Skin-Integrated Electromechanical Systems for Characterization of Deep Tissue Biomechanics

Compact electronic systems that perform rapid, precise mechanical characterization of living biological tissues have important potential uses in monitoring and diagnosing various types of human-health disorders. Active devices that perform high-precision, real-time evaluations of deep tissue structures (millimeter-scale) in a precise, digital and non-invasive fashion could complement capabilities of recently-reported approaches for sensing tissue biomechanics at supercial depths (typically micrometer-scale). This paper introduces a miniature electromagnetic platform that combines a vibratory actuator with a soft strain-sensing sheet for determining the Young’s modulus of soft biological tissues, with specic focus on skin. Experimental and computational studies establish the operational principles and performance attributes through evaluations of synthetic and biological materials, including human skin at various body locations across healthy subject volunteers. The results demonstrate dynamic monitoring of elastic modulus at characteristic depths between ~1 and ~8 mm, depending on the sensor designs. Arrays of such devices support capabilities in both depth proling and spatial mapping. Clinical studies on patients with skin disorders highlight potential for accurate targeting of lesions associated with psoriasis, as examples of practical medical utility.


Introduction
Technologies for rapid, in vivo assessments of soft tissue biomechanics have potential for broad utility in biological research and clinical diagnostics 1,2 . Of particular interest are advanced electromechanical systems that enable precise measurements of mechanical properties of tissues 3 that can provide diagnostic utility, track response to treatment and evaluate for small but clinically meaningful deterioriation for a wide range of dermatological conditions. For example, characterization of soft tissue biomechanics may guide objective assessment of disease severity for edema associated with lower venous leg disorders 4 or scleroderma, a lethal rheumatological and dermatological disease that currently depends on subjective physician grading scales 5 . An important focus is on the elastic modulus (the relationship between strain and stress), as the basis for dermatological evaluations of these diseases 1 .
Additional possibilities are in tracking of wound healing cascades and in tissue growth, regeneration and aging, each of which involves changes in the elastic modulus of the surface and/or sub-surface layers [6][7][8][9] .
Conventional methods for characterization rely on quasi-static measurements of displacement as a function of applied forces delivered via suction, torsion, compression or indentation [10][11][12][13][14][15] . An alternative known as magnetic resonance elastography (MRE) provides quantitative measurements of elastic modulus, including spatial-temporal mapping of tissue stiffness 16,17 . Although useful in many scenarios, these techniques usually involve elaborate setups and trained practitioners, as barriers to use outside of hospital and laboratory settings. Also, in many cases, the required tissue interfaces can lead to measurement uncertainties and di culties in mounting on curved or textured surfaces to track timedependent changes in mechanical properties.
Due to their miniature dimensions and skin-compatible formats, emerging classes of bio-integrated electronic platforms may offer powerful alternatives 18,19 . Recent research establishes the use of thin, exible piezoelectric actuators and/or sensors for characterization of soft tissue biomechanics, with measurements that rely on minute deformations of tissues at near-surface regions. Examples range from conformal sheets for high-resolution mapping of the elastic modulus near the surfaces of skin lesions 20 , to needle-shaped penetrating probes for in vivo mechanical sensing as guidance in biopsies 21 , and to thin, exible piezoresistive cantilevers as indentation sensors for mechanical characterization of cancerous breast tissues 3 . These and other related platforms differ from past technologies in their thin, exible geometries and their ability to form minimally invasive interfaces to complex topographies and textures of biological surfaces [22][23][24] . An important mode of use is in locating and identifying aberrant tissues through abnormal elastic moduli that result from speci c disease states 3,20,21,25 . In many cases, however, the limited depth of sensing and the complex designs of these devices represent drawbacks that prevent uses in many important applications.
This paper presents a simple, miniature electromechanical system that can interface with biological tissues for rapid evaluations of their elastic modulus, at a range of frequencies and depths and across a variety of spatial scales, including two dimensional mapping. These devices integrate components for mechanical actuation and sensing in a single package, using certain ideas adapted from those used as the basis of skin-integrated haptic interfaces for virtual/augmented reality 26

Results And Discussion
Materials, designs, integration schemes and performance characteristics. Fig. 1a presents a schematic illustration and an image of a representative device, which we refer to as an electromechanical modulus (EMM) sensor. The stack involves (1) a top layer that generates a time-dependent Lorenz force, as the source for vibratory actuation (Fig. 1b), (2) a thin strain sensor in the form of a serpentine metal trace, as the basis for mechanical sensing (Fig. 1c) and (3) a supporting thin elastomeric layer, as a reversible, soft interface to a tissue surface. The total thickness of this example is 2.5 mm and the contacting area is ~2 cm 2 (lower inset of Fig. 1a). The fabrication begins with patterning of serpentine-shaped electrical traces as resistive strain sensors, followed by transfer printing onto a soft, exible substrate (poly(dimethylsiloxane) (PDMS), ~30 μm thick). Thin gold (Au) lines form an open mesh structure (100 nm thick) to de ne a sensing area of ~0.5 cm 2 , embedded above and below by layers of polyimide (1 μm thick), as illustrated in Figs 1c and d. A sequence of assembly steps prepares the actuator and wired connections for integration with the underlying sensor to yield a functional system. The actuator includes a nickel-coated neodymium magnet (8 mm diameter, 1.5 mm thick) on a thin polyimide disk (75 μm thick) and a copper coil (Cu, 50 μm wire diameter, 240 turns with an outer diameter of 12 mm, electrical resistance of ~70 Ohm (Yisu Electronics, Inc.)), as displayed in Fig. 1b. Detailed information appears in the Supplementary Figs 1 and 2.
As illustrated in the equivalent circuit diagram in the upper inset of Fig. 1a Fig. 1d and Supplementary Fig. 2) provides an input channel to the lock-in ampli er, to capture the amplitudes of periodic variations in the sensor resistance, as V S at the frequency of the vibration. By comparison to existing methods for sensing tissue biomechanics at super cial depths (micrometer-scale) by use of piezoelectric actuators/sensors 20,21 , these devices mechanically couple with contacting tissues through millimeter-scale thicknesses and thereby allow characterization of deep tissue biomechanics on length scales de ned by the geometry of the sensor, as described subsequently. Information on the measurement mechanism and operational principles appear in Supplementary Fig. 3.
The surface of the strain sensor allows intimate, stable interfaces to tissues of interest (i.e. forearm, Fig.  1e). Conformal contact occurs via lamination in a simple, reversible manner that enables multiple cycles of use (100×), without signi cant change in measurement accuracy ( Fig. 1e and Supplementary Fig. 4). Fig. 1f shows a device conformally mounted on the curved surface of the skin of the ngertip of a volunteer subject. As shown in Supplementary Fig. 5a, the performance remains the same, to within experimental uncertainties, after 10 3 cycles of bending into cylindrical shapes. The encapsulation layers (polyimide/PDMS, 1 μm/30 μm thick) 27 isolate the system from moisture or bio uids. Speci cally, the devices offer consistent performance before and after 7 days of immersion in arti cial sweat solution at 50 o C ( Supplementary Fig. 5b). With the actuator mounted on top, the devices offer stable measurement results on curved surfaces with different radii of curvature ( Fig. 1g and Supplementary Fig. 6).
These simple designs and fabrication strategies yield reliable devices at high yields. Statistical data for the resistance of the strain sensor (R sensor ), the device yield and the signal-to-noise ratio (SNR) associated with 100 devices appear in Supplementary Fig. 7. The yield corresponds to the percentage of functional devices, and the SNR is the ratio between V S and the noise level with a sine wave with amplitude, V A , of 5V at a frequency, f, of 50 Hz in the top actuator, during measurements. Failure most typically results from fractures in the strain sensor or from disconnections between the wires of the coil in the actuator.
These results suggest high levels of uniformity and consistency in device performance (e.g. R sensor ~10 3 Ohm, total yield 96 % and SNR ~ 40 dB). Although this system can apply to a range of biological tissues, the results reported here focus on human skin through studies of healthy volunteers (Fig. 1g) and patients associated with a dermatology clinic, on various body locations, including curved surfaces of the face, forearm, shoulder, etc ( Supplementary Fig. 8).
Experimental and computational analysis of the device operation.  Supplementary Fig. 9). Here, samples with high modulus lead to low strain, and therefore low V S , in agreement with FEA results in Fig. 2a. An important engineering consideration is that the coil can create electromagnetic induction effects on the sensor during measurements, thus generating some cross-talk with V S at high frequency (~10 μV at 1000 Hz with V A of 5 V, see details in Supplementary Fig.   11). This consideration favors low frequency (<100 Hz) operation, where such inductive effects induce voltages that are approximately two orders of magnitude lower than those associated with the sensor signals. Unless otherwise stated, the following studies use a xed f (e.g. 50 Hz) and V A (5V). Samples with moduli less than 500 kPa (red in Fig. 2e) are of particular interest because they are most relevant to many soft biological tissues, also with high sensitivity to output V S (Fig. 2f). The experimentally measured (symbols) and FEA-simulated (lines) V S vary consistently with modulus from 10 kPa to 500 kPa. Here, increasing the thickness also increases V S , mostly due to the decreasing effects of the rigid support (glass wafer) in limiting the deformations.  Measurements on hydrogels, and on porcine and human skin. The EMM sensor can characterize the mechanical properties of a range of biomaterials and skin regions both ex vivo and in vivo ( Figure 3). Recent research shows that hydrogels (poly(ethylene-glycol) diacrylate, Sigma-Aldrich) at different levels of hydration (water concentration) have Young's moduli that span those associated with most soft biological tissues in animal models and human subjects [28][29][30] . Fig. 3a presents results from samples with various levels of hydration, at thicknesses of ~4 mm (inset of Fig. 3a). V S increases with hydration from shows that the noise decreases with the square root of averaging time for an individual measurement (i.e. integration time, t; the duration of a measurement operation that yields the value of V S ). As an example, increasing the integration time from 1 ms to 10 s decreases the noise from ~1 μV to ~10 -2 μV, approximately two orders of magnitude smaller than the signal.
The measurements determine the average elastic modulus of the skin to a characteristic depth of ~8 mm, as previously demonstrated in Fig. 2g. Each location in Fig. 3e includes the skin, super cial fat, underlying muscle tissues, etc, with a total tissue thickness that exceeds this characteristic depth [31][32][33] . Measurements of elastic modulus at different locations on the body from ten healthy volunteer subjects with ages between 25-32 years and ten with ages between 60-68 years are in Fig. 3g (determination of modulus values rely on results in Supplementary Fig. 12). The results lie within expected values for human skin and ex vivo biomaterials determined in the small strain regime using techniques based on suction 11,12 , torsion 13 and indentation 10 . The devices operate well on both hair bearing and hairless areas of the skin (Supplementary Fig. 14). Bending around curved surfaces induces only minor changes in the results ( Supplementary Fig. 6). Consistent with expectation and recent reports 2 , the moduli increase with age, typically due to a loss in hydration 34 , in accordance with Figs. 3b and d. Detailed information for these clinical tests appears in SI Appendix. The modulus can also depend on the tension in the skin due to non-linear mechanical responses associated with collagen and elastin bers in the dermis 35 . The tension typically decreases with increasing age 2 , thereby reducing the apparent modulus 36 .
Muscle activity can also affect the moduli measured across depths associated with the devices reported here. An example in Fig. 3h shows a device on the forearm in a relaxed state and in a tensed condition due to lifting a dumbbell. Repetitive cycles of movements during real-time recordings of V S yield moduli values that vary continuously between minimum and maximum values of 205 kPa and 320 kPa, respectively (details of dynamic measurements appear in Methods). These values correspond to average moduli of the skin and underlying muscles to a characteristic depth of ~8 mm. Recent studies based on ultrasound elastography methods 37 report muscle moduli that exhibit a similar trend (e.g. the modulus of biceps muscles increases by ~100 kPa due to contraction) 38,39 . Such capabilities may support various applications in kinesiology and rehabilitation.
Results obtained from patients with skin diseases in clinical settings appear in Figure 4. These measurements reveal localized variations in skin modulus associated with lesions. A tissue-phantom model ( Supplementary Fig. 15) for this case combines a low modulus silicone substrate (8 mm Fig. 17). As expected, the lesions (black frames, Figure 4) exhibit higher moduli than those of nearby skin, due primarily to differences in skin elasticity and hydration 42 . These rapid (~1 min), simple measurements have potential clinical signi cance in rapidly identifying and targeting of skin lesions, with quantitative metrics that have promise as diagnostic biomarkers for a range of skin conditions.
Miniaturized designs for multilayer biological targets. In addition to measuring elastic modulus to relatively large depths (over 8 mm), the lateral dimensions of the devices can be reduced, in a manner guided by computational modeling, to reduce these depths to values approaching those of the dermis (~1 mm). As an example, Fig. 5a summarizes devices that have sensing areas (surface area of the magnet) with diameters (D) from 8 mm to 1.5 mm, all with magnets that have the same thickness (1.5 mm). Here, reducing D decreases the contacting area between the device and sensor, and therefore lead to decreases in V S for a given f (50 Hz) and V A (5 V). Fig. 5c shows the cross-sectional strain distributions obtained by FEA in a su ciently thick tissue with elastic modulus of 200 kPa, subjected to pressure on the surface from devices with different D. The distributions exhibit saturation depths (red lines in Fig. 5c) that decrease with D (i.e. ~8.2 mm for D= 8 mm, ~3.3 mm for D= 3 mm and ~1.6 mm for D= 1.5 mm), consistent with experimental results (Fig. 2g and Supplementary Fig. 18). The results suggest the basis for depth pro ling of the modulus, of relevance for many types of biological tissues. For skin, the stratum corneum, epidermis and upper dermis (typically 1~2 mm thick) serve as protective barriers against environmental hazards for subcutaneous tissues that consist of super cial fat and connective muscles over bones. These layers exhibit different moduli and thicknesses. Fig. 5d  The intersection of these two curves thus determines the calculated modulus for each layer, as 198 kPa and 52 kPa for E A and E B (Fig. 5f), respectively, which are in excellent agreement (within 5 % error) with the moduli of the sample in Fig. 5d.
To showcase this multilayer capability in clinical practice, Fig. 5g summarizes the results of moduli measured on the cheek areas and ngertip joint (near the nail plate) in human subjects (details appear in Supplementary Fig. 19). As an example of the former, literature reports indicate that the combined thickness of the epidermis and dermis is ~1.8 mm in the cheek region 43 , and that other tissues (i.e. super cial fat and muscle) appear beneath the dermis. Measurements using devices with D of 3 mm and of 1.5 mm yield V S of 28.7 μV and 19.3 μV on cheek, respectively. By utilizing the simulation curves of V S for both cases from Fig. 5e and locating the intersection point as in Supplementary Fig. 19a, the cheek moduli are (1) 248 kPa for the skin layer with thickness of 1.8 mm; and (2) 59 kPa for inner tissues (blue in Fig. 5g). These measured moduli are consistent with values reported for the cheek region 44 and associated super cial fat in human subjects 45 .
In addition to body areas such as the cheek with comparatively large tissue thicknesses, measurements on regions where bones lie near the surface (e.g. hand joints, ngertip dorsum, etc), where the tissue structure is thin, are of particular interest in clinical diagnosis and treatment of dermal pathologies such as scleroderma 5 . As an example, consider a simple estimate of the combined thickness of skin and tissues (~3 mm; ~2 mm for the skin and ~1 mm for the underlying tissues) in the ngertip joint near the nail plate for a volunteer subject (Supplementary Fig. 20) 46,47 . Measurements with EMM sensors yield V S of 27.1 μV (D = 3 mm) and 18.2 μV (D = 1.5 mm), corresponding to modulus values of (1) 316 kPa for the skin layer, and (2) 67 kPa for inner tissues at this region of the body (red in Figure 5G and Supplementary   Fig. 19b). These results agree with those determined using conventional approaches 45,48 . These ndings demonstrate that a combined set of EMM sensors with appropriate D allow modulus characterization for multilayer biological targets with different thicknesses, across a wide range that involves not only bulk geometries (deep tissue scale) but also near-surface regions (super cial depth).
Interconnected arrays of devices for spatial mapping of modulus. Multiple EMM sensors can be used separately, as described above, or they can be con gured into arrays, as show in Figure 6. Here, Fig. 6a presents a photograph of a collection of strain sensors printed onto a polymer substrate before interconnection (fabrication procedures appear in Methods), highlighting mechanical exibility ( Supplementary Fig. 21) for wrapping areas of interest across the body, as shown on the back in Fig. 6b (volunteer subject, age of 32, male). Fig. 6c presents a schematic illustration of a 4 × 4 array of this type (4 columns, 4 rows, area of ~100 cm 2 , thickness of system as ~2.5 mm) after assembly of vibratory actuators ( Supplementary Fig. 22). Fig. 6d summarizes an equivalent circuit diagram of the system. Interconnection to multiplexers allows rapid readout of signals from each unit cell in a time sequence controlled by a data acquisition (DAQ) system that features a minimal number of addressing wires, with capabilities for de ning the frequencies and amplitudes of input voltages to each EMM sensor via a function generator (Tektronix) as a power supply (Supplementary Fig. 23). Details appear in Methods.
The resulting multiplexed system can perform fast mapping of elastic modulus on curved, soft surfaces of tissues under quasi-static conditions. As an example, Fig. 6e shows results from measurements of elastic modulus across the back (Fig. 6b) during relaxed (left) and tensed states (right) associated with muscle contraction. Here, the actuator array (50 Hz; 5 V, Sine-wave) produces signals from the underlying sensor array. Each unit cell corresponds to an elastic modulus value determined from an individual EMM sensor with a corresponding spatial resolution of ~1.5 cm 2 . Stretching the trapezius muscle (red frame in Fig. 6e) of the back in the tensed condition (right of Fig. 6e) leads to spatial variations of increased modulus associated with activation of this targeted muscle group. Speci cally, the average modulus for the tensed condition corresponds to ~430 kPa, compared to ~310 kPa for relaxed state, consistent with expectation and recent literature 49 .

Outlook
In summary, the results reported here establish the materials, device designs and integration schemes for a bio-integrated electromechanical system that can perform accurate, mechanical characterization of biological tissues in a non-invasive, rapid fashion. Detailed experimental and simulated investigations highlight the various features of device operation with a wide range of soft biomaterials and multilayer samples, and at various locations across human body under different conditions. Careful selection of device designs and integration of arrays of sensors support evaluations of depth dependent properties and spatial mapping, respectively. The ndings presented here have potential as the basis for routine monitoring of variations in elastic modulus for diagnosis and treatment of various disease states, applicable to nearly all parts of human body. Particularly promising opportunities are dermatology, where the data produced by these devices can assist in diagnosis, treatment tracking, and disease monitoring of medical dermatology, with natural extensions into aspects of aesthetic dermatology and recovery from surface wounds. Additional possibilities are in evaluating mechanical properties of the skin in a variety of physical conditions with an emphasis on age dependence 2 and the relationship between biomechanics and functionality 34 . The results may serve as predictors of potential for reactions of the skin to ageing, hydration loss and associated disorders, and further establish the role of skin in de ning health status.

Methods
Fabrication of Sheets of Strain Sensors. As shown in Supplementary Fig. 1 Fig. 5a). Fabrication of multiple sensors and repetitive transfer-printing onto a large-area layer of PDMS formed an array of such devices (Fig. 6a). Subsequent external wire connections relied on exible cables and heat seal connectors (HSCs, Elform Inc.) to printed circuit boards (PCBs) for measurements, as shown Supplementary Fig. 3.
Assembly with Vibratory Actuators. Assembly of the vibratory actuators onto these sensors completed the integration, to yield components with capabilities in measuring the elastic modulus. Procedures for assembly of the vibratory actuator exploited schemes described elsewhere 26 . Brie y, the rst step involved immersing a Cu coil (wire diameter of 50 µm, 240 turns, with an inter diameter of the coil of 2 mm and an outer diameter of 12 mm) into a layer of PDMS (diameter of 18 mm, 200 µm thick; 10:1 weight ratio of crosslinker) with the ends of the wire exposed to allow for external connection. The structure was then cured at 70 o C overnight. Next, the ring-shaped PDMS shell was cut into suitable size (inter and outer diameter of 12 mm and 18 mm, 2.4 mm thick) and then bonded onto the coil/PDMS structure via a commercial adhesive (Kwik-Sil, World Precision Instruments). In parallel, a nickel-coated neodymium magnet (8 mm diameter, 1.5 mm thick) mounted on the center of a polyimide disk (18 mm diameter, 75 µm thick) with a strong dual-side adhesive (Kapton, DuPont). Carefully aligning the coil/PDMS ring and magnet/polyimide disk yielded a vibratory actuator, bonded together with a silicone adhesive applied on the contacting area (Kwik-Sil, World Precision Instruments). The nal step involved deposition of a layer of SiO 2 (electron-beam evaporation, 100 nm thick) on the bottom surface of a polyimide disk across only a ring-shaped area (Fig. 1a). UVO treatment of the bottom surfaces of the actuator (polyimide-disk side) and the top surfaces of the fabricated sensor led to a strong bonding interface upon contact, to complete the assembly of the actuator and sensor. In this manner, the magnet of the actuator can vibrate in an out-of-plane direction in the ring-shaped PDMS shell, yielding pressure on the contacting tissue. Here, suction effects can be neglected due to the absence of a bonding interface between the sensing area of polyimide disk and strain sensor. The resulting overall system can directly laminate onto curved surfaces in an intimate contact, with stable measurements, as shown in Electromagnetic induction effect. During the measurement, alternating currents through the top coil of the actuator can induce an electromagnetic induction effect associated with the metal traces that de ne the strain sensor and the ower-shape mesh structure, thereby resulting in additional output voltage. To facilitate measurement of this induction effect, the magnet was removed from actuator during V A input into the top coil. As shown in Supplementary Fig. 11, the induced output voltages were separately measured as a function of actuation frequencies (10-10,000 Hz), while the EMM sensor without the magnet couples onto a sample of arti cial skin with elastic modulus of 200 kPa. The induced voltages remained below ~ 0.5 µV at low frequency (below 100 Hz), which were ~ 2 orders of magnitude lower than the signals. This effect increased with increasing actuation frequency, with an output voltage higher than 10 µV at 1000 Hz.  Supplementary Fig. 17. The pathological symptom included red, thick patches of skin lesion (typically over 8 mm diameter) with low hydration level across skin surface, and can be detected through physical palpations with detectable differences in skin properties such as stiffness and thickness. All of these volunteers and patients were at rest during the measurements.
After a process of cleaning pre-selected skin areas (lesion and normal) by gentle rubbing with alcohol wipes, the EMM sensors were mounted onto the relevant skin areas followed by conformal coverage with a medical dressing (Tegaderm, 3M) to secure device placement. The placement of the sensors was performed by research staff and/or medical doctors. The EMM sensors were pre-connected to a DAQ system (including a locking-in ampli er and a current source) located within the operational room. Data recording began after 10 s of system warm-up, to ensure stable operation. Each subject performed 1-min measurement in a resting position. Data were collected and stored for further data analysis on a tablet computer. Similar to the operation on patients, a corresponding measurement that simulated clinical tests on a tissue-phantom model appears in Supplementary Fig. 15.
Operation for Multiplexed Arrays of EMM Sensors. Fabrication of multiple strain sensors and repetitive transfer-printing onto a large-area layer of PDMS form an array of sensors ( Supplementary Fig. 21) and electronic interconnects based on exible, lightweight conductive cables (heat seal connectors (HSCs), Elform Inc.). Connection to an external multiplexing board allow for an interface to a 4:1 multiplexer that enables readout from each sensor at a time, as controlled via a back-end DAQ system. Assemblies of actuators aligned with the strain sensor array yielded the complete mapping systems ( Supplementary   Fig. 22).
Operation of the multiplexed array of EMM sensors appears in Supplementary Fig. 23. During measurements, all of the actuators are connected for vibration at a speci c frequency (f) and amplitude of input voltage. The setup for spatial mapping of the skin modulus used a function generator (Tektronix) to produce a sine-wave power input with preprogrammed frequency and amplitude, delivered through the interface board to certain actuators in the mapping system. For the strain sensor array, a current source connected through the interface board to a multiplexer delivered current to a certain sensor in the system.