=Paper=
{{Paper
|id=Vol-2166/afcai18-paper8
|storemode=property
|title=Towards Estimating Collective Motor Behavior: Aware of Self vs. Aware of the Other
|pdfUrl=https://ceur-ws.org/Vol-2166/afcai18-paper8.pdf
|volume=Vol-2166
|authors=Lisa Rombout,Martin Atzmüller,Marie Postma-Nilsenová
|dblpUrl=https://dblp.org/rec/conf/afcai/RomboutAP18
}}
==Towards Estimating Collective Motor Behavior: Aware of Self vs. Aware of the Other==
https://ceur-ws.org/Vol-2166/afcai18-paper8.pdf
Towards Estimating Collective Motor Behavior: Aware
of Self vs. Aware of the Other
Lisa E. Rombout, Martin Atzmueller & Marie Postma-Nilsenová
Department of Cognitive Science & Artificial Intelligence, Tilburg University, The Netherlands
{l.e.rombout, m.atzmuller, marie.postma}@uvt.nl
Abstract. Many social activities involve motor-coordination between groups of
people. Especially collective synchronous motor behavior is a complex phenomenon
that has been associated with social bonding and the blurring of self-other bound-
aries. In order to coordinate movement in a group, people have to divide their
attentional resources between the self and others. A group moving in synchrony
can then be viewed as one network or a complex organism, where the behavior
of the network is determined by the individual traits of its nodes and their in-
teraction. In this study, we examine methodological and theoretical approaches
towards measuring both individual traits and group interaction in the context of a
group dance.
Keywords: collective behavior; position sensors; automatic movement tracking; inte-
roception; proprioception; exteroception
1 Introduction
In the performing arts, there are several formal as well as informal theories about what
makes a collaborative performance ’work’. Many of them touch upon the division of
attentional resources, describing the ideal state of a performer as balanced, aware of
their surroundings, and alert. The concept of ’flow’ appears to be related to this ideal,
as does the concept of the ’zéro’ from physical theater [13]. Zéro describes the body
as a tabula rasa, a resting point with the potential of movement. It exists in space and
moves according to the constraints and affordances of the body itself, the space it is in,
and the other bodies around it.
Compared to models of collective animal behavior, we know relatively little about
the processes governing coordinated collective motor behavior in human agents. In or-
der to coordinate successfully, each individual needs to be able to process in a rapid
succession information about the expected position of one’s own body in relation to the
expected position of others. From a modeling perspective, this process can be seen as
a complex network through which the behavior propagates. In order to describe prop-
erties of the network, it is necessary to measure and estimate various behavioral and
relational aspects that may be governed by different sensory and executive mechanisms.
The purpose of our study is to develop and test a range of instruments that can be used
to measure individual dispositional tendencies to perceive certain internal and external
signals and to relate the measures to actual collective performance.
1.1 Interoception, Exteroception and Proprioception
Several studies on embodiment illusions have identified individual differences in how
different categories of sensory input are handled. In general, the distinction is made be-
tween interoceptive, exteroceptive and proprioceptive feedback [12]. For a majority of
people, exteroceptive feedback and specifically vision is the most important informa-
tion used to guide body ownership and agency; a reliance that does not appear to be very
malleable [16, 28]. However, some individuals have a higher interoceptive sensitivity,
which means that they can sense the internal physiological state of their body rela-
tively well [20]. The classical rubber hand illusion approach (using external signals) [8]
does not elicit the embodiment illusion in these individuals [32]. However, an altered
illusion that provides synchronous heart-rate feedback instead (an internal signal) does
work [30].
Interoceptive sensitivity and affect are closely related. Dating back to the James-
Lange theory of emotion [15, 19], the peripheral autonomic changes that accompany
emotional experience can be viewed as an integral part of it, regardless of precise cause
and effect. The occurrence of this physiological affective feedback and an individuals
sensitivity to it have both been shown to affect emotional experience [6, 34]. We there-
fore theorize that individual interoceptive sensitivity might also influence the social
affect experience in a group. Synchronized behavior is present in several human social
practices, such as chanting, marching, dancing, praying, clapping or singing [35]. This
behavior has been shown to influence social bonding in several contexts. For example,
making music and dancing together has an immediate positive effect on the pro-social
behavior of four-year olds [18].
Despite the recent interest in interoception, exteroception, and proprioception as
measures of dispositional tendencies towards certain types of sensory information, few
instruments exist to estimate these properties beyond traditional self-reports. Therefore,
little is known about the effects of, for example, interoceptive disposition on the ability
to coordinate one’s motor behavior with others. In the experiment described below, we
tested a range of newly developed instruments in the context of a group dance. In addi-
tion to measuring the movement of the dancers, we also compared their performance in
three different experimental conditions.
2 Methods
The participants in the study were dance students (N=11) at a dance academy in the
Netherlands. Additionally, the choreographer of the dance was enlisted as the expert
evaluator of the quality of the performed dances (N=1). Participation was voluntary and
informed consent was obtained prior to the collection of all measurements. The dance
students did not receive any form of reimbursement for their participation.
2.1 Pre-pilot practice sessions
Two practice sessions were organized with the dancers to test out the different ap-
proaches to data collection. One of the tested approaches was based on the use of
micro-controllers specifically designed for creating wearables, such as the Arduino
Lilypad [10]. These can be integrated into clothing relatively easily. We examined the
potential of stretch, pressure and accelerometer sensors to gather data from the dancers,
using both Bluetooth and Xbee (radio) shields to send real-time data from the dancers
to a computer (since storage on the Lilypad itself was insufficient). These protocols
proved to be problematic in terms of timing or in terms of reliably tracking more than
6 data-streams at the same time.
Next, we employed a Kinect depth sensor, which uses an infrared laser projector and
a monochrome CMOS sensor to map the environment in 3D. Similarly to the wearables,
the Kinect was only able to recognize up to six bodies simultaneously. Post-processing
did not provide a solution, as there were many instances of occlusion and the field-of-
view of the Kinect was not large enough to capture the entire dance. For movement in
more enclosed spaces, the Kinect might be interesting if the sensor is installed at a high
angle and body-tracking is performed via post-processing.
Lastly, we provided every dancer with wrist- and ankle bands in bright colors with
the intention to use color tracking on the video footage. This proved to be quite effective
for up to four dancers, after which occlusion again became a problem. For our actual
experiment, we therefore focused on proximity tags and hand-analyzed video footage.
2.2 Design
We used a within-participants design, where the subjects danced three times under dif-
ferent conditions. Because all dancers had to participate in the same dance, it was not
possible to counterbalance the conditions. The dance used in this study had been prac-
ticed by the subjects for several weeks at the time of measurement. The subjects re-
hearsed the dance for performances unrelated to this study. The measurements were
collected during an extra practice-session one week before the first performance.
2.3 Measurements
Interoceptive sensitivity Interoceptive sensitivity can be divided into interoceptive
sensibility (self-assessment), interoceptive accuracy (performance on objective tests),
and interoceptive awareness (meta-cognitive - correspondence between accuracy and
confidence) [14]. All of these measures were assessed before dancing started. The sub-
jective measurement was the short form of the Body Perception Questionnaire [25], the
body awareness part only (26 items, 5 point scale). The objective measurement was a
heart-rate detection and a heart rate distinction task. Subjects were asked to count along
with their own heart rate for an unknown period of time, after which their count and their
real heart rate were compared. For the distinction task, subjects watched a flashing red
circle on a screen and had to indicated whether the flashing was synchronous with their
heart rate or not. For both tests, subjects were also asked to indicate their confidence on
a 10-point scale. The actual heart rate was measured using a Grove/Seeedstudio ear-clip
sensor (see figure 2).
Fig. 1. Propriocep-
tion test Fig. 2. Heart rate test
Exteroceptive sensitivity We used a subjective measure of exteroceptive sensitivity
applying a newly developed questionnaire, based on the Body Perception Questionnaire
but focused on awareness of surroundings and other people (5 items, 5-point scale).
Proprioceptive sensitivity To measure proprioceptive sensitivity, a few different ap-
proaches were used. The subjective measurements were based on the Body Perception
Questionnaire and parental report questionnaires when assessing proprioceptive sensi-
tivity in children [7, 23]. We developed two short questionnaires, one based on aware-
ness of bodily position (5 items, 5-point scale), and one on behavior (5 items, 5-point
scale). The two-part objective measurement was developed specifically for this study.
Subjects were seated and blindfolded, and given a pen to place on a paper in front of
them. They were then asked to raise their hand as high as it would go, and place it back
on the paper in one quick movement, as close to the original spot as possible. For the
second part, they were asked to place the pointer finger of their non-dominant hand on
the paper, and place a dot with the pen in their dominant hand as close to the tip of the
finger as possible, again starting with their hand high up (see figure 1).
During the Dance While the subjects were dancing, they were filmed from three angles
with Sony Cyber-Shot DSC-HX5V cameras. Synchronicity scores were extracted from
this footage by hand, by selecting the frames in which individual dancers began and
ended certain movements. The last movement of the dance, a sudden head-movement
to the side (see figure 3, duration of movement was < 500 ms), was transcribed in this
way to establish a preliminary ’synchronicity score’ for the different dances.
In addition, Sociopattern proximity tags [5]1 were applied in order to detect close-range
proximity (1-1.5 meters) of the individuals wearing them. Accelerometer data was also
collected using these sensors, for each proximity contact. This infrastructure has been
deployed in various environments for studying the dynamics of human contacts, e. g.,
1
http://www.sociopatterns.org
Fig. 3. Mid head-turn, last movement of the dance
at conferences [4, 11, 21]. Postprocessing and analysis is then supported by the Ubicon
software platform [3].
Post-dance Questionnaires After each dance, subjects were asked to fill out a self-
assessment manikin (measures of valence, arousal and dominance, 9-point scale) to
indicate their affective state during the dance [9]. Additionally they were asked to rate
the awareness of their own body, the other dancers, and their surroundings during the
dance (3 items, 9-point scale). They were also asked to indicate their closeness to the
other dancers using an inclusion of others in the self scale (IOS, 7-point scale) [1].
Lastly, they were asked to rate the quality of their own dancing and the quality of the
dance as a whole. The expert was also asked after each dance to rate the quality of the
dance as a whole (9-point scale).
2.4 Procedure
After providing informed consent, each subject went through the baseline interoceptive,
proprioceptive and exteroceptive measurements. Then they were given ’secret personal
instructions’ for the first dance, and performed the dance. After the dance, they filled
out the post-dance questionnaires, and the expert gave their rating of dance quality. This
procedure of instructions-dance-questionnaire was then repeated two more times.
The instruction for the first dance was to dance as usual. For the second dance, the
participants were instructed to focus mainly on their own body (with the incentive that
there would be questions about that after the dance), and the third dance on their sur-
roundings and the other dancers. Subjects were not told that everyone received the exact
same instructions. Some post-dance questions were added specific to the instructions to
maintain the motivation to follow them. The expert was not aware of the content of the
instructions.
3 Results
In order to explore the relation between different types of measurements for interocep-
tive, exteroceptive, and proprioceptive sensitivity, as well as the actual performance dur-
ing the dance, we conducted a series of correlation analyses. Performance synchronicity
was operationalized in terms of the interval (in frames) between the start of the head
movement of the first dancer and the start of the head movement of all other dancers.
Higher interval meant a lower performance synchronicity. The head movement ana-
lyzed occurred towards the end of the short dance and was perceptually the most promi-
nent synchronous group action performed. The size of the participant group did not al-
low for a factor analysis. As can be seen in Figure 4, there was a strong relation between
proprioceptive predispositions measured with the questionnaire (Proprioception-Q) and
the baseline performance of the dancers: higher proprioception was negatively linked to
a higher delay, i.e., positively related to synchronicity. There was also a strong relation
between proprioception measured with an actual behavioral task (Proprioception-T) and
delay in synchronicity in the condition where dancers were instructed to focus on oth-
ers. Next to the weak relation between Proprioception-Q and Proprioception-T, these
results suggest that the two types of measurements possibly capture different compo-
nents of proprioceptive sensitivity. Finally, there was a relatively strong negative rela-
tion between interoceptive sensitivity and delay in synchronicity in the condition where
dancers were focusing on their own body. Interestingly, this led to a higher coordination
with other dancers. In fact, the results indicate that interoceptive dancers - those who
are successful in monitoring the internal processes of their own body - may be more
equipped to coordinate with others in general.
Fig. 4. Correlation between dispositional measures and dance performance.
In line with this observation, the expert, unaware of the instructions, was most surprised
by the third dance (’focus on other’), noting that ’the dancers seemed to have more fun,
but the dance was not good’. This impression is confirmed by the overall synchronic-
ity scores which were the lowest in the focus-on-other condition (calculated in terms
of the delay from first dancer movement Mean_Baseline = 3.5 frames, Mean_Focus-
self = 4.9 frames, and Mean_Focus-other = 10.9 frames). This outcome again suggests
that awareness of one’s own body is an important precondition for synchronizing with
others.
4 Conclusion and Discussion
The setup of this pilot study and its first results indicate findings that may be of inter-
est for network modeling of the captured relations. Modeling group behavior as com-
plex networks is an important research direction, e. g., [2, 24] regarding methods from
complex network analysis [29, 33]. Analyzing the individual measures of interoceptive,
exteroceptive and proprioceptive sensitivity and relating that to each participants’ syn-
chronicity performance, we could presumably describe a network of interactions where
some participants are more in sync with each-other than others. Sub-networks may de-
velop, where dancers who react similarly to the different conditions synchronize their
behavior.
In order to analyze group cohesion and synchronicity dynamics in groups of indi-
viduals, those individuals, e. g., dancers, can then be modeled as actors in a (complex)
network. Modeled as a graph, the actors correspond to nodes where the edges (links)
between those are given by connectivity or cohesion metrics. For example, these can
relate to spatial proximity (as measured by the applied proximity tags), gaze (line-of-
sight) or synchronicity relationships between the actors.
The predictive coding account of embodiment states that body ownership is a pro-
cess of error reduction between the predicted bodily state and the sensory feedback from
body and environment [17]. The cerebral body is constructed by multi-sensory integra-
tion and sensory input is weighted according to its perceived importance [31]. In this
context, attention can be re-interpreted as an optimization of precision weighting [28].
Attention is (re)directed towards those sensory elements that minimize prediction er-
rors. Recently, efforts have been made to model these mechanisms on the scale of the
individual [27]. We propose that similar but expanded computational models could be
developed for collective movement due to the flexible self-other boundaries experienced
by the participants [22].
We see two possible approaches to expand further on the current pilot study. The
first is to focus on dyadic interactions, simplifying the network approach and allowing
for more precise automated measurement through the Kinect or other sensors. One ad-
vantage of this approach is that participants can be paired according to their interocep-
tive, exteroceptive or proprioceptive sensitivity, allowing a closer look at these different
styles of approaching embodied social interaction. The second approach would be to
focus on very large groups of people and choose measurements based on proximity or
large overall movement. For example, when a group of people is performing a ’wave’
as seen in sporting events, their synchronicity can likely be measured quite well by a
pressure-sensor in the chair, recording only the moment of rising and the moment of
sitting down again.
Several of the measurements can be improved upon. Most importantly, heart rate
distinction and detection tasks suffer under the drawback that they are susceptible to
false successes if the subject has reasonable knowledge about healthy heart-rates and a
well-developed sense of timing [14]. Additionally, subjects who have a high interocep-
tive sensitivity but feel their heart-rate on a different delay then the sensor used are at a
disadvantage in the detection task. An altered version of the detection task, where the
heart-rate is presented at a range of different delays, could be more precise [26].
In conclusion, our study is the first to explore the contribution of individual dispo-
sitional tendencies to perceive certain internal and external signals towards measuring
and describing synchronous collective motor behavior. This type of behavior has links
to social bonding and affect, embodiment, and self-other boundaries, and as such is a
complex phenomenon of which the dimensions are as yet relatively unknown.
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