adduction n.a. n.a. n.a.
right wrist internal/external rotation n.a. n.a. n.a.
left shoulder ﬂexion/extension n.a. n.a. n.a.
left shoulder abduction/adduction n.a. n.a. n.a.
left shoulder internal/external rotation n.a. n.a. n.a.
left elbow ﬂexion/extension n.a. n.a. n.a.
left wrist ﬂexion/extension n.a. n.a. n.a.
left wrist abduction/adduction n.a. n.a. n.a.
left wrist internal/external rotation n.a. n.a. n.a.
central body r ¼0.55
;p,0.001 r¼0.41; p¼0.082
neck ﬂexion/extension r¼0.47
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right hip abduction/adduction n.a. n.a. r¼0.02; p¼0.925
right hip internal/external rotation n.a. n.a. r¼0.23; p¼0.337
right knee ﬂexion/extension n.a. n.a. r¼0.52
right knee abduction/adduction n.a. n.a. r¼0.24; p¼0.317
right knee internal/external rotation n.a. n.a. r¼0.70
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left hip abduction/adduction n.a. n.a. r¼0.02; p¼0.944
left hip internal/external rotation n.a. n.a. r¼0.31; p¼0.200
left knee ﬂexion/extension n.a. n.a. r¼0.31; p¼0.193
left knee abduction/adduction n.a. n.a. r¼20.03; p¼0.901
left knee internal/external rotation n.a. n.a. r¼0.34; p¼0.160
left ankle ﬂexion/extension n.a. n.a. r¼20.04; p¼0.886
left ankle internal/external rotation n.a. n.a. r¼20.11; p¼0.646
Denotes signiﬁcant correlations.
Indicates a correlation where the movement variable was not normally distributed.
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