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2012 IEEE RO-MAN: The 21st IEEE International Symposium on
Robot and Human Interactive Communication.
September 9-13, 2012. Paris, France.

A Method for Altering Vibrotactile Textures
Based on Specified Materials
Yoichiro Matsuura, Shogo Okamoto, Shuhei Asano, Hikaru Nagano, & Yoji Yamada
to specify the distribution of pin heights when designing
virtual textures. Therefore, such devices are generally noteasy for end users to use when designing virtual textures
although Ikei et al. proposed a method for creating virtual
textures for pin matrices based on photos of the materials [2].
Some tactile texture displays duplicate the shear force orfriction that occurs between the materials and the finger pads
during tactile exploration [4] [5] [6] [7] [8] [9]. To design
textures using these texture displays, the end users needto know or be able to measure the frictional interactions.
Ideally, however, such knowledge or procedure should not
be required. Furthermore, some methods synthesize virtual
textures by selectively stimulating the mechanical receptor
classes [10] [11]. However, these methods are not for end
users as they require specific knowledge of receptors.

Abstract— A vibrotactile texture display produces virtual
textures by applying vibratory stimuli to finger pads. In thisstudy, we developed a technique to alter such textures based on
certain specified materials. For example, the technique allows
us to alter vibrotactile textures using terms such as “wood-,”“cotton-,” or “paper-like” which are familiar to end users ofdisplays. The altered textures feel more similar to these specified
materials. We realized this technique by constructing a material
space, in which the materials are located based on the featuresof their vibrotactile spectra. The vibrotactile textures were thenmodified in this space. Our experimental results show that thetechnique can be used to alter a virtual wood texture to feellike cloth.

I. INTRODUCTION
A tactile display is a device used for presenting cutaneous
stimuli. In this article, we address a specific type of tactile
display, a vibrotactile texture display. Such displays produce
the tactile sensations of virtual material surfaces such as
cloth and wood by applying vibratory stimuli to finger pads.
Such texture displays are expected to be used for Internet
shopping, virtual museums, or software programs with haptic
feedback for mobile devices.
The purpose of this study is to provide a new method
for altering vibrotactile textures based on specified materials.
This method modifies a virtual material such that it becomes
perceptually similar to other materials such as cloth, wood, orleather. One advantage of such modification is that the usersof vibrotactile displays can design virtual textures by using
the names of familiar materials without special knowledge
regarding mechanical receptors, or the physical interactions
between finger pads and materials. For example, with ourtechnique, museum curators can create virtual textures of untouchable exhibits by using the names of specified materials.
They can indicate a texture such as the mixture of cloth andwood. Then, through the use of texture displays, they canprovide visitors with touch sensations of the exhibits.

One of the easiest methods for end users when designing textures is the synthesis of physical or psychophysicalprimitives. For example, Caldwell et al. developed a tactile
texture display that can selectively control the heat, pressure,surface roughness, and slippage stimuli [12]. The authors
then presented virtual materials by combining these physicalprimitives. Yamauchi et al. also proposed a method forsynthesizing three types of psychophysical primitives, i.e.,
perceived roughness, softness, and friction, for vibrotactile
texture displays [13]. Using these methods, the end users canpotentially create and modify virtual textures by adjustingthese familiar primitives. Our technology clearly differs fromthe methods in [12] and [13], which are based on specified
physical and psychophysical properties, whereas our method
is based on specified materials. Providing these methods
together will be more helpful for end users when designing
virtual textures.

II. ALTERING VIBROTACTILE TEXTURES BASEDON TEXTURE SPECTRA

Differences from related studies in terms of virtual texture
designs at the end-user side
Tactile texture displays have not always been suitablefor helping end users design virtual textures on their own.
A typical tactile texture display is a pin matrix. Using
this device, end users touch pins imitating the surface profiles of the intended materials or the pressure distributions
within the contact area between the finger pads and thematerials [1] [2] [3]. With this technique, end users need

Here, we describe our technique for altering vibrotactile
textures based on specified materials. First, we configurea feature quantity space of cloth, wood, and leather. The
feature quantities are generated based on the power spectraof vibrations that occur when a probe scans the material
surfaces. The measurement of vibrations is described insec. II-A. The methods used to compute the feature quantities
and space are described in sec. II-B. The method used to alter
the virtual textures is described in sec. II-C.

This work was in part supported by MEXT KAKENHI (23135514).The
authors are with the Department of Mechanical Science and Engineering,
Nagoya University, Japan.

978-1-4673-4605-4/12/$31.00 ©2012 IEEE

995

Moving direction

Laser displacement sensor

Amplitude ofvibrotactile stimuli[dB] (1µm is 0 dB)

y

x

Laser
WeightContactor

Textured surface

45
30

Meissner
MerkelPacinian

15
0
-15
-30

0
1
10
100
1000
Frequency of vibrotactile stimuli [Hz]Fig. 1. Schematic diagram of the apparatus used for measuring the surface
profile of a texture with sustained pressure

Fig. 3.
Frequency characteristics of mechanical receptors: detection
threshold (redrawn from [17])A. Texture characteristics hidden in the spectrum of vibrotactile signals

the detection of deformations in nonhairy parts of the skin.
Fig. 3 shows the frequency threshold characteristics of thesemechanical receptors for Meissner’s, Merkel’s, and Pacinian
corpuscles. Meissner’s and Merkel’s corpuscles are relatively
sensitive in a band of up to a few tens of hertz. The sensitivityof Pacinian corpuscles is considerably high in a band higher
than approximately 100 Hz. We chose the feature quantitiesof the vibrotactile textures by considering their frequency
characteristics, as described in the following section.
Method for extracting a feature quantity vector related to
textures: We assume that the tactile sensations of material
surfaces are influenced by the vibrotactile spectra uniqueto a material. We computed the amplitude spectra of thevibrations obtained in sec. II-B.1. We divided the frequency
band of 0–500 Hz into ten subbands, and calculated the sumof the amplitude spectra for each subband. The sum of theamplitudes in the ith subband for material A was determinedbySome studies have indicated a close relationship between
the tactile sensations of material surfaces and the spectra of finger pad vibrations or deformations. For example,
Bensmaı̈a and Hollins suggested that tactile differences between finely rough surfaces correlate with the differences
between the power spectra of the high-frequency bands ofthe skin vibrations caused when stroking such surfaces [14].
Okamoto et al. showed that perceived differences in vibrotactile textures are represented by an index based on theirspectra, including not only high-frequency bands but also
bands of around a few tens of hertz [15]. Furthermore,
Wiertlewski et al. showed that virtual materials can bepresented even in the absence of a relative displacement
between the finger pad and tactile display by maintaining thespectra of friction forces between them [9]. Based on thesestudies, we hypothesize that feature quantities related to theperceived characteristics of materials are extracted from thespectra of vibrotactile signals.
B. Feature quantities of vibrotactile texturessAi =1) Measuring the vibration of a contactor with sustained pressure: Finger pad deformations depend on thesurface profiles of the material during a tactile exploration.
Some researchers have attempted the indirect measurements [14] [16]; however, the direct measurement of suchfinger pad deformations remains difficult to achieve. Hence,
instead of real finger pad deformations, we measured thevibrations of a metal contactor using a load equal to atypical human force during a tactile exploration of 120 g.
The contactor has a rigid hemisphere with a radius R of
4 mm, and was moved horizontally using a linear roboticarm (Fig. 1). Each material was measured for a randomly
selected distance of 100 mm with a scanning speed of
20 mm/s. The displacements of the contactor were measured
using a laser displacement sensor (CD5-30, OPTEX FA Co.,
Kyoto, Japan), the resolution of which was set to 0.02 µm.
For the materials, we measured poplar wood, walnut wood,four types of clothes, and taurillon and vegetable-tanned
leathers, as shown in Fig. 2. Each material was sampledthrice.
2) Feature quantity vector related to textures:Role of mechanical receptors and frequency characteristics: Three types of mechanical receptors contribute toZ fia(f )df(i = 1, · · · , 10),

(1)

fi−1

where f and a(f ) are the frequency and amplitude spectra,
respectively. These sums were considered as the feature
quantities related to the perceived characteristics of thematerials. The intervals of integration are{f0 , f1 , · · · , f10 }= {0, 5, 10, 30, 50, 70, 100, 150, 250, 350, 500}.

(2)

We used narrow intervals for integration at lower frequencies,
as the sensitivities of Meissner’s and Merkel’s corpuscles atthe low-frequency bands are high, while the bands in whichthese receptors are more sensitive than the others are narrow.
We used wide intervals for integration at high-frequency
bands of more than 100 Hz since, in this wide band, thesensitivity of Pacinian corpuscles is markedly higher than
the sensitivities of the other two types of corpuscles. The
feature quantity vector related to the perceived characteristics
of material A is expressed assA = (sA1 , sA2 , · · · , sA10 )T .
996

(3)

3 mm
(a) Wood (poplar)

3 mm

3 mm

(b) Wood (walnut)(c) cloth A (cotton)

3 mm

3 mm

(e) cloth C (roughly woven)(f) cloth D (finely woven)Fig. 2.

3 mm(d) cloth B (linen)

3 mm(g) Taurillon leather

3 mm(h) Vegetable-tanned leather

Measured materials

Group ofaaamaterials
B

Factor 3

C. Space of texture features: Factor analysis of feature
quantity vectors

A (a1 , a2 , a3 )ϭͲƌ

We applied the factor analysis to feature quantity vectorsof the materials to construct a factorial space of virtualmaterials. A factor analysis is a method used to present avariety of multivariates with fewer factors. As a result of
the analysis, three factors were extracted. The implication ofeach factor can be known from its factor loadings. The factor
loadings indicate the strength of the relationship between afactor and its multivariates.

ƌC

Centroidaaamaterials
B
Factor 2

A
Fig. 5.

(b1 , b2 , b3 )C (c1 , c2 , c3 )Method for making texture A perceptually close to texture B

D. Method for altering vibrotactile textures based on specified materials

For the first factor, its factor loadings for low-frequency
bands were small, while those for high-frequency bands
were high. Hence, a material whose first factor is large
has high-frequency components. For the second factor, its
factor loadings for high-frequency bands were small, andthose of low-frequency bands were large. The second factor
represents the magnitudes of low-frequency components. For
the third factor, its factor loadings for the middle bands (30–70 Hz) were larger than those for the other bands. Hence, thisfactor features components of the middle-frequency bands.

Here, we describe how to alter the vibrotactile texture ofmaterial A, such that it feels similar to that of material B.
To achieve this, we generate material C on a line passing
through material A and the center of the group of B materials,
as shown in Fig. 5. The squares and the star represent thegroup of B materials and their centroid, respectively. The
feature quantities of material C are very similar to those ofmaterial A, as material C is closely located to material A.
However, the features of material C somewhat include thoseof material B. Hence, we consider material C to feel like a
combination of materials A and B.
Let ai and a = (a1 , a2 , a3 )T be the ith factor score andcoordinate of material A in the factorial space, respectively.
In addition, r is a mixing ratio, which indicates how closely
we make material A feel like material B. The position vectorof material C in the factorial space is determined by

The distributions of the materials in the factorial space areshown in Fig. 4. In the first and second dimensional planes(Fig. 4(a)), wood is located at the bottom. Coarse cloth (cloth
A, B, and C) and leather are located in the upper part. Fine
cloth (cloth D) is located at the center. In the second andthird dimensional planes (Fig. 4(b)), wood is located in theleft part. Coarse cloth (cloth A, B, and C) and leather are
located in the right part. Fine cloth (cloth D) is located at
the bottom. The same types of materials were located neareach other in space, and thus, the feature quantities extracted
from the vibrotactile spectra represent the characteristics ofthe materials well.

c = rb + (1 − r)a.

(4)

In (4), b is the position vector of the center of the B materials.
Given that the ith factor loading vector obtained by the factor
analysis is li , the feature quantity vector of material C is997

Coarse cloth
2
Factor 3 (middle band)

Factor 2 (low band)

2

䠇
䠇
䠇

1

Leather䠆䠆䠆0Fine cloth
-1

Wood

-2
-2

-1
0
1
Factor 1 (high band)

Wood(a) First and second factorial planes

䠆
䠆
䠆

0

-2
-2

2

䠇䠇
䠇

1

-1

䕱䞉䞉䞉poplar䕕䞉䞉䞉walnut tree䠇䞉䞉䞉cloth A䕧 䞉䞉䞉cloth B䠆䞉䞉䞉cloth C䕻 䞉䞉䞉cloth D䕿䞉䞉䞉Taurillon leather䖪䞉䞉䞉Vegetable-tanned leather

Coarse cloth

Leather

Fine
cloth
-1
0
1
Factor 2 (low band)

2(b) Second and third factorial planes
Fig. 4.

Distribution of materials in factorial spaceobtained by

y





sC1

c1
 sC2 sC ∼ (l1 , l2 , l3 )  c2  =  .  .
.
 . 
c2
sC10


(5)

Coil
MagnetAluminum base

The amplitude spectra of material A are
aA = (aA (f ), f = 1, 2, · · · , 500)
= (aA1−5 , aA6−10 , · · · , a351−500 )Fig. 6.

Schematic illustration of the tactile display(6)
Camerawhere f and aAl−m are the frequency and the subvector
consisting of the amplitudes for the frequencies of l to m,
respectively. aAl−m is determined byaAl−m = (aA (l), aA (l + 1), · · · , aA (m)) .

x

Acrylic Plate

Direction ofvibration

(7)

y
x

Voice-coil-motor
based tactile display

The amplitude spectrum of material C is determined by


sC1
sC10
aC =
aA1−5 , · · · ,aA351−500
sA1
sA10= (aC (1), aC (2), · · · , aC (500)) . (8)Fig. 7.

Given that the phase spectrum of material C is identicalto that of material A, the surface profile of material C isdetermined by


N 
X
2πf x
+ 6 CA (f ) ,aC (f ) · cos
y(x) =(9)N

Schematic illustration of the experimental apparatus

applied by the display. The display can present vibratory
stimuli of more than 500 Hz, which covers the activation
bands of the three types of mechanical receptors: Meissner s, Merkel s, and Pacinian corpuscles. We used a cylindricaltype voice coil motor (X-1740, Aoyama Special Steel Co.,Tokyo, Japan) as the actuator. Its maximum thrust force was
2.42 N with a current of 0.96 A. The movement of the coil
was restricted along the Y-axis, producing a sufficient amountof thrust.

f =1

where x and CA (f ) are a position on the material surface,
and the complex number of the spectrum of material A,
respectively. y(x) is the surface profile of virtual materialC, and is presented to the user of the texture display as
vibrotactile stimuli.

B. Experimental system
III. EXPERIMENTAL APPARATUS

The experimental apparatus is shown in Fig. 7. This apparatus measures finger motion using a camera (PlayStation
Eye, Sony Computer Entertainment Co., Tokyo, Japan), andpresents vibration stimuli to the finger pad in response to themeasured motions. The spatial resolution of the camera was
0.625 mm/pix. The control flow of the system is shown in
Fig. 8. The participants in the experiment scanned the acrylic

A. Vibrotactile texture display
The vibrotactile texture display used in this study is shownin Fig. 6. The dark gray parts were driven along the Yaxis, whereas the light toned parts were grounded. The users
explored an acrylic plate along the X-axis of the display
with their finger, and experienced Y-axial vibrotactile stimuli
998

their correct answer rates were higher than chance (0.25).
In contrast, the correct answer rates of cotton and taurillon
leather were not significantly higher than chance. These twomaterials were often confused, which is reasonable since they
are closely located in the factorial space (Fig. 4). However,
the tactile sensations of their real counterparts are not very
similar and are easily identifiable. According to the introspective reports of the participants, the softness of taurillon
leather was not presented well by the vibrotactile display.
Softness is not represented by the vibrations. Hence, wehave deemed taurillon leather unsuitable for our vibrotactile
display. In experiment 2, we used wood, cotton, and linen.
Cotton was expected to be recognizable among these threematerials.

Hand motion

HumanfingerMicrocomputer

D/A

Current
driverControl signal(Force command)
Fig. 8.

VCM

Hand
motionTactilestimulus

Input current

Block diagram of the experimental apparatus

plate of the vibrotactile display with their index finger, which
was attached to a red marker. The camera above the display
calculated the position of the center of the marker. The
positional information was sent to a microcomputer, which
determined the displacements applied to the finger pad.
Given that the finger position was x(t), y(x(t)) determinedby using (10) was presented to the participant’s finger pad
as vibrotactile stimuli.

C. Experiment 2: Verification of the method for altering
vibrotactile textures based on the specified material
The participants identified the virtual materials including
cotton, linen, wood, and the one altered using the proposed
method, which was a mixture of wood and cotton.
1) Stimuli: Four types of virtual materials were presented
to the participants: cotton (cloth A), linen (cloth B), wood
(poplar), and material X. Material X was a mixture of poplar
and cotton, with poplar as the base material. Using the
proposed method, we modified material X to feel similar tocotton, with r = 0.2. The participants were informed that thefour virtual materials would be presented. As in experiment
1, they did not know the correspondence between the realand virtual materials. Each material was presented 20 times
in random order. Hence, a total of 80 trials were conducted
per participant.
2) Procedures: The participants touched the virtual materials, and identified whether they were cotton, linen, or wood.
They were allowed to freely touch the real counterparts ofthese three virtual materials during the experiment. They
wore headphones, and were not blindfolded. The participants
were the same three volunteers from experiment 1.
3) Result of experiment 2: The average answer rates
of experiment 2 are listed in tabel II. The correct answer
rates of wood, cotton, and linen were 0.95, 0.52, and 0.95,

IV. EXPERIMENTS ON ALTERING VIBROTACTILETEXTURE
A. Objective of the experiments
In experiment 1, we tested four types of materials to selectthose most suitable for a vibrotactile display. In experiment2, we investigated whether our method can alter vibrotactile
textures based on the specified materials. For this, we used
the materials chosen through experiment 1.
B. Experiment 1: Materials suitable for a vibrotactile display
1) Stimuli: The virtual materials used were made up ofvibratory stimuli from four types of materials, poplar wood,
cloth A (cotton), cloth B (linen), and taurillon leather. We
expected that the participants would identify these four typesof virtual materials successfully since they were able tocorrectly identify their real counterparts. The participants
were informed in advance that these four types of virtualmaterials would be presented. However, they did not know
the correspondence between the real and virtual materials.
Each material was presented 20 times in random order.
Hence, a total of 80 trials were conducted per participant.
2) Procedures: The participants touched the virtual materials one by one before identifying them. The participants
were also allowed to touch the real materials freely during
the experiment. They wore headphones, which played a pinknoise to insulate the participants from the sounds generated
by the voice coil motor. They were not blindfolded. Because
the experiment was preliminary, the participants were three
volunteers from our laboratory, none of whom are an authorof this article.
3) Results of experiment 1: The average answer rates ofexperiment 1 are listed in tabel I. The participants were able
to identify the vibrotactile stimuli of wood and linen, as

TABLE I

Presented

R ESULTS OF EXPERIMENT 1: AVERAGE ANSWER RATES

virtualmaterial

CameraPoplar
CottonLinen
Leather

Perceived/Identified material
Poplar
CottonLinen
Leather
0.77
0.18
0.02
0.05
0.02
0.27
0.42
0.30
0.00
0.05
0.52
0.43
0.15
0.60
0.12
0.13

Presented
virtualmaterial

TABLE IIR ESULT OF EXPERIMENT 2: AVERAGE ANSWER RATIOS

999

Poplar
CottonLinen
X

Perceived/Identified material
Poplar
Cotton
Linen
0.95
0.05
0
0.03
0.52
0.45
0
0.05
0.95
0.28
0.70
0.02

Averageanswer rates

1䠆䠆

this altered texture more frequently as cotton than as theoriginal wood texture. As a following study, we will apply
the technique to various types of materials to further establish
its effectiveness.

䠆

0.5

R EFERENCES
0
P (Cotton | Wood)
P (Cotton | X)(a) P (Cotton|Wood)< P (Cotton|X)

P (Wood | Cotton)
P (Wood | X)(b) P (Wood|Cotton)< P (Wood|X)

Fig. 9. (a) The rates at which wood and material X were answered as
cotton, and (b) the rates at which cotton and material X were answered aswood. Material X was a mixture of poplar and cotton, and its base material
was poplar. Using the proposed method, we modified material X to feelsimilar to cotton.

respectively. These rates were higher than chance (0.33).
Hence, the participants were sufficiently able to identify thevibrotactile textures of these materials.
Material X was determined to be wood and cotton at rates
of 0.28 and 0.7, respectively. We tested whether material X
felt similar to cotton by comparing the answer rates. The results of the t-test are shown in Fig. 9. Let P (Cotton | Wood)be the probability of the participants answering cotton for
the wood material. P (Cotton | X) is the probability ofthe participants answering cotton material for the material
X. We determined that P (Cotton | Wood) < P(Cotton |X)(t0 (4) = 7.12, p < 0.01, two-tailed), and P (Wood |Cotton) < P(Wood | X)(t0 (4) = 2.79, p < 0.05, twotailed). Hence, material X is more similar to cotton than tothe original wood. These results indicate that material X feels
like a mixture of wood and cotton. Therefore, our technique
was successful in altering the vibrotactile texture of woodbased on cotton, and made the wood feel somewhat similar
to cotton. This result should be tested for a sufficient numberof paticipants and variety of materials in the future.
V. CONCLUSIONS
We developed a technique for altering vibrotactile textures
based on specified materials. The technique enables the end
users of a texture display to modify the textures using terms
such as “wood-,” “cloth-,” or “paper-like,” which does not
require knowledge regarding the mechanical interactions between human finger pads and material surfaces or mechanicalreceptors. Our method utilizes the feature quantity spaces ofmaterials, which were displaced based on the features ofvibrotactile spectra. The spectra were observed by probing
the materials. The textures were modified in this space suchthat their feature quantities approached those of the specified
materials. We conducted two types of experiments using
a vibrotactile texture display with a voice coil motor toverify the effectiveness of our technique, and verified theeffectiveness of our method through material identification.
Using our method, we altered a wood texture to feel similar
to cotton. The participants of our experiments identified[1] R. D. Howe, W. J. Peine, D. A. Kontarinis, and J. S. Son, “Remote Palpation Technology,” IEEE Engineering in Medicine
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