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Toward a new generation of smart skins

Perspective | FOCUS
Perspective | FOCUS
Toward a new generation of smart skins
Takao Someya
* and Masayuki Amagai3,4*
Rapid advances in soft electronics, microfabrication technologies, miniaturization and electronic skins are facilitating the
development of wearable sensor devices that are highly conformable and intimately associated with human skin. These
devices—referred to as ‘smart skins’—offer new opportunities in the research study of human biology, in physiological tracking
for fitness and wellness applications, and in the examination and treatment of medical conditions. Over the past 12 months,
electronic skins have been developed that are self-healing, intrinsically stretchable, designed into an artificial afferent nerve,
and even self-powered. Greater collaboration between engineers, biologists, informaticians and clinicians will be required for
smart skins to realize their full potential and attain wide adoption in a diverse range of real-world settings.
mart skins are capable of monitoring minute physiological
changes that occur very gradually over long periods in daily
life1. In the research realm, smart skin promises to advance our
understanding of human physiology and of the range of phenotypes
that lead from health to disease; in the wellness arena, it opens up
new possibilities for the continuous monitoring of fitness and sleep
for consumers; and in the clinical setting, it is transforming the provision of healthcare and the ways in which medical personnel can
monitor patients2–4.
Despite the above promise, the increasing adoption of smart
skins in real-world settings requires progress in several areas. These
include further reductions in device size and obtrusiveness, optimization of battery power, increased device robustness and working
lifetime, improved sensor sensitivity and dynamic range, and greater
parallelization of analyte measurements. In addition to improvements in the devices themselves, new computational approaches
will be needed to facilitate data analysis, data security and data confidentiality. Input from skin biology should also drive the engineering of new smart skin materials to enhance biocompatibility and
reduce biofouling over a device’s lifetime. And, as smart skins move
out of the laboratory setting, more knowledge is needed concerning patient behavior and compliance, together with input on how
to integrate device data into clinical decision making and existing
laboratory testing. Robust evidence of the efficacy and safety of
these devices will also require expert input into clinical trial design,
patient recruitment and consent. Finally, device manufacturing
costs and mass production must all be economically competitive.
In this Perspective, we provide a short introduction to the key
drivers in electronics that are facilitating smart skin design, outline
advances in our knowledge of skin biology, discuss the challenges
posed by skin sensing and provide an overview of future directions
for the field. In our view, further progress in smart skin will require
increasing collaboration of experts from a wide array of disciplines,
including electronics engineers, materials engineers, chemical engineers, biologists, informaticians and clinicians.
Sectors driving smart skin development
Three main areas have facilitated the rapid development of smart
skins over recent years. One important contributor has been
advances in semiconductor microfabrication technologies. These
have driven the miniaturization of silicon microelectronics and
enabled the downsizing of medical devices from stationary, handheld instruments to the current generation of wearable sensors that
sit non-invasively and unobtrusively on the skin.
At the same time, the emergence of mechanically soft
electronics5,6, which are capable of twisting, bending and stretching like a rubber sheet7, has also transformed the types of wearable
device used in skin sensing. Devices using soft electronics can be
deployed in close contact with the skin and thus can measure biological signals with a much higher precision than previous sensors8.
A third driver has been recent progress in robotics. Human skin
is an elegant sensor that has inspired the development of electronic
skins (e-skins) for robots that can detect pressure and thermal distributions5,6. This work in robotics has resulted in the development
of highly conformable e-skin that in turn is suitable for use on the
human body. Thus, a silicon membrane can now be directly laminated onto a person’s skin8. Such intimate and conformal integration of electronics with the human skin is allowing researchers to
aggressively incorporate more advanced electronic functions, such
as stimulators, displays and power sources, into skins.
The ultimate goal of smart skin is to non-invasively measure all
aspects of human activities in daily life under conditions as natural
as possible, which would enable e-skins and human skin to interactively reinforce each other and maximize their potential in several
different realms, including research, wellness and fitness, and the
clinical setting.
In this last arena, smart skin promises to dramatically change
the practice of medicine. One of the current limitations of medicine
is that the diagnosis and treatment design is largely based on the
observation of patients’ symptoms in a clinic or hospital without
detailed knowledge of their daily environmental conditions outside
this setting. Many environmental factors, dietary factors or psychological stressors affect important medical parameters that are
currently only assessed in hospitals, such as blood pressure, body
temperature on different parts of the body, serum electrolyte or
hormone levels, and transepidermal water loss. At the same time,
conventional medicine often administers treatments of last resort
to patients presenting symptoms of late-stage disease; it stands
to reason that interventions aimed at asymptomatic, earlier stage
disease—which could be tracked via biomarkers detected using
non-invasive smart sensors—would have a higher chance of
success. Thus, routine monitoring of these medical parameters
using smart skins is expected to transform medical treatment in the
coming years.
The current sensor landscape
On-skin sensors currently measure three types of biological signal:
electrical, physical and chemical (Table 1). Of the sensors used to
Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, Japan. 2Thin-Film Device Laboratory & Center for
Emergent Matter Science (CEMS), RIKEN, Wako, Japan. 3Department of Dermatology, Keio University School of Medicine, Tokyo, Japan.
Center for Integrative Medical Sciences, RIKEN, Yokohama City, Japan. *e-mail: [email protected]; [email protected]
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Table 1 | Biological signals that can be measured through the skin
Category Target analyte
Challenges for wearables and/or skin electronics
Seizures, epilepsy, head injuries,
dizziness, headaches, brain
tumors and sleeping problems
High resolution is required to accurately distinguish the pattern and size of an EEG
signal. As an EEG signal is very small, measurement is sensitive to the surrounding
environmental conditions66,67.
Cardiovascular disease
As in EEG, high resolution is required. To precisely detect small signals, impedance
between the skin and electrode can be reduced by conductive gel electrodes.
However, the gel dries out in long-term usage68,69.
Neuromuscular diseases,
kinesiology, motor control
As surface EMG attaches to the skin and measures electrical signals from muscle
activity, it must be stable under a variety of physical deformations. Surface EMG
measurement has limitations in interpretation. Fat can affect EMG recordings; it
increases the amplitude of the surface EMG signal. Cross-talk among neighboring
muscles makes it difficult to measure signals from an individual muscle, particularly
for deep muscles70.
Measurement of tremor
Both high sensitivity and fast response time are required. Mechanical robustness
is important for strain sensors. In most cases, strain is measured by the change in
resistance as the length of the resistor changes. However, change in sensitivity due to
the intrinsic limits of the material itself poses a problem71,72.
Heartbeat, heart rate
Both high sensitivity and fast response time are required. As mechanical deformation
usually causes performance changes in pressure, it is difficult to measure pressure
separately from the effect of strain68.
Intraocular pressure
Since the target pressure range is very low, high sensitivity and thorough reversibility
of pressure sensors are required to measure intraocular pressure. When sensors
are directly placed on an eyeball, both optical transparency and biocompatibility are
required. In addition, practical applications mandate wireless systems73,74.
Body temperature
High sensitivity is required in the range 35–45 °C. Such sensitivity is difficult to
achieve; in general, temperature sensitivity of flexible sensors is low75. The main
method is to measure resistance variation of a metal at different temperatures.
Oximetry, PPG, vein mapping
Because photonic devices can probe information inside the body, conformal contact
between sensors and skin does not mean a precise alignment between sensors and
target. The absorption depth of incident light depends on wavelength of light sources
and the position of the skin.
Cardiac auscultation, swallowing, Mechano-acoustic signals on the skin are weak; therefore, high sensitivity is
needed. Their analysis needs to consider mechanical impedance matching between
the device and the skin. Sounds from the body and the environment need to be
Chemical Glucose
Accuracy is critical; measurement accuracy criteria are specified by the US Food
and Drug Administration as a requirement for approval. The following issues have
to be solved: lag time, long-term stability for enzymatic glucose detection, and
contamination by biofouling16,17.
Lactic acid
Muscle fatigue
Most lactic acid sensors are based on enzymes (for example, lactate oxidase). Like
glucose sensors, these sensors also face stability issues relating to the enzyme. As
the detection of lactic acid is used to monitor changes of physical condition during
exercise, it does not usually require long-term or continuous monitoring. As the
exercise progresses, the amount of accumulated lactic acid increases, making it more
difficult to calibrate absolute values20,76.
Potassium and
sodium ions
Most ion sensors measure the voltage difference (open circuit potential) between
working and reference electrodes, whereas enzymatic sensors are based on
amperometry. Voltage-based measurements are susceptible to environmental
conditions. Na+ and K+ concentrations are used as secondary biomarkers in sweat
monitoring. Dehydration can induce an increase in the concentrations20.
Chloride ion
Cystic fibrosis
Sweat agonists (e.g., pilocarpine) are used to force sweating through iontophoresis.
During the iontophoresis, skin irritation may occur and cause discomfort. In addition,
efficiency in sweat collection is important because the total quantity of sweat
is small77.
measure electrical signals, electrocardiography (ECG) and electroencephalography (EEG) are in widespread use for monitoring the
heart and brain, respectively. Because of the large amplitude of ECG
(~1 mV), its detection is much easier than that of other electrical
signals, such as EEG and electromyography (EMG). In commercial
ECG monitors, readily accessible external units are connected to a
set of gel-based electrodes that attach to the body by external cables.
Using these devices, the ECG can be monitored using well-established instructions (for example, determination of electrode pasting
positions, signal frequency, data acquisition and analysis; Table 1).
The three main physical signals detected by skin sensors are temperature, pressure and strain. Body temperature is one of the most
basic indicators for health status; however, skin sensors measure surface temperature9 rather than core body temperature, which is the
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Skin surface
Tight junction
Corneocyte(Kelvin’s 14-hedron)
Stratum corneum
Stratum granulosum
Stratum spinosum
Stratum basale
Basement membrane
Langerhans cell
Hair follicle
Sweat gland
Blood vessels
Fig. 1 | Schematic structure of human skin. a, The skin is not a simple flat shield against external insults, but contains complex appendages such as
hair follicles and sweat glands. The skin consists of three main layers: the epidermis, dermis and subcutaneous fat. The dermis contains blood vessels,
lymphatic vessels and nerves, which are linked to other remote organs in the body. b, The epidermis contains two sets of physical barriers: the stratum
corneum as an air–liquid barrier and tight junctions as a liquid–liquid barrier. Tight junctions are formed between the differentiated keratinocytes or SG2
cells, which are located in the second layer of the stratum granulosum (SG). Langerhans cells are antigen-presenting cells; they capture external antigens
from the tips of extended dendrites above tight junctions to present them to the immune system.
clinically important measurement. Regarding pressure, both pulse
and blood pressure are biological signals important for monitoring
cardiovascular status, whereas intraocular pressure is an important
marker for glaucoma. In the context of strain, various body motions
can be recorded as indicators, including tremor, another clinically
relevant measurement. In some neurological diseases, aberrant or
altered body motions are also important indicators of disease. For
example, tremor is an important signal for monitoring Parkinson’s
disease and epilepsy. Furthermore, the locations of physical impairment and tremor conditions, such as frequency and interval, can be
used to infer the affected region of the brain. By measuring pressure and strain on the skin, vital signs, such as pulse and respiration
rates, and movement of the living body, such as swallowing, can also
be measured10–12.
In terms of chemical sensors, most of the emphasis in sensor
development has been on wearable monitors for glucose. Glucose
level is a critically important biomarker for diabetes, and its direct
measurement in blood requires painful blood sampling and can
lead to scarring of the pinprick sites. As an alternative, non-invasive
wearable sensors that monitor glucose concentrations in interstitial
fluid using needles have been actively studied and commercialized
in recent years. Because glucose in the interstitial fluid originates
from blood glucose, both levels are, in principle, the same. However,
the glucose levels in interstitial fluid show a delay of approximately
20 min compared with glucose levels in blood13. Monitoring glucose
in external body secretions, such as saliva, sweat and tears, has been
intensively studied as a non-invasive approach. Indeed, skin chemical sensors integrated with microfluidics have been developed to
monitor glucose in sweat14, and a correlation between glucose levels
in biofluids and those in blood has been reported15–17.
Three main issues continue to challenge non-invasive measurements of glucose. The first is sensor sensitivity. The glucose level in
sweat is ~100 times lower than that in blood; thus, to ensure robust
and representative measurements of blood glucose, wearable sensors require high sensitivity and reliability. Second, although the
enzymes (for example, glucose oxidase) used in glucose sensors
have high selectivity, they are prone to error due to cross-contamination of the sample by other analytes. Biofluids contain many
materials, such as ascorbic and lactic acids, that affect the accuracy
of glucose oxidase detection, particularly at low sugar concentrations. The third problem is the lag time for on-skin measurement,
which is more complicated when monitoring interstitial fluids than
blood because of measurement protocols. The lag time includes the
time of biofluid collection, in addition to intrinsic lag time. Thus,
the total lag time depends on how these sensors collect saliva,
tears and sweat, which confounds accurate real-time monitoring.
Furthermore, long-term stability is an important issue for all enzymatic sensors.
Although glucose is the main target for chemical sensors, several devices for measuring other chemical biomarkers are also
under development. These include ones that measure lactic acid
for muscle fatigue and peripheral oxygen saturation for anesthesia management, surgeries and patient monitoring in intensive
care units. In cystic fibrosis diagnosis, ionic sensors can monitor
potassium and sodium ions (hydration status) while monitoring
chlorine ion concentration in sweat. Indeed, sweat monitoring is
one of the most intensively studied areas for measuring target analytes18–21. Wristband-type sweat analysis sensors are now available
that contain all the electric modules, including power source, in
one device20. In addition, photonic ultrathin-film devices directly
contacting the skin, referred to as photonic skins, have also been
used to measure more advanced biological information, such as
blood oxygen22,23.
Non-invasive skin monitoring devices also enable the continuous
measurement of physiological parameters from skin surfaces that
are affected by various environmental and psychological factors. For
example, transepidermal water loss, which involves water evaporation from the skin surface, is one of the most important parameters
to evaluate skin barrier function24; in the future, it may be possible to
use measurements of its changes to predict the development of skin
conditions, such as atopic dermatitis. Similarly, in diabetes management, non-invasive measurements of glucose spikes after meals
might prove more informative than recording fasting glucose for
predicting the risk of diabetes mellitus and cardiovascular events25.
The skin surface of healthy individuals is weakly acidic26. But
we have little information on how skin surface pH fluctuates in
response to different environments (for example, under high or low
humidity conditions at different temperatures, which constantly
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change in daily life). Non-invasive skin monitors will allow us to
gather such data. This type of monitoring will be possible only when
skin sensors do not affect the homeostasis of the skin’s stratum corneum (see below).
Understanding skin biology
Human skin is more than ‘skin deep’; it also serves as a mirror of
internal organ function. The skin provides a physical permeability
barrier, which protects the body from infectious agents, and functions in thermoregulation, sensation, ultraviolet protection, and
wound repair and regeneration. These various functions of the skin
are mediated by one or more of its three major layers—from outside
to inside, the epidermis, dermis and subcutaneous fat (Fig. 1). The
skin contains blood vessels, lymphatic vessels and nerves that are
linked to other remote organs in the body. Thus, the skin is the most
practical organ from which valuable information inside the body
can be extracted by visual inspection and palpation. Thus, smart
skins have tremendous potential to non-invasively monitor different biological signals from multiple organs.
The clinical meaning of ‘non-invasive’ is that there is no physical break in the skin and no disturbance to the homeostasis of the
skin. Thus, gaining the best possible understanding of the precise
mechanism of skin homeostasis is indispensable for designing
smart skins that do not disturb essential physiological mechanisms.
Furthermore, the skin has traditionally been considered a simple
organ sheet that functions to protect the delicate living body from
the harsh environment. However, we now know that the skin is
much more than a static, impenetrable shield against external
insults. Rather, it is a dynamic, complex, integrated arrangement
of cells, tissues and matrix elements that mediate a diverse array of
functions. Recent advances in dermatology and cutaneous biology
have provided deeper insights into the complex structure and function of the skin27,28.
The epidermis harbors at least two sets of physical barriers—
namely, the stratum corneum as an air–liquid barrier and tight junctions as a liquid–liquid barrier29,30—together with elegant innate and
acquired immune system barriers (Fig. 1). The stratum corneum
of human skin is the outermost barrier of the body’s surface. It is
approximately 10 to 20 µm thick and contains about 10 to 25 layers
of cornified cells or dead keratinocytes. Using Raman spectromicroscopy and time-of-flight secondary ion mass spectroscopy, the
stratum corneum has now been shown to comprise at least three
distinct layers31–34. The upper layer appears to function as a sponge,
where water-soluble small molecules soak in and out. The middle
layer has the capacity to absorb and hold water, and the lower layer
contributes to the structural strength of the stratum corneum. Tight
junctions seal intercellular spaces and limit molecular movement
through the paracellular pathway; these are formed between the last
living keratinocytes, SG2 cells (the second layer of stratum granulosum)35,36. SG2 cells and cornified cells are shaped as a tetrakaidecahedron (a polyhedron with 14 faces), with tight junctions at their
edges37. Although differentiated keratinocytes continue to move up,
no leakage occurs because tight junction formation shifts attachments from one edge to another edge of tetrakaidecahedrons during
the transition.
The skin contains appendages, including hair follicles, sweat
glands and sebaceous glands. Only mammals have hair, the primary role of which is insulation and protection from harsh external
conditions. Myelinated sensory nerve fibers run parallel to the hair
follicles, surrounding them and forming a dense nerve network. A
vascular network is also well developed around the follicles, encasing them. Recently, hair follicles have also been found to play a role
as immune sensors through the secretion of several chemokines to
recruit immune-mediated cells in response to mild physical stress
such as gentle scratching38. Thus, we need to remember that even a
minor perturbation may affect skin homeostasis, which could result
in misinterpretation of extracted signals through skin by electric
skin sensors.
Challenges associated with skin measurements
Skin sensors are categorized as non-invasive devices and have
fewer risks than implantable devices, but that does not mean they
are without risk. Indeed, for individuals with certain metal allergies, contact dermatitis is unavoidable, which may cause systemic
contact dermatitis in rare cases39,40. Moreover, considering the longterm use of skin electronics, the possibility of developing allergies
through cutaneous sensitization to metals and other chemicals used
in skin sensors cannot be ruled out.
Most skin electronic devices have been manufactured on continuous films that inhibit the secretion of sweat or other fluids from
the skin because of their low gas permeability, which would cause
overhydration and maceration of the stratum corneum and interfere with its normal barrier function. Thus, prolonged exposure of
skin electric devices could easily induce irritant contact dermatitis, resulting in removal of the device. Therefore, device long-term
safety has not yet been proven dermatologically. In addition, the
non-physiological space created between the skin and the electric
device creates a challenge in measuring a biofluid such as sweat,
which we wish to treat as a surrogate for blood and/or interstitial
body fluid. The delay or low sensitivity of skin surface measurements compared with those of core body or blood is due to these
and other factors and needs to be optimized and calibrated individually, depending on the purpose of skin surface measurements.
Another challenge is data analysis. Faint biological signals can be
easily hidden by different types of environmental noise, body noise
(for example, myoelectricity at the time of brain wave measurement), motion artifacts and sensor misalignment. The robustness
of a biological signal depends on increasing the sensor’s sensitivity
and selectivity for the signal and the filtering technique by which we
extract only the salient data. In addition, an algorithm is needed to
extract the desired biomarkers from clean data, most likely with an
assistance of artificial intelligence systems. Increasing the quality of
a signal would promote its application to therapy and create a bidirectional closed-loop system whereby electronics and the human
body monitor and stimulate each other.
Most non-invasive measurements of biological signals on the
skin are based on indirect detection methods. As indirect measurements can be subject to a greater risk of artifacts than traditional
tests of clinically validated biomarkers in the controlled laboratory setting, wearable sensors often require calibration and crossvalidation via the detection of multiple different markers. This can
increase the confidence of indirect measurements and also take into
account individual-to-individual variation in biological signals and
differences that arise as a result of physical conditions at the time
of measurement at the skin site (for example, temperature or atmospheric pressure).
Because of such inherent inaccuracies, indirect biological signals cannot always be used in a clinical setting as absolute indicators for disease diagnosis. Conversely, the availability of daily
biological monitoring by skin electronic devices may introduce a
new parameter for clinical assessment. For example, the severity
of atopic dermatitis is currently measured by severity scoring of
atopic dermatitis (SCORAD)41 or eczema area and severity index
(EASI)42, which are both based on the extent of skin lesions that
result from scratching. If the duration of scratching behavior itself
could be monitored at specific body sites throughout the day, the
scratching monitoring score itself may provide a suitable clinical
parameter for disease activity. In medicine, it is also often necessary
to continuously observe subtle changes over a prolonged period
(e.g., for more than 1 week) to ensure the safety and effectiveness
of new devices. Furthermore, in the case of ECG measurements
for neurological conditions, such as epilepsy, a tremendous need
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exists to constantly monitor the incidence of seizures over a long
period because it is difficult to predict when they will occur. The
ultimate ideal skin sensor should be designed to avoid disturbing
the homeostasis of the physiological skin barrier to prevent misleading monitoring outcomes.
Unlike in medical settings, however, there are still many nonclinical applications wherein there is an interest in tracking physiological status and a greater tolerance for measurement error. Thus,
wearable sensors have received wide adoption in fitness and sports,
where biological signals, such as lactic acid in sweat for muscle
fatigue and ions for hydration, as well as ECG and EMG monitoring, have all been in wide use43,44.
Future directions
The development of smart skin promises new approaches to observational human research, offers novel applications in wellness and
fitness, and augurs a new era of healthcare, enabling medicine to not
only move out of clinical centers to outpatient settings but also transition away from sporadic treatments of last resort for end-stage,
symptomatic disease to preventative and continuous interventions
in presymptomatic disease. But for these applications to be realized in real-world settings, smart skin presents major challenges for
material engineers, electronics engineers and chemical engineers,
who in turn will require increased input from clinicians, biological
researchers and informaticians.
Capturing symptoms of chronic disease requires the detection of
small changes over long periods with high reproducibility. Similarly,
tracking physiological status in healthy individuals over long periods of time necessitates sensor technology capable of robust and
reproducible measurements in many environmental contexts. Thus,
it is essential to simultaneously improve not only the precision and
robustness but also the length of time of biological signal measurement under the harsh environment of normal daily life.
Furthermore, usability is one of the most important evaluation
parameters for wearable sensors. Ideally, a measurement should
commence immediately after the sensor is attached to the approximate body location without expert knowledge, unlike in traditional
medical measurements in which a trained technician fixes and measures a probe at an appropriate body location on the subject.
As the miniaturization, thickness and weight of skin sensors continues to be optimized, we expect to see an increase in the length of
monitoring possible and a decrease in the burden and obtrusiveness
of devices in patients and healthy subjects. In addition, the intimate
integration of electronics with the skin should improve measurement accuracy, reduced contact impedance and minimize the
chance of sensor detachment during body motion. To fully exploit
these envisaged benefits of skin sensors, innovative technologies are
needed to further improve their reliability.
Materials researchers are being challenged to take new steps in
the design of material concepts. For example, multimodal, largearea, stretchable sensor arrays are in development using organic
semiconductors, which are inherently soft and compatible with
large-area manufacturing processes45. Similarly, self-healing stretchable conductors and intrinsically stretchable semiconductors have
also been recently reported46–48.
Undesired effects due to disturbance of skin homeostasis by
wearable devices may also be reduced dramatically by adding
breathability to lightweight, thin, stretchable, and non-cytotoxic
materials. Our group (M.A., T.S. et al.)49 has recently reported skin
sensors based on nanomesh structures, which offer high gas permeability and prevent inflammatory reactions, even when adherent to
the skin for 1 week.
Another notable trend is the increasing adoption of sensors that
measure multiple biomarkers. Biomarkers targeted by skin sensors are expanding from a single-point, single-analyte approach to
devices capable of sensing multiple analytes at multiple time points,
Smart skin
Drug delivery
Healable skin
Rubbery skin
Photonic skin
Highly precise
Fig. 2 | Recent research trends in smart skin from four viewpoints. First,
the structures of smart skins are advancing from stretchable8 to ultra-thin45
to breathable49 sensors, resulting in enhancement of biocompatibility, as
well as reduced burden of sensor attachment. Second, multi-modality is
expanding from electric43 to physical10 to chemical18 sensors. Third, more
advanced functions such as stimulation54, drug delivery14 and displays55
are being incorporated, in addition to sensing functions. Fourth, novel
materials such as self-healing conductors47, intrinsically stretchable
semiconductors46 and photoactive materials22 are being developed.
Images reproduced from refs. 8,14,18,22 with permission from AAAS. Images
reproduced from refs. 10,45–47,49 with permission from Springer Nature.
Images reproduced from ref. 55 with permission from Wiley. Image
republished with permission of Royal Society of Chemistry, from “Roll
to roll processing of ultraconformable conducting polymer nanosheets,”
Zucca, A. et al. J. Mater. Chem. C 3, 6539–6548 (2015)43; permission
conveyed through Copyright Clearance Center, Inc. Image reprinted with
permission from An, B. W. et al., “Stretchable, transparent electrodes as
wearable heaters using nanotrough networks of metallic glasses with
superior mechanical properties and thermal stability,” Nano Lett. 16,
471–478, Copyright 2016 American Chemical Society54.
particularly for chemical biomarkers. Because of the inherent inhomogeneity and dynamism of the human body, multi-point sensing is
needed to improve measurement reliability. In particular, large-area
sensors that establish intimate contact with the skin for multi-point
sensing require softness. Furthermore, it is important to improve
accuracy on the basis of complex information from different analytes because most skin sensors rely on indirect measurements.
Increasing the quality of a biological signal from a sensor is
another important goal. It would promote medical applications of
sensor technology and create a bidirectional closed-loop system
whereby electronics and the human body monitor and stimulate
each other. The emergence of stretchy devices that can be directly
laminated onto the skin is being adapted for multiple electronic
functions50–53, including stimulation54 and displays55. In this respect,
there is likely to be increasing overlap between smart skins and the
nascent area of electroceuticals56,57.
Beyond their use in monitoring and stimulating human physiology, smart skin also promises to enhance prosthetics. For example,
a prosthetic hand that feels both pain and pressure has recently
been described51. Inspired by touch receptors in human skin, this
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multilayer ‘e-dermis’ senses pressure information, which is converted into spiky signals similar to the output of actual neurons and
transmitted to the peripheral nerves in the skin, which ‘feel’ pressure58. Furthermore, touch sensation can be implemented by artificial nerve systems, wherein ‘electronic neurons’ based on flexible
organic electronics recognize and react to sensory inputs59. In this
way, electronics and the skin interactively reinforce each other in a
symbiosis, and smart skins as bidirectional systems are producing
new relationships between humans and machines.
A final goal for devices in the field, many of which are still very
much in the research phase, is to engineer systems that can be produced on a large scale. Because sensor systems are being simplified
and becoming more sophisticated in terms of analyte measurement, high-throughput manufacturing of many devices has been
established. However, we cannot underestimate the importance
of establishing mass production technology for smart skins and
reducing manufacturing cost to facilitating the dissemination of
this technology.
Figure 2 summarizes recent research in skin sensors and illustrates the emergence of two key trends. First, smart skin research
is maturing from an endeavor carried out inside the laboratory to
work outside the laboratory, including clinical trials. Field trials
have started as practical requirements are being met by substantial improvements in the reliability of the devices, which in turn is
ensuring greater accuracy and reliability of sensor measurements.
By improving the electrical performance of individual stretchy elements and interconnections while maintaining their mechanical
durability in conjunction with advances in flexible power sources
(including wireless power transmission60,61, a flexible battery62,63,
and a self-powered system with flexible photovoltaic cells1), appropriate solutions can be selected to achieve the integration of different systems and requirements.
Second, the migration of smart skins out of the laboratory and
into the field has triggered the need for more extensive collaboration, not only between engineers and clinicians, but also between
engineers and biologists and informaticians. For example, the
emerging understanding of skin structure and function can be used
to inform sensor design. The change from continuous film to nanomesh structure of skin electronic devices has provided a much better physiological microenvironment for skin surfaces, especially for
long-term use49, minimizing undesired effects on homeostasis of
stratum corneum and skin barrier functions. Similarly, given the low
signal-to-noise ratio of many biological signals and the high interindividual variability of analyte levels, innovative computational
approaches for filtering out biological and technical variance in onskin measurements will also be key. For example, the accuracy of
ECG and photoplethysmography (PPG) measured by wearables can
be significantly improved by integration with accelerometers that
can compensate motion artifacts64,65. In addition, data security and
privacy issues must be addressed by sufficiently ensuring safety of
information in all the steps, from the collection of biometric information with sensors, data transmission and storage in the server to
actions such as medical treatments. To constructively utilize smart
skins in combination with existing knowledge from the information
technology sector and healthcare realm, regulations must be carefully set by considering a balance among benefits, risks and costs.
Finally, in the realm of healthcare, it will be important to ensure
that the devices under development satisfy the needs of physicians
and health personnel in terms of clinical decision making and
ensuring that sensor outputs are clinically actionable. Engineers
will also need to work closely with clinicians to ensure efficient
patient recruitment and appropriate design and conduct of human
trials. The need for input from qualified medical personnel applies
not only to human testing in the context of a clinic, but also to
observational studies in an outpatient setting, where an understanding of patient compliance and behavioral issues may also have
a substantial influence on measurement reliability. For fields that
normally work in silos to come together, we believe the driver will
be an appreciation for the importance of skin biology in electric
skin device design. In seeking to devise clinically relevant technology for accurate, long-term measurements, a deep understanding
of the mechanisms underpinning skin homeostasis will have to
take center stage.
Received: 24 October 2018; Accepted: 3 January 2019;
Published online: 2 April 2019
1. Park, S. et al. Self-powered ultra-flexible electronics via nano-gratingpatterned organic photovoltaics. Nature 561, 516–521 (2018).
2. Chiauzzi, E., Rodarte, C. & DasMahapatra, P. Patient-centered activity
monitoring in the self-management of chronic health conditions. BMC Med.
13, 77 (2015).
3. Piwek, L., Ellis, D. A., Andrews, S. & Joinson, A. The rise of consumer health
wearables: promises and barriers. PLoS Med. 13, e1001953 (2016).
4. Gambhir, S. S., Ge, T. J., Vermesh, O. & Spitler, R. Toward achieving precision
health. Sci. Transl. Med. 10, eaao3612 (2018).
5. Someya, T. et al. A large-area, flexible pressure sensor matrix with organic
field-effect transistors for artificial skin applications. Proc. Natl Acad. Sci. USA
101, 9966–9970 (2004).
6. Someya, T. et al. Conformable, flexible, large-area networks of pressure and
thermal sensors with organic transistor active matrixes. Proc. Natl Acad. Sci.
USA 102, 12321–12325 (2005).
7. Rogers, J. A., Someya, T. & Huang, Y. Materials and mechanics for stretchable
electronics. Science 327, 1603–1607 (2010).
8. Kim, D.-H. et al. Epidermal electronics. Science 333, 838–843 (2011).
9. Taylor, N. A. S., Tipton, M. J. & Kenny, G. P. Considerations for the
measurement of core, skin and mean body temperatures. J. Therm. Biol. 46,
72–101 (2014).
10. Schwartz, G. et al. Flexible polymer transistors with high pressure sensitivity
for application in electronic skin and health monitoring. Nat. Commun. 4,
1859 (2013).
11. Kang, D. et al. Ultrasensitive mechanical crack-based sensor inspired by the
spider sensory system. Nature 516, 222–226 (2014).
12. Yao, S. & Zhu, Y. Wearable multifunctional sensors using printed stretchable
conductors made of silver nanowires. Nanoscale 6, 2345–2352 (2014).
13. Klonoff, D. C. Noninvasive blood glucose monitoring. Diabetes Care 20,
433–437 (1997).
14. Lee, H. et al. Wearable/disposable sweat-based glucose monitoring device with
multistage transdermal drug delivery module. Sci. Adv. 3, e1601314 (2017).
15. Farandos, N. M., Yetisen, A. K., Monteiro, M. J., Lowe, C. R. & Yun, S. H.
Contact lens sensors in ocular diagnostics. Adv. Healthc. Mater. 4,
792–810 (2015).
16. Kim, J., Campbell, A. S. & Wang, J. Wearable non-invasive epidermal glucose
sensors: a review. Talanta 177, 163–170 (2018).
17. Lee, H., Hong, Y. J., Baik, S., Hyeon, T. & Kim, D.-H. Enzyme-based
glucose sensor: from invasive to wearable device. Adv. Healthc. Mater. 7,
e1701150 (2018).
18. Koh, A. et al. A soft, wearable microfluidic device for the capture, storage,
and colorimetric sensing of sweat. Sci. Transl. Med. 8, 366ra165 (2016).
19. Choi, J. et al. Skin-interfaced systems for sweat collection and analytics. Sci.
Adv. 4, aar3921 (2018).
20. Gao, W. et al. Fully integrated wearable sensor arrays for multiplexed in situ
perspiration analysis. Nature 529, 509–514 (2016).
21. Ghaffari, R., Baker, L. B. & Rogers, J. A. Skin-interfaced systems for sweat
collection and analytics. Sci. Adv. 4, eaar3921 (2018).
22. Yokota, T. et al. Ultraflexible organic photonic skin. Sci. Adv. 2,
e1501856 (2016).
23. Lochner, C. M., Khan, Y., Pierre, A. & Arias, A. C. All-organic optoelectronic
sensor for pulse oximetry. Nat. Commun. 5, 5745 (2014).
24. Blattner, C. M., Coman, G., Blickenstaff, N. R. & Maibach, H. I.
Percutaneous absorption of water in skin: a review. Rev. Environ. Health 29,
175–180 (2014).
25. Ceriello, A. Impaired glucose tolerance and cardiovascular disease: the possible
role of post-prandial hyperglycemia. Am. Heart J. 147, 803–807 (2004).
26. Hanson, K. M. et al. Two-photon fluorescence lifetime imaging of the skin
stratum corneum pH gradient. Biophys. J. 83, 1682–1690 (2002).
27. Segre, J. A. Epidermal barrier formation and recovery in skin disorders.
J. Clin. Invest. 116, 1150–1158 (2006).
28. Matsui, T. & Amagai, M. Dissecting the formation, structure and barrier
function of the stratum corneum. Int. Immunol. 27, 269–280 (2015).
Nature Biotechnology | VOL 37 | APRIL 2019 | 382–388 | www.nature.com/naturebiotechnology
Perspective | FOCUS
NaTuRe BiOTechnOlOGy
29. Kubo, A., Nagao, K. & Amagai, M. Epidermal barrier dysfunction and
cutaneous sensitization in atopic diseases. J. Clin. Invest. 122, 440–447 (2012).
30. Tsukita, S., Furuse, M. & Itoh, M. Multifunctional strands in tight junctions.
Nat. Rev. Mol. Cell Biol. 2, 285–293 (2001).
31. Candi, E., Schmidt, R. & Melino, G. The cornified envelope: a model of cell
death in the skin. Nat. Rev. Mol. Cell Biol. 6, 328–340 (2005).
32. Manabe, M., Sanchez, M., Sun, T. T. & Dale, B. A. Interaction of filaggrin
with keratin filaments during advanced stages of normal human epidermal
differentiation and in ichthyosis vulgaris. Differentiation 48, 43–50 (1991).
33. Bouwstra, J. A. et al. Water distribution and related morphology in human
stratum corneum at different hydration levels. J. Invest. Dermatol. 120,
750–758 (2003).
34. Kubo, A. et al. The stratum corneum comprises three layers with distinct
metal-ion barrier properties. Sci. Rep. 3, 1731 (2013).
35. Yoshida, K. et al. Functional tight junction barrier localizes in the second
layer of the stratum granulosum of human epidermis. J. Dermatol. Sci. 71,
89–99 (2013).
36. Van Itallie, C. M. & Anderson, J. M. Architecture of tight junctions
and principles of molecular composition. Semin. Cell Dev. Biol. 36,
157–165 (2014).
37. Yokouchi, M. et al. Epidermal cell turnover across tight junctions based on
Kelvin’s tetrakaidecahedron cell shape. Elife 5, e19593 (2016).
38. Nagao, K. et al. Stress-induced production of chemokines by hair follicles
regulates the trafficking of dendritic cells in skin. Nat. Immunol. 13,
744–752 (2012).
39. Thyssen, J. P. & Menné, T. Metal allergy—a review on exposures, penetration,
genetics, prevalence, and clinical implications. Chem. Res. Toxicol. 23,
309–318 (2010).
40. Winston, F. K. & Yan, A. C. Wearable health device dermatitis: a case of
acrylate-related contact allergy. Cutis 100, 97–99 (2017).
41. European Task Force on Atopic Dermatitis. Severity scoring of atopic
dermatitis: the SCORAD index. Consensus report of the European Task Force
on Atopic Dermatitis. Dermatology 186, 23–31 (1993).
42. Hanifin, J. M. et al. EASI Evaluator Group. The eczema area and severity
index (EASI): assessment of reliability in atopic dermatitis. Exp. Dermatol. 10,
11–18 (2001).
43. Zucca, A. et al. Roll to roll processing of ultraconformable conducting
polymer nanosheets. J. Mater. Chem. C 3, 6539–6548 (2015).
44. Imani, S. et al. A wearable chemical-electrophysiological hybrid biosensing
system for real-time health and fitness monitoring. Nat. Commun. 7,
11650 (2016).
45. Kaltenbrunner, M. et al. An ultra-lightweight design for imperceptible plastic
electronics. Nature 499, 458–463 (2013).
46. Wang, S. et al. Skin electronics from scalable fabrication of an intrinsically
stretchable transistor array. Nature 555, 83–88 (2018).
47. Oh, J. Y. et al. Intrinsically stretchable and healable semiconducting polymer
for organic transistors. Nature 539, 411–415 (2016).
48. Xu, J. et al. Highly stretchable polymer semiconductor films through the
nanoconfinement effect. Science 355, 59–64 (2017).
49. Miyamoto, A. et al. Inflammation-free, gas-permeable, lightweight,
stretchable on-skin electronics with nanomeshes. Nat. Nanotechnol. 12,
907–913 (2017).
50. Liu, Y., Pharr, M. & Salvatore, G. A. Lab-on-skin: a review of flexible and
stretchable electronics for wearable health monitoring. ACS Nano 11,
9614–9635 (2017).
51. Someya, T., Bao, Z. & Malliaras, G. G. The rise of plastic bioelectronics.
Nature 540, 379–385 (2016).
52. Khan, Y., Ostfeld, A. E., Lochner, C. M., Pierre, A. & Arias, A. C. Monitoring
of vital signs with flexible and wearable medical devices. Adv. Mater. 28,
4373–4395 (2016).
53. Choi, S., Lee, H., Ghaffari, R., Hyeon, T. & Kim, D. H. Recent advances in
flexible and stretchable bio-electronic devices integrated with nanomaterials.
Adv. Mater. 28, 4203–4218 (2016).
54. An, B. W. et al. Stretchable, transparent electrodes as wearable heaters using
nanotrough networks of metallic glasses with superior mechanical properties
and thermal stability. Nano Lett. 16, 471–478 (2016).
55. Kim, J. et al. Ultrathin quantum dot display integrated with wearable
electronics. Adv. Mater. 29, 1700217 (2017).
56. Majid, A. Electroceuticals (Springer, 2017).
57. Famm, K., Litt, B., Tracey, K. J., Boyden, E. S. & Slaoui, M. A jump-start for
electroceuticals. Nature 496, 159–161 (2013).
58. Osborn, L. E. et al. Prosthesis with neuromorphic multilayered e-dermis
perceives touch and pain. Sci. Robot. 3, eaat3818 (2018).
59. Kim, Y. et al. A bioinspired flexible organic artificial afferent nerve. Science
360, 998–1003 (2018).
60. Hwang, X. et al. Epidermal radio frequency electronics for wireless power
transfer. Microsyst. Nanoeng. 2, 16052 (2016).
61. Kim, J. et al. Battery-free, stretchable optoelectronic systems for wireless
optical characterization of the skin. Sci. Adv. 2, e1600418 (2016).
62. Xu, S. et al. Stretchable batteries with self-similar serpentine interconnects
and integrated wireless recharging systems. Nat. Commun. 4, 1543 (2013).
63. Fu, K. K., Cheng, J., Li, T. & Hu, L. Flexible batteries: from mechanics to
devices. ACS Energy Lett. 1, 1065–1079 (2016).
64. Lanata, A., Guidi, A., Baragli, P., Valenza, G. & Scilingo, E. P. A novel
algorithm for movement artifact removal in ECG signals acquired from
wearable systems applied to horses. PLoS One 10, e0140783 (2015).
65. Jarchi, D. & Casson, A. J. Description of a database containing wrist PPG
signals recorded during physical exercise with both accelerometer and
gyroscope measures of motion. Data (Basel) 2, (1 (2017).
66. Norton, J. J. S. et al. Soft, curved electrode systems capable of integration on
the auricle as a persistent brain-computer interface. Proc. Natl Acad. Sci. USA
112, 3920–3925 (2015).
67. Debener, S., Emkes, R., De Vos, M. & Bleichner, M. Unobtrusive ambulatory
EEG using a smartphone and flexible printed electrodes around the ear. Sci.
Rep. 5, 16743 (2015).
68. Becker, D. E. Fundamentals of electrocardiography interpretation. Anesth.
Prog. 53, 53–63, quiz 64 (2006).
69. Liu, Y. et al. Epidermal mechano-acoustic sensing electronics for
cardiovascular diagnostics and human-machine interfaces. Sci. Adv. 2,
e1601185 (2016).
70. Nazmi, N. et al. A review of classification techniques of EMG signals during
isotonic and isometric contractions. Sensors (Basel) 16, (1304 (2016).
71. Lotharius, J. & Brundin, P. Pathogenesis of Parkinson’s disease: dopamine,
vesicles and alpha-synuclein. Nat. Rev. Neurosci. 3, 932–942 (2002).
72. Son, D. et al. Multifunctional wearable devices for diagnosis and therapy of
movement disorders. Nat. Nanotechnol. 9, 397–404 (2014).
73. Araci, I. E., Su, B., Quake, S. R. & Mandel, Y. An implantable microfluidic device
for self-monitoring of intraocular pressure. Nat. Med. 20, 1074–1078 (2014).
74. Kim, J. et al. Wearable smart sensor systems integrated on soft contact lenses
for wireless ocular diagnostics. Nat. Commun. 8, 14997 (2017).
75. Yokota, T. et al. Ultraflexible, large-area, physiological temperature sensors for
multipoint measurements. Proc. Natl Acad. Sci. USA 112, 14533–14538 (2015).
76. Jia, W. et al. Electrochemical tattoo biosensors for real-time noninvasive
lactate monitoring in human perspiration. Anal. Chem. 85, 6553–6560 (2013).
77. Emaminejad, S. et al. Autonomous sweat extraction and analysis applied to
cystic fibrosis and glucose monitoring using a fully integrated wearable
platform. Proc. Natl Acad. Sci. USA 114, 4625–4630 (2017).
The authors thank H. Lee, H. Kawasaki and T. Ebihara for fruitful discussions.
Competing interests
The authors declare no competing interests.
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