IEEE GCCE 2022 1570822914

1	  2	  3	  4	  5	  6	  7	  8	  9	  10	  11	  12	  13	  14	  15	  16	  17	  18	  19	  20	  21	  22	  23	  24	  25	  26	  27	  28	  29	  30	  31	  32	  33	  34	  35	  36	  37	  38	  39	  40	  41	  42	  43	  44	  45	  46	  47	  48	  49	  50	  51	  52	  53	  54	  55	  56	  57	  60	  61	  62	  63	  64	  65	  Difference in skin conductance dynamics to horror
and family bond emotional movies
Tatsuki Makioka, Shogo Okamoto

Ibuki Tara

Department of Computer Science
Tokyo Metropolitan University
Hino, Japan

Department of Mechanical Systems Engineering
Nagoya University
Nagoya, Japan

Abstract—We investigated differences in skin conductance
responses depending on the type of emotions evoked during
the experience of audio-visual contents. We hypothesized thatthe dynamics of the skin conductance response would differ
depending on the type of emotions aroused. We used two types
of audio-visual contents: videos that evoke feelings of familybond and those of fear. The proﬁles of the measured skinconductance response were approximated using two exponentialfunctions and a Gaussian ﬁlter to investigate the differences indynamics in a parametric manner. Viewers’ skin conductance
responses changed in horror scenes and those evoking familybond impressions. The skin conductance responses tended tochange more quickly toward horror movies than those featuring
family bonds. The results suggest that the type of emotions canbe discriminated based on the changes in skin conductance.
Index Terms—Emotion, Skin conductance, Fear, Family bondI. I NTRODUCTION
A growing number of computer systems are attempting
to estimate and leverage users’ emotional states to decide
about their behaviors and provide services. For example, music
players read the emotions and moods of listeners and makeplaylists accordingly [1]. A conversational health-care systemjudges human emotions before advising them [2]. In thesetechnologies, the estimation of human emotions is typically
based on facial pictures, voices, and physiological signals,
such as heart rates.
The skin conductance of human ﬁngers changes upon emotional stimuli due to sweating, and it has been used in many
psycho-physiological studies and engineering studies [3]–[5].
The skin conductance response is less privacy-sensitive thanfacial pictures or voice data. However, thus far, few studies
have investigated the relationship between the type of emotions and dynamics of skin conductance responses whereas
the dynamics of skin conductance responses were studied
between different types of stimulus modalities [6]. The skinconductance could respond differently against different kindsof emotional stimuli considering that their neurophysicologicalprocesses differ [7].
In this study, we investigated the difference in the dynamics
of skin conductance responses by using the two types of
emotionally arousing short videos. One was horriﬁc and theother featured family bonds. It is expected that the skinconductance response changes rapidly in response to aversive/22/$31.00 ©2022 IEEE

stimuli such as fear. In contrast, impressive family-bond scenes
are speculated to require a cognitive process, which may
cause relatively slow changes in physiological responses. We
computed two parameters determining the dynamics of skinconductance responses after approximating the dynamic responses by using a combination of two exponentially decayingfunctions. These parameters were then compared between thetwo types of short videos.
II. M ETHODSThis study was approved by the Institutional Review Boardof Hino Campus, Tokyo Metropolitan University (#H21-046).
A. Emotionally Arousing Movies
Two horror movies were used for the experiment. In thesemovies, monsters suddenly appeared to horrify the viewers.
Each video was approximately 2 min in length.
Further, we used two movies dealing with family love.
In both videos, a child is reunited with his/her parent aftera long time of separation. The length of each video wasapproximately 3 min.
These movies were played on a 21-inch display that wasplaced 60 cm away from the participant’s head. The sounds
were played through headphones.
B. Skin Conductance Response
The skin conductance response is a physiological index
related to arousal. Sweating associated with tension or excitement changes the electrical properties of the skin, and itchanges merely 1–2 s after the stimulus presentation [8].
A skin electrical activity measurement unit (AP-U030mII, Nihon Suntech, Japan) and ampliﬁer (MaPI720CA, NihonSuntech, Japan) were used to measure skin conductance. Eachof the two electrodes was attached to the ﬁrst and second
ﬁngers of participants. These devices were connected to a DAQ
device (NI USB-6211, National Instrument Corp., TX) andcontrolled by the Data Acquisition Toolbox of Matlab (Matlab2021a, Mathworks, MA).
C. Participants
Fourteen university students in their 20s that were unawareof the purpose of the study participated in the experiment. All
participated in the experiment after providing written informedconsent.

1453

Fig. 1. Functional modeling of skin conductance responses. Temporal
evolution of skin conductance (black curve) is approximated as the sum oftwo exponential functions (red and blue curves).
Fig. 2. Means and standard errors of λ1 and λ2 by fear and family-bondscenes. Left: λ1 . Right: λ2 .

D. Experimental task
Participants were asked to rest for 90 s to ensure that they
were in a stable mental condition before experiencing eachaudio-visual content. They held a load cell while watching
videos to report the subject magnitude of fear or family bondthey felt by a grip force. These time-series grip forces wereused to make sure that the changes in the skin conductancewere caused by emotional experiences.
E. Analysis of Skin Conductance Responses
As shown in Fig. 1, the proﬁle of the skin conductance
response can be functionally approximated using two exponential functions and a Gaussian ﬁlter N (t) [9] byx(t) = A(exp(λ1 t) − exp(λ2 t))(1)−(t − τ )2
1exp()2σ 2
2πσ(2)

N (t) = √h(t) = x(t) ⊗ N (t)(3)where h(t) is the approximated curve and A, λ1,2 , and σ are
the parameters to determine the dynamics. The λ1,2 values
are negative. The temporal changes of the skin conductance
responses at the fear or impressive scenes were clipped andanalyzed by using these formulae. The least-squares solutions
were computed by using the fmincon function of Matlab. A
few samples were excluded for the later analysis because of
their low goodness of ﬁt values.
We focused on λ1 and λ2 because they largely determine
the waveform dynamics. We performed two-sample t-tests tocompare the estimated λ1 and λ2 values between the horror
and family-bond videos. For this comparison, we assumed thatthe variances were not equal for λ1 and λ2 .
III. R ESULTS
Fig. 2 shows the mean and standard error for λ1 andλ2 for each type of video. λ1 values barely exhibited adifference (t(15) = 2.25, p = 0.040), and those for the horror
videos were smaller than those for the family-bond videos.
In contrast, λ2 values exhibited no difference among the twotypes of videos (t(18) = 1.85, p = 0.080).

The small λ1 values for the horror movies indicate that theskin conductance responses caused by fear are more rapidly
attenuated than those caused by a family-bond scene. Although
the difference in λ2 was not signiﬁcant between the two typesof movies, the rise in skin conductance tended to be quicker
for horror scenes than for family-bond scenes. These suggestthat the skin conductance response changes more slowly whenfeeling family bonds than when feeling fear.
IV. C ONCLUSION
We investigated the differences in the dynamics of skinconductance responses when watching two types of videos
that aroused fear or feelings of family bond. Thus far, suchdifferences dependent on the type of emotions have yet tobe reported. The two emotions were parametrically comparedafter approximating the skin conductance responses by using
a linear combination of two exponential functions. For thefear emotion, it was suggested that the skin conductance
response was more quickly attenuated than for the familybond emotion. These results showed a tendency for skinconductance response to differ by emotion. This property
allows comuter interfaces to estimate human emotions basedon the parameters determining the dynamic skin conductance
responses. A study on a variety of emotion types remains
studied in the future whereas only fear and excitement weretreated in this study.
R EFERENCES[1] S. Sana, G. Sruthi, D. Suresh, G. Rajesh, and G. Subba Reddy,“Facial emotion recognition based music system using convolutional neural networks,” Materials Today: Proceedings, 2022,
10.1016/j.matpr.2022.03.131.
[2] M. Czerwinski, J. Hernandez, and D. McDuff, “Building an AI that feels:
AI systems with emotional intelligence could learn faster and be more
helpful,” IEEE Spectrum, vol. 58, pp. 32–38, 2021.
[3] I. Tara, S. Okamoto, Y. Akiyama, and Y.Yamada, “How important is
the timing of vibrotactile stimuli for the excitement feeling of audiovisual contents,” in Proceedings of IEEE Global Conference on Consumer
Electronics, 2021, pp. 183–185.
[4] ——, “Heightening fear response to horror video scenes by applying
vibratory stimuli to upper bodies of viewers,” in Proceedings of IEEE
Global Conference on Life Sciences and Technologies, 2022, pp. 254–256.
[5] T. Makioka, S. Okamoto, and I. Tara, “Fear magniﬁed by vibratory stimuli
to the upper-body at predictive horror scenes,” in Proceedings of IEEE
Global Conference on Consumer Electronics, 2022.

2454

[6] I. Tara, S. Okamoto, Y. Akiyama, and Y. Yamada, “Temporal characteristics of skin conductance and subjective intensity in response to unpleasantaudio-visual and vibrotactile stimuli,” in IEEE International Conferenceon Intelligence and Safety for Robotics, 2021, pp. 24–27.
[7] J. Posner, J. A. Russell, A. Gerber, D. Gorman, T. Colibazzi, S. Yu,Z. Wang, A. Kangarlu, H. Zhu, and B. S. Peterson, “The neurophysiological bases of emotion: An fmri study of the affective circumplex
using emotion-denoting words,” Human Brain Mapping, vol. 30, no. 3,
pp. 883–895, 2009.
[8] A. D. Craig, “How do you feel? Interoception: the sense of the physiological condition of the body,” Nature Reviews Neuroscience, vol. 3,
no. 8, pp. 655–666, 2002.
[9] D. R. Bach, G. Flandin, K. J. Friston, and R. J. Dolan, “Modelling
event-related skin conductance responses,” International Journal ofPsychophysiology, vol. 75, no. 3, pp. 349–356, 2010.

3455