Audio-visual stimuli change not only robot’s hug
impressions but also its stress-buffering effects
Masahiro Shiomi1 · Norihiro Hagita1
Received: date / Accepted: date

Abstract: This paper describes how audio and visual
stimuli during a robot’s hug change its perceived
impressions and stress-buffering effects. In human science
literature, the perceived gender influences the impressionsof touch interactions, including hugs. In this study weinvestigate whether the perceived gender of an interacting
agent controlled by audio-visual stimuli affects theinfluence of positive hugs like a stress-buffering effect.
We used a system called Metahug that integrates a robot
and a virtual reality application and prepared both femaleand male-appearance agents and experimentallyinvestigated the audio-visual effects for human-robot huginteraction. Our results showed that the robot’s hug
impressions were significantly different based on theagents’ genders. Moreover, the participants reported
significantly lower tension in a stressful task when theyhugged an opposite-gender-appearance agent compared toa same-gender-appearance agent. Our results suggest that
the Metahug system can change both the impressions of arobot’s hug and stress-buffering effects of the hug byaltering the audio and visual stimuli of the virtual reality
application.
Keywords: hug interaction,interaction, virtual reality

human-robot

touch

1 Introduction

Touch interaction is a growing research topic in thehuman-robot interaction research field. Due totechnological advances, social robots are interacting with
us by shaking hands and giving hugs at museums [2, 3],elementary schools [4, 5], and shopping malls [6, 7].
This paper is an extended version of a previous work of
Shiomi et al. [1] and contains additional references,
experiment and discussions.
1Intelligent Robotics and Communication Labs., ATR,
2-2-2 Hikaridai Keihanna-Sci. City, Kyoto, Japan
E-mail: m-shiomi@atr.jp

Robotics researchers consider a robot’s touch a key factor
not only for friendly interaction but also for providing
positive effects to the people who are being touched,because past studies in human-human interaction showedvarious merits from touch interaction [8-13]. Past studies
investigated the merits of human-robot touch interaction
from the following viewpoints: mental health support [14],motivation management [15], stress-buffering effect [16],and promoting prosocial behavior [17].
However, these previous works only used machine- or petlike-appearance robots in their touch interactions andfocused less on the perceived gender of the robots and their
touches. Based on human science literature, genderchanges the impressions of touches between people[18][19]. However, it remains unknown how a robot’s
perceived gender changes the impressions of its hugs.
Note that the investigation of gender effects with robots intouch interaction suffers from several difficulties,
including hardware configuration for specific appearancesand expense.
To investigate the merits of the perceived genders ofrobots by avoiding such difficulties, we integrated a virtual
reality (VR) application and a huggable robot to easilychange its appearances and its voice to control its
perceived gender using audio-visual stimuli (Fig. 1). In
this study, we used the MetaHug [1] system to address thefollowing research questions:Fig. 1 MetaHug system

2- Can the changes of the audio-visual stimuli in a VR
application alter the robot’s perceived gender?
- How does the perceived gender change the humanparticipant’s feelings about the robot’s hug?
In this study we also investigate the stress-buffering
effects of a robot’s hug. Human science literature has
already identified stress-buffering effects through actual
touch interaction (including hugs) both with close people[9] and imagined touch interaction from such people [10].
Another study showed a stress-buffering effect thoughhuman-robot touch interaction [16], but it failed to focus
on the perceived gender effect. If the robot’s perceived
gender influences the stress-buffering effects, suchknowledge would contribute to touch interaction between
people and robots and the design of mental support robot
systems. Thus, we address the following researchquestion:- How does the perceived gender of a robot change thestress-buffering effects of its hugs?
2 Related Work
2.1 Touch interaction between people
Several researchers have investigated how intimate touch
interaction with friends of family, such as affective
touches and hugging, provide positive effects to the people
who are being touched. For instance, researchers who
focused on hug effects for physical health reported thatblood pressure and heart rates are reduced by hug
interactions [8]. Another research described the effects on
immunity and reported that touch interaction with close
people decreases the risk of infections from viruses [9].
Goldstein et al. investigated the relationships betweensocial touch analgesia and brain-to-brain coupling byobserving hand-holding situations [20]. From anotherperspective, researchers argued that imagined touch
supports might increase stress-buffering effects more thanimagined voice supports [10].

To investigate the effects of touch interaction between
people, the gender effect is one essential factor about
responses to being touched. For example, female
participants respond more positively to being touched bymale participants [18]. Another researcher compared thetouch effects between the same gender and the opposite
gender and reported that being touched by the latterprovides merits in specific situations [21]. Evans et al.
reported the negative effects of same-gender touch innursing situations, such as between male patients and malenurses [19].
These studies showed both the positive and negative
effects of touch interaction as well as how genderinfluences them and the feelings of being touched. These

Shiomi et al.

results suggest that the perceived gender of robots also
influences the touch interaction.
2.2 Touch interaction between people and robots
Robotics researchers have also shown that touch
interaction with robots effectively provides positiveeffects to the interacting people, similar to human-humantouch interaction [14-16, 22-28]. One popular touchable
robot is Paro whose seal-like appearance supports elderly
people from a mental health perspective [14]. Sumioka et
al. reported that using a huggable device during telecommunication can decrease stress [16]. These studies
focused on passive touches, i.e., from people to robots, but
recently others have focused on the effects of active
touches, i.e., from robots to people. For example, a robot’s
active touch increases human motivation and provides
better impressions than a passive touch [15, 22]. Other
studies focused on hug interactions between robots andpeople and reported that active hugs encourage prosocial
behaviors (larger charitable donations) in people and selfdisclosures and raised interest to interact with the robot
again [25][26].

In the research field of human-robot interaction, theperceived gender effects have been broadly investigatedusing multiple kinds of real robots [29][30][31]. For
example, Powers et al. reported that the gender of a robot’s
voice’s influences its perceived knowledge [29]. Ghazali
et al. focused on a robot’s facial characteristics and gendereffects in persuasive interaction and concluded that an
opposite gender robot created higher psychologicalreactance to participants than a same gender robot. [30].
Siegel et al. also investigated the gender effects ofpersuasive effects in human-robot interaction and argued
that people more highly evaluated a robot of the opposite
gender [31].
In a touch interaction context, due to the difficulties ofpreparing various kinds of robots with different
appearances, several researchers employed virtual agentsto change/control the perceived gender of an interacting
target. For instance, Suzuki et al. integrated a femaleappearance agent and a mechanical hand device toinvestigate the effects of motivation improvement [32].
Bailenson et al. investigated gender effects using a VR
application and reported that touch forces were changed
by gender combinations [33]. Another study investigatedthe effects of a virtual agent’s gender and its body size on
virtual hug interactions and argued that the combinationsof genders between participants and agents influenced theinteraction time [34].
These studies highlighted the merits of touch interaction
between robots and people and described the perceived
gender effects of interacting agents. On the other hand, thestress-buffering effect of hugging a robot remains
unknown, and the perceived gender effects in hug

Audio-visual stimuli change not only robot’s hug impressions but also its stress buffering effects

interactions have also not been investigated yet. If arobot’s hug has similar stress-buffering effects that arechanged by its perceived gender, such knowledge will
benefit robot applications with haptic interaction.
3 SystemFigure 2 shows the components of our MetaHug system.
Its motion controller function manages both the VR
application part (i.e., motions and voices of virtual agents)
and the robot part (i.e., robot motions).

3

Virtual reality application part
Head position

Virtual agent

Position tracker(Oculus sensor)

HMD(Oculus rift)

Touch sensor(ShokacCube)

Motioncontroller

Pressure

Robot(Moffuly)
Hug

Robot partFig. 2 System overview
3.1 VR application partIn this study, we used Unity and Oculus Rift to control theaudio-visual stimuli for the participants through a VR
application. We also used two Oculus sensors to detect the
Oculus Rift’s position, i.e., the users’ head positions.

We prepared female- and male-appearance virtual agentsusing commercial 3D models and speech synthesis
software. We adjusted their heights to be identical to avoid
size effects. These agents autonomously made eye-contact
with the users using head position information andcontrolled their lip behavior for synchronization with the
speech contents. We also prepared a hug animation forboth agents.
3.2 Robot part
We used Moffuly [17] that can hug people. This robot has
a 1 DOF for each elbow and sufficient arm length for huginteractions. For a safe hug, we installed a touch sensor(ShokacCube, developed by Touchence) in the tip of its
arms to detect contact with people; if the sensor detects aparticular amount of pressure, the hug motion stops andMoffuly will slightly open its arm.
3.3 Motion controller function
With the sensor information from the VR application partand the robot part, i.e., head position and pressure
information, the motions and the voices of the virtual
agents are controlled as well as the robot’s motions forsynchronized hugs. The motion controller decides thetiming at which to start their hug motions based on theuser’s head position. During a hug interaction, the robot
patted the users on the back. Since we prepared a oneminute hug for the virtual agents and the robot, their hug
motions finish simultaneously. About the hug time, eventhough past human science literatures reported that

intimate hugs provided several positive effects, they did
not describe the length of the hugs; we prepared rather
long hugging behavior (i.e., one-minutes) to express
intimate impressions.

4 Experiment
4.1 Hypotheses and predictions
4.1.1 Hypotheses about hug impressions and gender

As described in Section 2, the perceived gender influences
touch interactions between people [18]. For example, paststudies reported that a touch from a person of the opposite
gender was welcomed, and a touch from a person of thesame gender caused complex situations in the context ofacceptance and rejections [18] [19]. Therefore, if the
MetaHug system appropriately controls the perceived
gender of virtual agents, people will have more positive
impressions to hug experiences when they interact with an
opposite-gender agent than with a same-gender agent.
Based on these considerations, we made the following
hypothesis about hug impressions:
Prediction 1: Participants will feel more comfortablehugging and a greater willingness to hug again with an
opposite-gender agent than with a same-gender agent.
4.1.2 Hypotheses about stress-buffering effectAs described in Section 2, past studies showed that huginteraction provides stress-buffering effects, regardlesswhether the interaction partner is an actual close person[8][9], an imagined close person [10], or a robot [16].
However, these studies did not address the perceived
gender effects, which we believe influences the stressbuffering effects through hug interaction, similar to othertouch interactions [18][19]. Following these considerations,
we made a hypothesis about the stress-buffering effect:
Prediction 2: Hug interactions with an opposite-gender
agent will decrease the stress of participants more than a
hug with a same-gender agent.
4.2 Participants
Eighteen Japanese people participated in our experiment:
nine women and nine men who self-reported their genders.
Their average age was 36.25 and the standard deviation
was S.D 8.74.

4

4.3 Environment
The experiment was conducted in our laboratoryenvironment where the MetaHug system is installed. We
recorded both video and audio information.
4.4 Conditions
This study has a mixed factorial design, i.e., we combined
within- and between-participant designs. The number ofwithin-participant conditions was two (same-gender andopposite-gender), and their order was counterbalanced.
The between-participant factor was the participant’s gender.

Same-gender condition: participants interacted with thesame-gender agent.
Opposite-gender condition: participants interacted withthe opposite-gender agent.
4.5 Procedure
First, we briefly described the experiment’s purposes andits procedures. After they gave signed consent, we
explained our system and how to give a hug with it by
wearing an HMD. In both conditions, the agents first

request a hug verbally, hug the participants so that they
could experience a hug, and thank the participant's
participation to this experiment. After the hug interaction
ended, the participants did a subtraction task as a stressor,
which is commonly used in human science literatures toreliably produce stress [35, 36]. We prepared threesubtraction tasks (2091 to 0 in 17-step sequences, 2337 to
0 in 19-step sequences, or 3567 to 0 in 29-step sequences)and counterbalanced their order. Each task length was fiveminutes. The experimenter told them to calculate as
quickly as possible and warned them that if they mademistakes, they would have to begin again.
4.6 Measurements
To investigate the hug interaction feelings, we prepared
two questionnaire items: 1) willingness to get another hug
and 2) the comfort of the hug experience on a 1-to-7 point
scale, where 7 is the most positive.

To investigate the stress experienced by the participants
during the task, we followed a past procedure [10], whereparticipants self-reported their perceived stress during thetasks. We followed this approach because a past study
reported that this method more accurately measures
perceived stress during tasks than post-task measurements.
Self-reported perceived stress also showed a temporalcorrelation between physiological and psychological stressmeasurements [37]. The participants reported their stressratings (0-to-10 scale, where 0 is no stress and 10 isextremely stressed) at 30-second intervals (prompted by atone) during each five-minute task. We gathered ten stressratings for each condition. The Cronbach α value was 0.97.

Shiomi et al.

5 Results
5.1 Verification of prediction 1
Figure 3 shows the average and the S.E. of the comfort
impressions. We conducted a two-way mixed ANOVA
with two factors: participant-gender (between-participant)and agent-gender (within-participant factor). The results
showed significant differences in the agent-gender factor(F(1, 14)=12.962, p=.002, η2 = 0.448) and in theinteraction effect (F(1, 14)=12.962, p=.002, η2 = 0.448).
The results did not show any significant differences in theparticipant-gender factor (F(1, 14)=0.899, p=.357, η2 =0.053). We conducted a multiple comparison with the
Bonferroni method, which showed a significant difference
for the same-gender agent: female participants > maleparticipants, p=.043). For the opposite-gender agent, wefound no significant difference between the female andmale participants (p=.594). The results also showed asignificant difference for male participants: oppositegender agents > same-gender agents ( p<.001). For female
participants, we found no significant difference between
opposite- and same-gender agents (p=1.00).

Figure 4 shows the average and the S.E. for the willingness
to get another hug. We conducted a two-way mixed
ANOVA with two factors: participant-gender (betweenparticipant) and agent-gender (within-participant factor).
The results showed significant differences in the agentgender factor (F(1, 14)=5.982, p=.026, η2 = 0.272) and in
the interaction effect (F(1, 14)=7.965, p=.012, η2 = 0.332)
but not in the participant-gender factor (F(1, 14)=0.429,
p=.522, η2 = 0.026). We conducted a multiple comparison
with the Bonferroni method, which did not show any
significant difference for either the opposite-gender agent(p=.466) or the same-gender agent (p=.111). On the other
hand, the results showed a significant difference for maleparticipants: opposite-gender agents > same-gender agents,
p=.002). But for female participants, we found no
significant difference (p=0.794).
* : p <.05.

7

6

*

*

5

4
3
2

1
Same-gender

Opposite-gender

Male participants

Female participants

Fig. 3 Questionnaire results about comfortableness of hug
interaction

Audio-visual stimuli change not only robot’s hug impressions but also its stress buffering effects* : p <.05.

7
*

6
5

4
3

2
1

Same-gender

Opposite-gender

Male participants

Female participants

Fig. 4 Questionnaire results about willingness for another
hug
*

10

* : p <.05.

8
6
4
2
0

Same-gender

Opposite-gender

Male participants

Female participants

Fig. 5 Questionnaire results about perceived stress during
tasks (0 means no stress)
20

15
10

5
0

Same-gender

Opposite-gender

Male participants

Female participants

Fig. 6 Task performance
These experimental results partially supported prediction
1. Only male participants showed significantly morepositive impressions about comfort and willingness foranother hug when they interacted with the opposite-gender
agent than with the same-gender agent.
5.2 Verification of prediction 2
Figure 5 shows the average and the S.E. for perceived
stress. We conducted a two-way mixed ANOVA with two
factors: participant-gender (between-participant) and5

agent-gender (within-participant factor). The results
showed significant differences in the agent-gender factor(F(1, 16)=4.768, p=.044, η2 = .230). We did not find any
significant differences in the gender factor (F(1,16)=0.459, p=.508, η2 = .028) or in the interaction effect(F(1, 16)=2.700, p=.120, η2 = .120). These results indicatethat for both female and male participants, a hug
interaction with an opposite-gender agent relieved theirstress more than with a same-gender agent. Thus,
prediction 2 was supported.

6 DISCUSSION
6.1 Implications
Our results show that hug interactions with oppositegender agents offer stress-buffering effects for both female
and male participants. On the other hand, the agent-genderfactor significantly changed the hug impressions only formale participants. These results seem complex because apart of our hypotheses was not supported. But basically,
hug interactions with an opposite-gender agent provide
greater benefits than with a same-gender agent.

Another critical implication is that the experimental results
showed similar trends between human-human and humanrobot touch interactions. Past studies showed that females
react more positively to touch interaction than males [18],and male-male touch has a negative effect [19]. These
results showed promising effects for hug interaction with arobot using a VR application to manipulate the perceived
gender of the interacting agents, because this approachprovides opportunities to more easily change theappearances and the voices of agents than actual robots.
6.2 Hug effects toward task performances
In this study, we only investigated the stress-buffering
effects and the impressions of hug interactions bycontrolling the perceived gender of the interacting agents.
To deepen our understanding about the effects of hugs, weinvestigated how perceived gender during hug interactions
changed the participants’ task performances.

We measured their performance scores, i.e., the number ofcorrectly completed serial subtractions (Fig. 6). We
conducted a two-way mixed ANOVA with two factors:
participant-gender (between-participant) and agent-gender(within-participant factor). The results did not show any
significant differences for any of the factors: the agentgender factor (F(1, 16)=0.01, p=.980, η2 = .001), theparticipant-gender factor (F(1, 16)=1.304, p=.270, η2= .075), or the interaction effect (F(1, 16)=0.337, p=.569,
η2 = .021). Thus, the perceived gender did not
significantly affect the task performances.

6

6.3 Hug interaction effect compared to no-hug
We investigated whether the perceived gender changed thestress-buffering effect. But we did not compare a hug’s
power in the stress-buffering effect with a no-hug
interaction, because a previous study showed that a hug
interaction provided more stress-buffering effects than ano-hug interaction [16]. However, an additional
investigation about a hug’s stress-buffering effect with an
opposite-gender agent might provide evidence thatstrengthens the positive effects of a robot’s hug andcontribute to knowledge for the human-robot interaction
research field.

We conducted another experiment with 18 participants(nine women and nine men who self-reported theirgenders) whose procedure was basically the same as thefirst experiment except for the hug interaction. Instead ofa one-minute-hug interaction with virtual agents, theparticipants imagined a digital video camera and its
functions for one minute. We defined the additional
participant condition as no-hug. We also measured theperceived stress during the task by questionnaire. We only
compared these results to the opposite-gender condition
and integrated the participants’ genders because ourresults showed that this condition outperforms the samegender condition regardless of the participants’ genders
from the stress-buffering viewpoint.
We conducted a t-test for the perceived stress during tasks
between the opposite-gender and no-hug conditions (Fig.
7), and the results showed a significant difference(t(34)=2.228, p=.033, r=0.36). Thus, hug interactions with
an opposite-gender agent have a more significant stressbuffering effect than the no-hug interaction. We also
conducted a t-test for the task performance between the
opposite-gender and no-hug conditions (Fig. 8), and theresults did not show a significant effect (t(34)=1.422,
p=.164, r=0.24). Note that the comparison between a hug
interaction with a same-gender agent and no-hug
conditions did not show significant differences for either
the perceived stresses or the task performances. Even if
these results are investigated with an additional
experiment, the results might suggest the benefit of hug
interactions with an opposite-gender agent from a stressbuffering viewpoint.
6.4 Sexual orientation and preferrence
Our experiment results identified the positive effects of
hug interaction with an opposite-gender agent, but theseresults must be examined from subjective sexual
orientation viewpoints. All of the participants in our study
self-identified as heterosexual, which undoubtedly
influenced their impressions.

Moreover, we used virtual agents with an animationappearance and a doll-like robot. Possible future works
include investigating the effects of a more realistic (moreShiomi et al.

human-like) appearance virtual agent, the existing
character’s appearance virtual agents (more characterlike), and/or robots that provide different touch feelings
during hug interactions. Using such different agents or
robots will provide additional knowledge about humanrobot touch interaction.
6.5 Limitation and future work
This study has several limitations. We used a one-minutehug as a stimulus, but that length was decided heuristicallyto represent an intimate hug behavior. It would beinteresting to investigate the effects of hug length as wellas the minimum times to decrease stress by a hug.
Moreover, we experimented in a laboratory; an interesting
future work would be to install our system in realenvironments. For this purpose, a natural context for huginteractions and an appropriate conversational design must
be prepared, which was not covered in this study.

To investigate the stress of participants, some related
works used such objective measurements as electrodermal
activity to investigate stress [38, 39]. In this study we only
measured perceived stress by questionnaires to evaluate
the stress-buffering effects of hug interaction. However,using such objective measurements would provide
additional evidence about the stress-buffering effects of
hug interactions.
10* : p <.05.

*

8
6
4
2

0
Opposite-gender

No-hugFig. 7 Questionnaire results about perceived stress during
tasks with/without hug interaction (0 means no stress)
20

15
10
5
0

Opposite-gender

No-hugFig. 8 Task performance between with/without huginteraction

Audio-visual stimuli change not only robot’s hug impressions but also its stress buffering effects

7 Conclusion

We investigated how the perceived gender of virtual
agents changes the impressions and the stress-buffering
effects of hug interaction. We experimented with the
MetaHug system, which provides physical hug
interactions to people with virtual agents using an actual
huggable robot and a VR application. Participants
experienced two hug interactions with different virtual
agents, experienced stressful tasks, and reported theirperceived stress and hug impressions. Our experimental
results showed that a hug interaction with an oppositegender agent provided stress-buffering effects regardlessof the participants’ gender. However, hug impressions
only improved in male participants.
Acknowledgements: This work was supported by JST
CREST Grant Number JPMJCR18A1, Japan.
Conflict of Interest: The authors declare that they have noconflict of interest.
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Masahiro Shiomi received M. Eng. and Ph.D. degrees inengineering from Osaka University in 2004 and 2007. From2004 to 2007, he was an intern researcher at the Intelligent
Robotics and Communication Laboratories (IRC). He iscurrently a group leader in the Agent Interaction Design
department at IRC, Advanced Telecommunications ResearchInstitute International (ATR). His research interests include
human-robot interaction, social touch interaction, robotics forchildcare, and multiple social robots.

Norihiro Hagita received B.S., M.S., and Ph.D. degrees inelectrical engineering from Keio University, Japan in 1976,
1978, and 1986. From 1978 to 2001, he was with the Nippon
Telegraph and Telephone Corporation (NTT). He joined theAdvanced
Telecommunications
Research
InstituteAudio-visual stimuli change not only robot’s hug impressions but also its stress buffering effects

International (ATR) in 2001 and established the ATR MediaInformation Science Laboratories and the ATR Intelligent
Robotics and Communication Laboratories in 2002. His
current research interests include communication robots,
networked robot systems, interaction media, and patternrecognition. He is a fellow of the Institute of Electronics,
Information, and Communication Engineers, Japan as well asa member of the Robotics Society of Japan, the Information
Processing Society of Japan, and The Japanese Society for
Artificial Intelligence. He is also a co-chair for the IEEE
Technical Committee on Networked Robots.

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