ISASE 2022

Effects of surface textures and shapes on perceived softnessof hard materials
Qingyu SUN *, Junliang GUO **, Shogo OKAMOTO *** Graduate School of Engineering, Nagoya University, Furo-Cho, Chikusa-ku, Nagoya-shi, Aichi 464-8603, Japan
sun.qingyu@c.mbox.nagoya-u.ac.jp** Tokyo Metropolitan University, 6-6 Asahigaoka, Hino-shi, Tokyo 191-0065, Japanokamotos@tmu.ac.jp

Abstract: This study investigated the influence of multiple surface features on the perceived surface softness during rubbing motion.
Participants rubbed and ranked 13 types of 3D-printed rigid specimens with different macroscopic shapes and microscopic grains. A
regression analysis revealed that the amplitude of the surface sinusoidal shape and the diameter of microscopic grains positively andnegatively affected the signal-to-noise ratio calculated by the softness ranks, respectively. Smooth surfaces featuring a sinusoidal
macroscopic shape with an amplitude of 0.5 mm felt softer than flat, smooth surfaces. By contrast, surfaces featuring grains with adiameter of 1 mm felt harder than the flat, smooth surfaces. These findings can help design soft-feeling product surfaces.
Keywords: Softness, Texture, Microscopic grains, Surface shapeperception, because such influences were notquantitatively reported in [1] or [2]. We created 3Dprinted hard specimens with macroscopic heightvariations and micrograins. The participants rubbed thesesurfaces to rank them in terms of their perceived softness.
The influential factors were statistically analyzed anddiscussed.

1. INTRODUCTION
The softness perceived from surfaces is deeply related
to the luxury experienced while touching and usingproducts. Interestingly, perceived softness is not theinverse of physical hardness. Surface patterns and friction
mediate perceived softness. For example, plastic surfaces
with grains can feel softer than flat surfaces. In one study[1], [2], the effective radii of the grains were reported tobe approximately 30 μm or 1 mm. Inoue et al. [3]demonstrated that finger-sized concave and convex
shapes cause the surfaces to feel softer and harder,
respectively, when pushed by fingertips. Furthermore, areduction in the surface friction causes surfaces to feel
softer when they are rubbed with fingers [4]. Hence, by
manipulating the macroscopic and microscopic features ofthe surfaces, perceived softness can be altered even when
the surfaces are made of hard materials that cannot bedeformed by human fingers.
Thus far, the effects of macroscopic surface shapes on
the perceived softness have not been investigated for therubbing motion, although their effects on pushing motion
have been reported [3]. The objective of this study is toinvestigate whether sinusoidal surface height patterns
with large wavelengths contribute to the softness
experienced while rubbing surfaces. Additionally, weinvestigated the influence of microscopic grains, having
radii and heights of hundreds of micrometers, on softness

2. METHOD
2.1 Stimuli: 3D-printed surface textures
We created 13 3D-printed specimens. The 3D printerused was Form 3 (Formlabs, MA), with a nominal

Figure 1: Physical size of specimens and the threeparameters

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Table 1: Stimuli parameter values
H (mm)d (mm)

h (mm)

Stimulus

000A00.50

0.50

B00.750.25

C01.00

0.75

D0.5

00E

0.5

0.50

0.25

F

0.5

0.75

0.50

G

0.5

0.75

0.75

H0.5

1.00

0.50

I0.75

00J

0.75

0.50

0.75

K

0.75

0.75

0.50

L0.75

1.00

0.25

M

Table 2: Experimental result. Mean softness ranks andtheir SN ratio.

ASN ratio
(dB)
15.23

Meansoftness rank
4.9
7.4

Stimulus

resolution of 25 μm and the Young’s ratio of the plastic
was 2.8 GPa. The physical dimensions of the specimens
were 100 30 5 mm, as shown in Fig. 1. There are twomain surface features: macroscopic and microscopic. The
macroscopic feature was a sinusoidal wave with awavelength of 50 mm, and its amplitude (H) was a freeparameter ranging from 0 to 0.75 mm. The microscopic
spherical or hemispherical grains had diameter (d) ranging
from 0 to 1 mm and height (h) ranging from 0.25–0.75mm, as listed in Table 1.
These parameters were determined using an orthogonaltable to decrease the number and redundancy of thespecimens. In the orthogonal table, multiple parameters
are altered among the specimens. However, a similar
primary effect can be achieved using exhaustive
specimens, without considering the interaction between
the factors. The levels of parameters H, d, and h were 3, 4,and 4, respectively.

B

18.17

C

17.51

6.9

D

22.28

13.0

E

4.39

1.5

F

14.43

5.0

G

18.74

8.5

H

19.77

9.6

I

18.55

8.1

J

3.98

1.5

K

16.10

6.3

L

19.89

9.5

M

18.55

8.1

We used the signal-to-noise (SN) ratio employed in theTaguchi method to assess the softness of the specimens.
The participants ranked the softness of the specimens, i.e.,
where smaller ranks were softer. Smaller-the-betterfeatures were then used for the obtaining of the SN ratio
for specimen j:
𝑆𝑁10 log∑ 𝑦1𝑛where yji indicates the softness ranks assigned by eachparticipant, and n is the number of participants, i.e., 8. i is
the index of participants ( 𝑖 1, … ,8 ). The SN ratio
considers both the mean rank and its variability among
participants. When the mean rank and its variability weresmall, the SN ratio was high.
We then conducted a multiple regression analysis withthree physical parameters, H, h, and d as explanatory
variables and the SN ratio of the specimens as objectivevariable.

2.2 Tasks
The participants rubbed the randomly arranged
specimens using their index finger to explore the softness.
They wore a pair of glasses with translucent tapes suchthat they could not see the detailed shapes of thespecimens. They then ranked the specimens according totheir perceived softness. A higher rank referred to a harderspecimen. Tied ranks were allowed.

3. RESULTS
Table 2 lists the average softness ranks and SN ratios for
all the specimens. The softest specimens were stimuli E(𝐻 0.5 mm, 𝑑 0, ℎ 0) and J (𝐻 0.75 mm, 𝑑0, ℎ 0), while the least soft specimen was D (𝐻 0,𝑑 1 mm, ℎ 0.75 mm).

2.3 Participants
Eight university students in their twenties participatedin this experiment after providing their written informed
consents. The objectives of the study were not explained
to the participants prior to the experiments.

Table 3: Coefficients of three parameters for linear
regression analysis

2.4 Analysis

2Parameter

Coefficient

H (Amplitude of macro-shape)

5.28

0.060d (Diameter of micrograins)

9.18

0.010

h (Height of micrograins)

6.48

0.118

p-valuevariation of specimens and the number of participants.
This potentially caused weak statistical significance forsome parameters. Therefore, we intend to expand thisresearch in the future. Optimization of the sinusoidal
amplitude H and microscopic grain diameter d can also be
considered to maximize the perception of softness.

The results indicate that surfaces with a low-frequency
sinusoidal wave may present a softer texture than flat
surfaces with micrograins. We also conducted a Wilcoxon
signed-rank test to compare stimuli A (𝐻 0, 𝑑 0, ℎ0), i.e., a flat and smooth surface and J (𝐻 0.75 mm,𝑑 0 , ℎ 0 ), for which the SN ratio was the largest
among all surfaces. We found a significant difference
between A and J (𝑝 0.0078), indicating that stimulus J
was judged to be softer than stimulus A. Furthermore, theflat and smooth surface (Stimulus A) and the flat surface
with relatively large micrograins (Stimulus D) were alsosignificantly different ( 𝑝 0.0078 ) in terms of theirranks. Stimulus D was judged to be harder than stimulus
A.
Table 3 shows the regression coefficients of the linear
regression analysis, where H, d, and h are explanatory
variables. The amplitude of low-frequency sinusoidal
waves (H) exhibited a positive trend ( 𝑝 0.060 ),whereas the diameter (d) of microscopic grains exhibiteda significantly negative effect on the perceived softness.
The three parameters explained the SN ratio of softness
with the correlation coefficient and adjusted 𝑅 values
being 0.92 and 0.78, respectively.

5. Conclusion
In this study, we examined the influence of sinusoidal
waves with large wavelengths and microscopic grains on
the perceived softness of hard materials during therubbing motion. The participants explored and ranked 13
types of 3D-printed specimens having macroscopic andmicroscopic surface features designed using a cross table.
Regression analysis revealed that the SN ratio of softness
ranks increased in the presence of macroscopic sinusoidal
waves. To the best of our knowledge, this is the first reporton this phenomenon. Although further studies are required
to optimize the surface features, our findings make apositive addition in the literature for creating a perceived
softness for materials used in product packaging, carinteriors, and other such real-world consumer applications.
ACKNOWLEDGMENTS
This work was in part supported by MEXT Kakenhi#21H05819 and #20H04263.

4. DISCUSSION
The experimental results and analyses indicated thatsmooth surfaces with a macroscopic shape felt softer thanflat and smooth surfaces, or surfaces with micrograins.
Note that all the specimens were composed of the same
hard plastic resin; however, their surface softness felt
different when they were rubbed, owing to theirmacroscopic and microscopic surface patterns. The effectof microscopic patterns was also reported in [1] and [2],where micrograins caused surfaces to feel softer. Hence,
the results obtained in [1] and [2], and those of the present
study differ in terms of the effects of micrograins. Thisdifference may be caused by the difference in the materials
used in [1], [2], and the present study.
Although the cause of the abovementioned phenomenon
due to macroscopic shapes remains unknown, there are afew reports related to the demonstration of softness on
hard touch panels [5], [6]. They presented low-frequency
friction changes on the panel based on the pressing force
and velocity of the finger. The softness perception in our
experiment could possibly be due to changes in the finger
pressing force, or friction during the rubbing motion. The
tangential frictional force changes with changes in thesurface gradient [7]. The low-frequency changes infriction may induce perceived softness [5], [6].
The conducted research has its limitations, viz., theREFERENCES[1] Akane Ban et al., Vehicle interior parts, Patent JP5 253
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