sensors
ArticleHealing Function for Abraded Fingerprint Ridges in Tactile
Texture Sensors
Muhammad Irwan Yanwari 1,2
1

2*

and Shogo Okamoto 1, *Department of Computer Science, Tokyo Metropolitan University, Tokyo 191-0065, Japan;
irwan.yanwari@polines.ac.id
Department of Electrical Engineering, Politeknik Negeri Semarang, Kota Semarang 50275, Indonesia
Correspondence: okamotos@tmu.ac.jp

Abstract: Tactile texture sensors are designed to evaluate the sensations felt when a human touches
an object. Prior studies have demonstrated the necessity for these sensors to have compliant ridges
on their surfaces that mimic human fingerprints. These features enable the simulation of contact
phenomena, especially friction and vibration, between human fingertips and objects, enhancing thetactile sensation evaluation. However, the ridges on tactile sensors are susceptible to abrasion damage
from repeated use. To date, the healing function of abraded ridges has not been proposed, and its
effectiveness needs to be demonstrated. In this study, we investigated whether the signal detection
capabilities of a sensor with abraded epidermal ridges could be restored by healing the ridges using
polyvinyl chloride plastisol as the sensor material. We developed a prototype tactile sensor with anembedded strain gauge, which was used to repeatedly scan roughness specimens. After more than
1000 measurements, we observed significant deterioration in the sensor’s output signal level. The
ridges were then reshaped using a mold with a heating function, allowing the sensor to partiallyregain its original signal levels. This method shows potential for extending the operational lifespanof tactile texture sensors with compliant ridges.
Keywords: tactile sensor; self-healing material; abrasion damage

1. Introduction
Citation: Yanwari, M.I.; Okamoto, S.
Healing Function for Abraded
Fingerprint Ridges in Tactile Texture
Sensors. Sensors 2024, 24, 4078.
https://doi.org/10.3390/s24134078
Academic Editor: Olof Anton Lindahl
Received: 30 April 2024
Revised: 4 June 2024
Accepted: 19 June 2024
Published: 23 June 2024

Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Epidermal ridges, also known as dermatoglyphs, are raised, corrugated patterns on
the skin’s surface, notably on the palms of the hands. These structures play a crucial role inhuman tactile sensing capabilities [1–6]. In surface textural sensing, the ridges generate
vibrations when sliding over roughened surfaces, and the vibrations are transferred tomechanoreceptors inside the skin [4,5]. It has been empirically demonstrated that epidermal
ridges can enhance tactile signals by a factor of 100 in response to vibrations induced by
textures of specific wavelengths [6]. Many studies in tactile sensors have attempted toreplicate the human finger structure to emulate the sensing function of the human finger
pad [7–14]. For example, Lu et al. [9] replicated a sensor with a multi-layered structure thatcomprises upper layers characterized by high sensitivity to emulate tactile functionality
alongside lower layers featuring an extensive measurement range to facilitate pressure
sensing. Kim et al. [10] designed a sensor with a ridged structure found in different partsof a human fingerprint.
The absence of epidermal ridges significantly affects the signal from texture sensors. Human epidermal ridges possess a healing function that helps to maintain theirshape after minor injuries [15,16]. Unlike human sensors, synthetic tactile sensors do
not inherently possess mechanisms to maintain their structural integrity. To address thedamage of sensor or robotic skin, researchers have explored strategies to emulate theregenerative capacities of human skin, including the healing from cuts using healable
materials [17–26]. For example, Roels et al. [19,20] employed thermo-reversible Diels–Alderbonds to manufacture a soft finger that can heal from cuts through heating. The finger was

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2 of 12equipped with a bending sensor circuit made from the healable material. Tee et al. [17]demonstrated a synthetic skin with a self-healing function for cuts. This skin material was
conductive and exhibited pressure-sensitive performance. Khatib et al. [26] designed sensor
circuits for measuring the pressure, pH, and temperature on a self-healing material. The
material’s healing function was effective at room temperature and was further enhancedby heating. Zhou et al. [27] developed a healable fiber with piezoresistive properties thatcan be used for knitting cloth with strain-sensing capability. However, to date, healingmaterials have not been used for tactile texture sensors with epidermal ridges to enhance
the measurement of surface asperity.
This study focuses on restoring tactile texture sensors affected by abrasion damage,specifically targeting the epidermal ridges segment of the sensor. To date, no studies havevalidated healing functions for the surface ridges of tactile texture sensors. Further, thus
far, no such healing method has been implemented. Abrasion damage, which involves
the removal of material from the sensor surface, displays distinct characteristics comparedto cut damage. The missing portions are often very small, making reattachment, such as
in the method described by Wang et al. [28], impractical. To address this challenge, ourapproach involves using a reshapeable material as the primary component of the tactile
sensor. This material is complemented by a heating mold that facilitates the reshaping of
the damaged epidermal ridges. We prototyped a tactile texture sensor using this material
and tested its performance by sliding it over roughness specimens with designed surface
spatial wavelengths. The objective of this study is to demonstrate the effectiveness of thesensor’s healing function by recording the changes in the transducer’s outputs before andafter abrasion and healing, as well as to describe the method used to heal the abradedsensor’s ridges.
2. Sensor Design and Manufacturing
2.1. Structure and Dimensions
We devised a texture sensor, as illustrated in Figure 1, with a structure similar to thosemanufactured in previous studies [29–31]. The sensor was constructed with two layers
mirroring the composition of human skin’s epidermal and fat layers. The inner soft layer
exhibited a hardness of 0.17 MPa, while the outer hard layer had a hardness of 0.82 MPa.
These values are close to those determined by an anatomical study [32].
Length
50 mm

Width
30 mm
2 mm

Epidermis layer(hard material)

15 mm
HeightHeight30 mm

Epidermal ridges
Tactile receptor(strain gage)

15 mm

Fat (soft material)

60 mm
LengthBone (sensor base)
5 mmHeight

40 mm
Width

Figure 1. Sensor design. (Left): front view. (Right): side view.

The designed sensor had dimensions of 50 mm in length, 30 mm in width, and 30 mm
in height. The sensor’s plastic base had dimensions of 60 mm in length, 40 mm in width,and 5 mm in height. The top section of the sensor was circular, with a diameter of 65 mm,
imitating the shape of a human finger pad. During preliminary experiments, an alternative
sensor with a flat top surface was also employed. However, the edge of this sensor madeintensive contact with target specimens, posing challenges in maintaining secure contact

Sensors 2024, 24, 4078

3 of 12during sliding. The sensor weighed 70 g, including the plastic base, strain gauge, andits cable.
Atop the epidermal layer, a raised pattern was used to emulate the functionality of
epidermal ridges. This raised pattern was semi-circular with a diameter of 2 mm and had athickness of 2 mm beneath the ridge within the epidermal layer. The diameter of the ridge
is four to five times larger than that of an adult finger [33], necessitating downsizing in
future iterations. The patterned outer layer covered the top half of the sensor.
The most prominent natural frequency of the sensor was 415 Hz, as determined by
the peak frequency of the free vibration measured by the embedded transducer describedin Section 2.3.
2.2. Material
As the material with healing function, we employed polyvinyl chloride plastisol(Plastic Worm, Two-L Co., Ltd., Shiogama, Japan), of which hardness can be modulated byadjusting the mixing ratio of softener and hardener solutions. As mentioned in Section 2.4,
the material becomes loosened above 70 °C and completely liquefied at approximately
180 °C.
In order to determine hardness of each layer, we employed a formula from
Gent [34,35] regarding the relation between indentation hardness or Shore hardness andYoung’s modulus. We used a durometer (GS-721N, Teclock Co., Ltd., Okaya, Japan) for
measuring Shore hardness of the materials.
2.3. Transducer
The tactile sensor incorporated a strain gauge (KFGS-1-120-C1-11 L3M2R, Kyowa
Electronic Instruments Co., Ltd., Chofu, Japan) as a transducer to emulate the sensory
functionality of human tactile receptors. The strain gauge was 1 mm in length, with agauge factor of 2.10 and a resistance of 119.6 Ω. The strain gauge was positioned in the
middle between the inner and outer layers beneath the central ridge, as shown in Figure 1.
The signals from the strain gauge were conditioned by a dynamic strain amplifier (DPM913B, Kyowa Electronic Instruments Co., Ltd., Chofu, Japan). We set the strain gauge
configuration to 1500 µε/V. Data collection involved a data acquisition device (USB-6002,
National Instruments Co., Austin, TX, USA) controlled by the Data Acquisition Toolbox in
MATLAB (2023b, MathWorks Co., Natick, MA, USA).
2.4. Sensor Manufacturing
To manufacture the sensor, plastic molds created using the stereolithography technique(Form 3+, Formlabs, Somerville, MA, USA) were employed. These molds consisted offour primary components, as shown in Figure 2a. The sensor base, a part of the sensor,
features a central pillar designed to secure the cable of the strain gauge and prevent its
displacement during the manufacturing process. Additionally, four peripheral pillars on
the sensor base functioned as adhesive anchors for the soft material, preventing separation
between the plastisol and the sensor base during use. The body mold contained the liquid
plastisol during the manufacturing process of the inner layer. Tape was used to seal the gap
between the molds, as illustrated in Figure 2b,c. The layer mold secured the position of thestrain gauge between the inner and outer layers while maintaining the semi-circular shapeof the inner layer. During the formation of the inner layer, liquid plastisol was poured
through two holes located at the top of the layer mold. After completing the inner layer,
the manufacturing process was paused for two hours to allow for the solidification of
the inner layer before proceeding to the epidermal layer. Following this interim period,
the layer mold was removed from the assembly and replaced with the ridge mold. The
filling process for the ridge mold was executed from the side of the sensor. Subsequently,
the sensor underwent a two-hour cooling period before being extracted from the entire
mold assembly.

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4 of 12Material insertion
pointsGauge location
window

Ridges mold

Body
mold

Material insertion
pointsSensor base(bone)Layer
mold(a) Sensor mold part(b) Inner layer setup(c) Ridges layer setup

Figure 2. Sensor molds. (a) Four types of molds. (b) Photo of assembled molds for inner layer.
(c) Photo of assembled molds for outer layer.

2.5. Healing Processes
The sensor utilized a non-autonomous healing mechanism, specifically heating thematerial for reshaping. The surface of the abraded tactile sensor was first cleaned withan industrial paper towel. The sensor was then placed within a set of molds consisting offive parts, as shown in Figure 3a. These molds were fabricated using a heat-resistant resin(High Temp Resin, Formlabs, Somerville, MA, USA).
The heater plate, connected to a temperature controller (TXN-200AL, As One Co., Ltd.,
Osaka, Japan), was affixed to the ridge mold. The heating cable and temperature sensor
were positioned between the heater plate and the ridge mold (Figure 3c). Heating the plate
initiated the gelling of polyvinyl chloride plastisol. The ridge mold replicated the exact
surface ridge patterns used in the manufacturing process, while the side mold prevented
the leakage of liquefied material. Side and bone clamps applied pressure to the sensor fromtwo separate directions.

Figure 3. Molds for the healing process. (a) Five types of molds used for the healing process.
(b) Assembly of the molds. (c) Photo of the heater plate, cable, and temperature sensor.

During the healing process, the ridge mold and heater plate were heated to 70 ◦ C forfive minutes. Although the material is known to completely liquefy at 180 ◦ C, a lower
temperature is sufficient to turn the material into a gel. This gel fits into the female ridge
pattern of the mold under applied pressure. Additionally, heating at a temperature below
100 ◦ C prevents the formation of bubbles or vaporization of water content within thematerial. Furthermore, this low temperature helps to retain the position of the strain gauge
within the tactile sensor. The strain gauge and plastisol are not bonded; thus, if the plastisol
is overly heated, the gauge’s position may shift in the liquefied material (also see the fifth
paragraph in Section 5).
After heating, the sensor was retained within the healing mold until the mold temperature had sufficiently decreased before extraction. The sensor could be easily removed

Sensors 2024, 24, 4078

5 of 12from the molds because the surface of the polyvinyl chloride plastisol was oily immediately
after reshaping. Thus, no lubricant oils were used on the molds.
3. Experiment3.1. Textural Specimens
The specimens scanned by the tactile sensor were grating scales featuring alternating
grooves and ridges, as shown in Figure 4. The ratio of ridge width (RW) to groove width(GW) was 1:1, and the surface wavelength λ was defined as RW + GW. The specimens werecomposed of plastic (White Resin, Formlabs, Somerville, MA, USA) and had a total lengthof 13 cm, as depicted in Figure 5. We used two types of grating scales: one with RW andGW both at 1 mm, and another with RW and GW both at 0.5 mm. The depth of the grooves
was equal to the corresponding RW and GW values.

Figure 4. Specimen configuration. Ridge width (RW) and groove width (GW) were equal and they
were 0.5 for λ = 1 mm or λ = 2 mm.

Figure 5. Photo of the grating scale with λ = 2 mm (RW and GW = 1 mm). The depth of the groove
was 1 mm. The length and width were 13 cm and 4 cm, respectively.

3.2. Scanning Condition
The sensor was affixed to a six-degree-of-freedom articulated robot arm (MyCobot,
Elephant Robotics Co., Ltd., Shenzhen, China) as shown in Figure 6. The sensor slid over a
13 cm specimen at a constant speed of 30 mm/s, with the normal contact force maintained
at 1 N. The sensor continually scanned the two specimens alternately, completing five
iterations for each. The sensor then scanned a 13 cm long piece of sandpaper only once.
During this durability test, the sensor exhibited slow abrasion damage. To accelerate theabrasion process, we introduced sandpaper (Sankyo Rikagaku Co., Ltd., Okegawa, Japan)
with a 400-grit level. Once the scanning process started, the experimenter did not interferewith the measurement conditions.
The abrasion damage affected the output signals from the strain gauge, resulting
in a decline in the signal-to-noise ratio (SNR). This SNR was calculated as described in
Section 3.3. In this experimental setup, the scanning procedure was halted when the
SNR level dropped below 15 dB for both types of specimens, although specific signal
level requirements were not defined in this study. The abraded surface ridges were thenreshaped through the method in Section 2.5. Subsequently, the specimens were slid withthe sensor.
It is important to note that the surface of the sensor was greasy immediately after
the manufacturing and healing processes. The surface was then cleaned and conditioned
with talcum powder, and the sensor was slid over the specimen fifty times before the datacollection process began. During this pre-conditioning process, the sensor and specimens
were wiped several times with an industrial cloth.

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6 of 12Figure 6. Sensor placement in the robot arm.

3.3. Data Analysis
The epidermal ridges of the sensor exhibited dimensions larger than those of humanepidermal ridges. Nevertheless, the sensor demonstrated the capacity to capture featureson the specimen surface, as affirmed by the fundamental relationship that describes thespatio-temporal conversion of waves [36,37]:v = f λ,(1)

where v is the sliding velocity (30 mm/s), f is the vibratory frequency (Hz), and λ is thespatial wavelength of the specimen (mm).
Given the signal amplification role inherent to the epidermal ridges [6], the abrasion of
the ridges can be inferred from the signal levels. To assess the signal deterioration caused
by abrasion, we utilized the SNR of the voltage signals. The SNR was calculated as follows:
SNR = 20 log10 (Vsignal),Vnoise(2)where Vsignal and Vnoise represent the amplitudes of the signal and noise, respectively.
These amplitudes correspond to frequency components of 30 Hz and 15 Hz for specimens
with spatial wavelengths λ = 1 mm and 2 mm, respectively. The noise level was determined from the sensor outputs when the robot moved in the air without contact withthe specimens.
4. Results
The sensor tested specimens with spatial wavelengths (λ) of 1 mm and 2 mm at avelocity of 30 mm/s. Figure 7 shows examples of raw signals from the strain amplifier involts and their corresponding amplitude spectra after removing the DC components. The
amplitude spectra revealed peak frequencies of 30 Hz and 15 Hz, respectively, accompaniedby harmonic peaks at multiples of these frequencies, namely 60 Hz for λ = 1 mm and
30 Hz for λ = 2 mm.
Figure 8 displays the SNR values as the scanning procedures were repeated. For the
specimen with λ = 1 mm, the SNR values were nearly 20 dB before the 500th scan. The
values then gradually, but not monotonically, decreased, reaching below 10 dB after the
1300th scan. For the specimen with λ = 2 mm, the SNR values were mostly above 25 dB
before the 400th scan. With some fluctuations, the values then dropped below 15 dB after
the 1300th scan. After the healing process, the SNR levels returned to those observed before
the sensor experienced significant abrasion.

7 of 12(a) Sensor output (𝜆𝜆 = 1 mm)

2
0
–2
0

0.2

0.4
Time (s)

0.6

0.8

–60
–80

40

60

80

100

120

140

160

0.2

180

200

0.4
Time (s)

0.6

0.8

1.0

(d) Amplitude spectrum (𝜆𝜆 = 2 mm)

–20
–40
–60
–80
–100
0

20

40

Frequency (Hz)

60

80

100

120

140

160

180

200

Frequency (Hz)Figure 7. Examples of sensor outputs. Data from the 50th scan. Reference (0 dB) is 1.0 V.
(a) Amplitude spectrum for   1 mm

20
SNR (dB)

20

10
Before healing procedure
After healing procedure
0

0

200

400

600

800
1000
Scan number

1200

1400

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1400

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1800

(b) Amplitude spectrum for   2 mm
30
SNR (dB)

0

–2

0

–40

–100

0

0

Amplitude (dB)–20(b) Sensor output (𝜆𝜆 = 2 mm)

21.0(c) Amplitude spectrum (𝜆𝜆 = 1 mm)

0

Amplitude (dB)

Gauge output (V)Gauge output (V)Sensors 2024, 24, 4078

20

10

0
0

Before healing procedure
After healing procedure
200

400

600

800
1000
Scan number

1200

Figure 8. SNR for each specimen. Each point represents the mean acquired from five successive
scans. The ridges were healed after the iteration of 1350 times. (a) SNR at 30 Hz signal components
for the specimen of λ = 1 mm before and after healing. (b) SNR at 15 Hz signal components forthe specimen of λ = 2 mm before and after healing. After the 1350 scans, the sensor’s ridges were
reshaped. Fifty scans were performed to pre-condition the tactile sensor immediately after removalfrom the mold. The data during these processes were not recorded.

Figure 9 shows the amplitude spectra after the 50th scan (new sensor), 1350th scan(abraded sensor), and 1400th scan (healed sensor), with each representing the mean offive scans. Comparing the new (blue lines) and damaged (green lines) sensors, abrasion

Sensors 2024, 24, 4078

8 of 12

reduced the signal intensities across a wide frequency range of up to 200 Hz. As shownin Figure 9a for λ = 1 mm, the signal reduction of approximately 20 dB was observed
across the range. In contrast, for λ = 2 mm shown in Figure 9b, the signal attenuation
was nearly 30 dB in the range of 100–150 Hz. The decrease in amplitude after 1350 scansdepended on the frequency and specimen’s λ value. Following the healing procedure(brown lines), the signals exhibited patterns similar to those of a newly manufactured
sensor, although the amplitude levels of the healed and new sensors did not completely
match. The amplitude levels of the healed sensor lagged behind those of the new sensor byapproximately 20 dB at maximum, particularly in the 115–145 Hz range for the specimen
with λ = 2 mm. Nonetheless, this frequency range was far from the main frequency, that is,
15 Hz, calculated by Equation (1).
(a) Amplitude spectrum for   1 mm

05054th scan (new sensor)

2013501354th scan (damaged sensor)

Amplitude (dB)

14001404th scan (healed sensor)
 40

 60

 80

100
0

20

40

60

80

100
120
Frequency (Hz)

140

160

180

200

(b) Amplitude spectrum for   2 mm

05054th scan (new sensor)
2013501354th scan (damaged sensor)

Amplitude (dB)

14001404th scan (healed sensor)
 40

 60

 80

100
0

20

40

60

80

100
120
Frequency (Hz)

140

160

180

200

Figure 9. Comparison of amplitude spectra between new, damaged, and healed sensors. Means andstandard errors across five successive scans. (a) λ = 1 mm. (b) λ = 2 mm. Reference (0 dB) is 1.0 V.

The damage of the epidermal ridges was visually observed as shown in Figure 10(left). In contrast to an undamaged sensor, the affected sensor exhibited a flattening of
the ridges. Figure 10 (right) shows that the impaired ridges had been restored after thehealing process.

Sensors 2024, 24, 4078

9 of 12Figure 10. Sensor’s ridges. (a) Abraded sensor before the healing process. (b) Sensor after thehealing process.

5. Discussion
This study focused on restoring tactile texture sensors, particularly the segment mimicking epidermal ridges. These sensors suffer from abrasion damage after repeated use,and prior studies have not explored approaches similar to those examined in this study.
Through experimentation, we observed how the SNR of the sensor deteriorated due toabrasion damage. Furthermore, these SNR values were partly restored after the healing
process of the ridges.
The SNR is an assessment index based on a single frequency component and does
not account for other components. As shown in Figure 9, abrasion may affect a wide
frequency range. For evaluating such wide ranges, the evaluation indices used in previous
studies [38–40] may be utilized. These studies assessed the quality of vibrotactile signals
including multiple frequency components, taking into account human sensitivities todifferent frequency bands. Such indices might help in discussing how the tactile sensor’s
performance is impacted by damage from iterative use and how it might be mitigated by
the healing process. In the future, discussions should consider a wide frequency range, up
to 1000 Hz [41], in relation to human sensitivity.
In the field of tactile texture sensors, there is no established standard for sensitivity
levels. However, a threshold of 20 dB is typically considered indicative of a quality sensor
in some fields, such as wireless communication [42]. Referring to this standard, as shownin Figure 8, the SNR dropped below 20 dB after 500 scans for λ = 1 mm, whereas the SNR
remained above 20 dB even after 1000 scans for λ = 2 mm. One potential application of thetactile texture sensor is the autonomous classification of textures [43–45]. Therefore, thenecessary sensitivity levels should be discussed in the context of textural classification in
future studies. Furthermore, in actual industrial setups, the use of calibration specimens
is recommended for monitoring the signal intensity levels. During the long-term andcontinuous use of the sensor, the calibration specimens should be periodically scannedby the sensor, and the amplitude spectrum of the signal outputs should be analyzed. If a
problematic decrease in the response levels is detected, the user should be prompted toheal the sensor’s surface structure.
Some experimental results did not align with our expectations. We had predicted
that, as the sensor underwent repeated use, abrasion would progress and the SNR would
decrease monotonically. However, as shown in Figure 8, the SNR did not necessarily
decrease monotonically with abrasion. In some parts, the SNR increased with repeatedscanning. In other parts, the SNR fluctuated. One possible cause is the wear powder fromthe sensor material. Since the robot continued to scan the specimen automatically, thefriction conditions during the experiment might not have been maintained due to the wear
powder on the specimens. Furthermore, the sensor’s ridges were not only abraded but also
flaked off during iterative use. Such sudden changes in the surface conditions might have
led to abrupt changes in the sensory signals. Nevertheless, we do not have a convincing
explanation for the irregular changes in the SNR with the number of scans.
The most significant remaining problem is that the frequency response of the sensor
did not fully recover even after the ridges were apparently reshaped after the heatingprocess. A plausible reason is that the condition of the material in the deeper region near
the strain gauge was not fully restored. A potentially effective solution to this problem is toSensors 2024, 24, 4078

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increase the temperature of the mold used to heal the sensor’s surface ridges. In this study,
the temperature was set at 70 ◦ C, which was determined to be sufficient for reshaping theridged surface by visual inspection. Future work will focus on optimizing this process.
In the pursuit of our objective to restore sensor epidermal ridges, abrasive action
was simulated using sandpaper. However, the real-world use scenarios may involve avariety of types of materials, necessitating further experimentation to assess the sensor’s
durability under diverse operational conditions. Polyvinyl chloride plastisol was chosen
as the primary material for the sensor due to its accessibility and capacity to reshape after
heating. Despite its effectiveness, alternative healable materials such as microencapsulated isocyanates [21], poly(disulfides) [22], and natural rubber [23] offer the potential toenhance the capabilities beyond those of polyvinyl chloride plastisol. Therefore, continued
experimentation with these healable materials is essential to optimize sensor performance.
6. Conclusions
This study explored the concept of a healable tactile texture sensor to address the
problem of ridges’ abrasion. Earlier studies of healable materials developed soft robotic
fingers or skins with sensing capabilities [17–20,25,26]. However, these studies have notaddressed the abrasion of ridges unique to tactile texture sensors. Following the synthesis
and molding of a prototype sensor, distinct capabilities were observed between a newly
manufactured sensor and one with damaged ridges. The restoration of the damaged ridges
demonstrated the ability to recover the sensor’s performance to nearly peak levels. As afuture extension, it would be worthwhile to explore alternative healable materials and test
the designed sensor across a wider range of textures.
Author Contributions: Conceptualization, M.I.Y. and S.O.; methodology, S.O.; software, M.I.Y.;
validation, M.I.Y. and S.O.; formal analysis, M.I.Y. and S.O.; investigation, M.I.Y.; resources, S.O.; data
curation, M.I.Y.; writing—original draft preparation, M.I.Y.; writing—review and editing, M.I.Y. and
S.O.; visualization, M.I.Y.; supervision, S.O.; project administration, S.O.; funding acquisition, S.O.
All authors have read and agreed to the published version of the manuscript.
Funding: This research was in part funded by Suzuki Foundation (tactile texture sensor with selfrepairing epidermal ridges and enhanced human sensory processing).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Dataset available on request from the authors.
Conflicts of Interest: The authors declare no conflicts of interest.

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