Skin-inspired, sensory robots for electronic implants

Abstract

Drawing inspiration from cohesive integration of skeletal muscles and sensory skins in vertebrate animals, we present a design strategy of soft robots, primarily consisting of an electronic skin (e-skin) and an artificial muscle. These robots integrate multifunctional sensing and on-demand actuation into a biocompatible platform using an in-situ solution-based method. They feature biomimetic designs that enable adaptive motions and stress-free contact with tissues, supported by a battery-free wireless module for untethered operation. Demonstrations range from a robotic cuff for detecting blood pressure, to a robotic gripper for tracking bladder volume, an ingestible robot for pH sensing and on-site drug delivery, and a robotic patch for quantifying cardiac function and delivering electrotherapy, highlighting the application versatilities and potentials of the bio-inspired soft robots. Our designs establish a universal strategy with a broad range of sensing and responsive materials, to form integrated soft robots for medical technology and beyond.

Fig. 1. Schematic illustration showing bio-inspired sensory robots as minimally invasive smart implants for diagnosis, stimulation, and drug delivery.

A A robotic cuff for vascular system. The twisting motion provides physical enclosing around a blood vessel for precise detection of blood pressure and structural support. B A robotic patch for epicardial interface. The gripping motion enables gentle contact with a beating heart without residual straining, to provide real-time quantification of cardiac contractility and temperature, and electrotherapy. C An ingestible robot for digestive system. This structural transition from the shape of a miniaturized pill to a 3D expanded hoop enables extended stay inside stomach to provide both pH sensing and drug delivery. D A robotic gripper for bladder control. The adaptive motion of gripping onto a bladder provides precise tracking of bladder volume and targeted stimulation for treating urological disorders.

Fig. 2. Multi-materials Integration for Multi-modal Sensory Soft Robot.

A Schematic illustration of epidermis-dermis-muscle structure of skin. B Bio-inspired structure of soft robot from skin. C Conceptual illustration of the integrated multi-modal sensory soft robot with distinct nanocomposite sensors functionalized into each arm. D Schematic illustration of a starfish-inspired multi-modal sensory soft robot. Left: An exploded view highlighting 3 primary constituent layers, including a flexible multi-modal layer, a bio-adhesive layer, and an actuation hydrogel layer. Right: Schematic illustration highlighting the multi-material integration within the multi-modal layer including: (i) Silver nanowires (AgNWs) and polyimide (PI) as a flexible heater; (ii) AgNWs and PDMS as a strain sensor; (iii) Reduced graphene oxide (RGO) and PI as a temperature sensor; (iv) Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) and PI as sensing and stimulation electrodes. E Optical image of the flexible e-skin with six nanocomposite sensors. Optical image showing conformal attachment of the soft sensory robot onto human skin (F) and porcine tissue (G) with high mechanical compliance. H Top: Schematic showing a temperature-responsive bending from a bilayer of poly(N-isopropylacrylamide) (PNIPAM) and polyimide-based nanocomposite. Bottom: Volumetric shrinkage of PNIPAM across a temperature range of 25–60 °C. The data points represent the mean value from n = 3 independent experiments, and the error bars are in S.D. I–K Optical images and corresponding finite element modeling of thermal-triggered structural reconfiguration of soft robots. Colors indicate von Mises stress magnitude. I Biomimicry soft gripper encloses upon heating at 40 °C. J Chiral seedpod-inspired robot reverses helix at 40 °C. K Soft robotic pill expands upon heating at 40 °C. L, M Schematic and optical images of anisotropic integration of various functional materials into a polymeric matrix to form a multi-modal sensing system using an in situ solution-based approach. L A RGO/PI-based temperature sensor and an AgNW/PI-based heater on the same polyimide side. M PEDOT:PSS/PI-based electrodes and RGO/PI temperature sensors integrated on the two opposite sides of a PI layer, respectively. Scale bars, 5 mm.

Fig. 3. Anisotropic integration of nanocomposites for on-demand robotic actuation with spatiotemporal control.

Illustration of an exploded view (A) and optical image (B) of a soft robotic arm comprising a PNIPAM hydrogel layer, a RGO/PI thermal sensor, and an AgNW/PI actuation heater, bonded using n-butyl cyanoacrylate adhesive. Joule heating from the AgNW/PI heater triggers bending of the robotic arm. Scale bar, 5 mm. C, D SEM images of nanocomposite film surfaces. Here, deep reactive ion etching (DRIE) of partial regions reveals the anisotropic integration within the films, distinguishing pristine PI from AgNW/PI (C) and RGO/PI regions (D). AgNWs and RGO, with higher surface-free energy than PI, are uniformly dispersed inside the PI matrix, enhancing wetting and binding properties. Scale bars, (C) 1.5 μm, (D) 10 μm. E Infrared thermograph of an AgNW/PI heater demonstrating consistent heating performance even after 1000 bending and twisting cycles. F Surface temperature of this heater varies with input electric power, functioning efficiently at low power. G The bending angle of a soft robotic arm changes with varying input electric power. H Resistive response of the RGO/PI thermal sensor during bending, twisting, and PBS immersion, across temperatures from 23 °C to 92 °C. Data points represent mean values from n = 3 independent experiments, error bars in S.D. I Static cycling test of the RGO/PI thermal sensor. Here, the left y-axis represents resistance changes, while the right y-axis shows corresponding temperature changes. J Resistive response of an MXene-based thermal sensor across temperatures from 23 °C to 55 °C. K Temperature measurement comparison between the MXene/PI thermal sensor and a commercial thermal resistor (ERT-J0ET102H). L Stepwise coiling actuation of a soft robotic probe via sequential thermal stimulus. Top shows infrared thermograph and bottom shows structural changes from a flat to coiled state. Scale bars, 10 mm. M Integrated RGO/PI thermal sensors enable temperature measurement of localized regions for proprioceptive sensing. N Optical images demonstrating on-demand motion control of a three-arm soft robotic gripper via sequentially programming input power. Scale bars, 5 mm. 3 measurements are repeated with similar results to (C), (D), (I), (J), (K), (L).

Fig. 4. Design and construction of a soft sensory robot for wireless sensing and actuation.

A Schematic of a soft sensory robot featuring an electrical heater, a polyacrylamide (PAAm)-based pressure sensor, and two inductive coils for transmission sensing signals (B) and electrical power (C). B Exploded view of the sensing components containing a capacitor with two electrodes, a PAAm-hydrogel dielectric layer, and a copper (Cu) inductive communication coil. C Exploded view of actuation components consisting of a PNIPAM actuation hydrogel, a flexible electrical heater, and a radiofrequency (RF) power harvester based on a copper coil. D Equivalent circuit diagram of wireless pressure sensing, where pressure variations alter the capacitance and, thus, resonance frequency which is captured wirelessly through a vector network analyzer (VNA). E Equivalent circuit diagram of wireless actuation, where a transmitting coil connected to an RF power amplifier energizes the receiving coil, powering the heater for robotic motion. F Measured capacitive change of the PAAm-based pressure sensor in response to applied pressure. G Measured shift of resonance curves of the PAAm-based pressure sensor in response to applied pressure. H Change of the LC resonant frequency as a function of applied pressure serving as a signal-transduction scheme for wireless pressure detection. I Thermal distribution during wirelessly harvesting energy exhibits minimal heating in the receiving coil and efficient power consumed by the electrical heater, ensuring minimal heat damage to surrounding bio-environments. J Optical images of a soft sensory robot undergoing a wireless actuation to transform from a flat state to a bent state. K The output power as a function of frequency, optimized at ~15 MHz. L The output electrical power varies with the input power. M The temperature change of the electrical heater over time under various output powers used for wireless actuation. N Optical images of the deformed RF coils including bending, twisting, and distorting. O Measured resonance frequency of RF coil under various shape deformations. Here the bending angle θ is 60^o. Scale bars, 5 mm. Data are presented (F), (K), (L) from n = 3 independent experiments, and the error bars are in S.D.

Fig. 5. Soft sensory robots interfacing with various internal organs.

A A fully implantable, soft robotic gripper precisely measuring bladder volume and providing electrical stimulation through wireless closed-loop control. B The control platform including a wireless power harvesting network, a full bridge amplifier, a voltage regulator, and signal conditioning circuits integrated with a Bluetooth System-on-Chip, and a MOSFET switch. C Block diagram for the bladder stimulation module. D A soft robotic gripper deployed onto an artificial bladder, demonstrating deflation and inflation cycles. E Measured resistive characteristics of the buckled strain sensor on the artificial bladder correlated with volume changes. F The 3D buckling strain sensor monitoring real-time volumetric changes during cyclic bladder operations, with resistance and volume changes displayed on dual axes. G Programmed electrical stimulation (top) and measured volume of an artificial bladder (middle and bottom). This demonstration is conducted using a volume threshold of ~100 mL, and amplitude of 3 V. A slight delay in the deactivation process could be attributed to the microcontroller unit’s response time. H A soft robotic cuff enclosing around a blood vessel for monitoring blood pressure. I Optical image of the cuff on an artificial vessel stimulating blood circulation. J Measured resistive changes of the strain sensor at various simulated blood pressures. K Fluidic pressure measurement in an artificial artery system using the soft robotic cuff, displaying resistance changes on the left y-axis and pressure changes on the right y-axis. L A soft ingestible robot designed for continuous stomach pH monitoring and extended drug delivery. M Optical images showing the robot entering, expanding and blocking in the stomach. N Electrical response of PEDOT:PSS/PVA hydrogel to pH change ranging from 3 to 7 over time, with resistance on the left y-axis and pH changes on the right y-axis. O Rhodamine-B embedded into the poly lactic-co-glycolic acid (PLGA) matrix to form a drug delivery patch concealed inside the robot. Its release is measured by UV-vis absorbance over an hour at different temperatures. Scale bars, 5 mm. Data are presented (E), (J) from n = 3 independent experiments, and the error bars are in S.D.

Fig. 6. In vivo validation of a soft robotic thera-gripper for epicardial sensing and electrical stimulation (E-stim).

A Schematic illustration showing the thera-gripper features minimally invasive insertion at the resting state and wraps onto the surface of a beating heart at the actuation state. The thera-gripper contains four strain sensors made of serpentine Au/PI resistors, two E-stim electrodes based on Au, and two temperature sensors made of thermal resistors. B Finite element modeling of the actuation state. The colors in the legend indicate the magnitude of the von Mises stress. C Image of a soft robotic thera-gripper grasping on the epicardial surface of a living mouse heart. Scale bar, 5 mm. D Schematic illustration showing the thera-gripper position on a mouse heart, where the strain sensors (labeled as S1, S2, S3, and S4) are located onto different heart chambers for locally monitoring of dysfunctional tissue. E Confocal microscope images of 3T3-J-2 cells before (control) and after exposure to as-prepared soft robots integrated with an e-skin layer and a PNIPAM hydrogel-muscle layer, incubated at 37 °C and 39 °C for 48 h. Scale bars, 50 μm. F Comparative cell viability before and after soft robot’s exposure, indicating that 3T3-J-2 cells exposed with the soft robot and cultured at the elevated temperature (39 °C) have no decreased viability. Scale bars, 50 μm. Mean ± S.D. n = 3. P value by Unpaired t-test. G Temperature measurements from the thera-gripper during its deployment onto the mouse heart, demonstrate the device’s capability to monitor thermal variations in real-time. H The surface ECG trace during electrical stimulation using a pair of Au E-stim electrodes. Optical images of a healthy heart (I) and an injured heart 2 weeks after myocardial infarction (MI) (J). The MI area is shown by the white dashed circle in (J). M-mode echocardiographic images from a healthy (K) and post-MI heart (L). Representative measurements of local cardiac contractions before (M) and after MI (N) using a soft robotic thera-gripper wrapping onto a living mouse heart.