Polymer-waveguide-based flexible tactile sensor array for dynamic response

Multilevel Cu-LIG Tactile Sensing Arrays for 3D Touch Human-Machine Interaction

High-performance flexible tactile sensors have attracted significant attention in the domains of human-machine interactions. However, the efficient fabrication of sensors with highly sensitive responses over a broad load range still remains a challenge. Here, we propose a one-step laser writing route to construct a distinctive multilevel piezoresistive structure, consisting of Cu nanoparticle-doped graphene protrusions and surrounding porous Cu sheets. This multilevel structure enables the assembled tactile sensors to exhibit superior sensitivity at both low-pressure (1468 kPa-1 at 0-200 kPa) and high-pressure (1345 kPa-1 at 600-800 kPa) stimulations. Its enhancement mechanism for piezoresistive sensing has been investigated. The programmable laser writing process facilitates the development of human-machine interaction devices that recognize multidimensional gestures such as sliding, clicking, and pressing. This advancement serves to promote the development of high-performance interactive sensing technologies.

Ultra-High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

Monitoring minuscule mechanical signals, both in magnitude and direction, is imperative in many application scenarios, e.g., structural health monitoring and robotic sensing systems. However, the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix, and achieving sensitivity for detecting micrometer-scale deformations is also challenging. Herein, we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement, capable of detecting minute anisotropic deformations. The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%, thereby enabling its utility in accurately discerning the 5 μm-height wrinkles in thin films and in monitoring human pulse waves. The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase. Additionally, when integrated with machine learning techniques, the sensor's capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100% accuracy. The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli, offering a novel perspective for enhancing recognition accuracy.

Multi-Degree-of-Freedom Force Sensor Incorporated into Soft Robotic Gripper for Improved Grasping Stability

In recent years, soft robotic grippers have emerged as a promising solution for versatile and safe manipulation of objects in various fields. However, precise force control is critical, especially when handling delicate or fragile objects, to avoid excessive grip force application or to prevent object slippage. Herein, we propose a novel three-degree-of-freedom force sensor incorporated within a soft robotic gripper to realize stable grasping with force feedback. The proposed optical sensor employs lightweight and compact optical fibers, thereby allowing for cost-effective fabrication, and a robust sensing system that is immune to electromagnetic fields. By innervating the soft gripper with optical fibers, a durable system is achieved with the fibers functioning as a strengthening layer, thereby eliminating the need for embedding an external stiffening structure for efficient bending actuation. The innovative contact-based light loss sensing mechanism allows for a robust and stable sensing mechanism with low drift (<0.1% over 9000 cycles) that can be applied to soft pneumatic bending grippers. We used the developed sensor-incorporated soft gripper to grasp various objects, including magnetic materials, and achieved slip detection along with grip force feedback without any signal interference. Overall, this study proposes a robust measuring multi-degree-of-freedom force sensor that can be incorporated into grippers for improved grasping stability.

Optofluidic chip with directly printed polymer optical waveguide Mach-Zehnder interferometer sensors for label-free biodetection

Optofluidic devices hold great promise in biomedical diagnostics and testing because of their advantages of miniaturization, high sensitivity, high throughput, and high scalability. However, conventional silicon-based photonic chips suffer from complicated fabrication processes and less flexibility in functionalization, thus hindering their development of cost-effective biomedical diagnostic devices for daily tests and massive applications in responding to public health crises. In this paper, we present an optofluidic chip based on directly printed polymer optical waveguide Mach-Zehnder interferometer (MZI) sensors for label-free biomarker detection. With digital ultraviolet lithography technology, high-sensitivity asymmetric MZI microsensors based on a width-tailored optical waveguide are directly printed and vertically integrated with a microfluidic layer to make an optofluidic chip. Experimental results show that the sensitivity of the directly printed polymer optical waveguide MZI sensor is about 1695.95 nm/RIU. After being modified with capture molecules, i.e., goat anti-human immunoglobulin G (IgG), the polymer optical waveguide MZI sensors can on-chip detect human IgG at the concentration level of 1.78 pM. Such a polymer optical waveguide-based optofluidic chip has the advantages of miniaturization, cost-effectiveness, high sensitivity, and ease in functionalization and thus has great potential in the development of daily available point-of-care diagnostic and testing devices.

Laser-assisted direct roller imprinting of large-area microstructured optical surfaces

In this study, a high-throughput fabrication method called laser-assisted direct roller imprinting (LADRI) was developed to lower the cost of nanoimprinting large-area polymer films and to address problems associated with nanoimprinting, namely, microstructural damage and precision in flatness of entire film. With LADRI, the laser directly heats the microstructured surface of the roller mold, which heats and melts the surface of a polymethyl methacrylate (PMMA) film to replicate the microstructures on the mold rapidly. In this study, the effects of laser power density, scanning speed, size of the microstructures, and contact pressure on the replication speed were investigated experimentally. The replication speed increased as the power and scanning speed increased. However, because the film required heating until it filled the entire depth of the microstructure, an appropriate replication speed was necessary. This result was supported by simulation of the temperature distribution inside the mold and the PMMA using transient heat conduction analyses. To demonstrate the applications of LADRI, two different optical surfaces were replicated: an antireflection (AR) structure with conical structures sized several hundred nanometers and a light-extraction structure with a microlens array (MLA) comprising 10 μm lenses, for display and illumination, respectively. The replication degree of the MLA was governed by the contact pressure. Polymer flow simulation indicated that the heat conduction and flow speeds of the melted PMMA surface were comparable within several tens of micrometers. In addition, the reflectivity of the AR structure decreased from 4 to 0.5%, and the light intensity of the light-extraction structure increased by a factor of 1.47.

Flexible waveguide integrated thermo-optic switch based on TiO2 platform

Mechanically flexible photonic devices are critical components of novel bio-integrated optoelectronic and high-end wearable systems, in which thermo-optic switches (TOSs) as optical signal control devices are crucial. In this paper, flexible titanium oxide (TiO₂) TOSs based on a Mach-Zehnder interferometer (MZI) structure were demonstrated around 1310 nm for, it is believed, the first time. The insertion loss of flexible passive TiO₂ 2 × 2 multi-mode interferometers (MMIs) is -3.1 dB per MMI. The demonstrated flexible TOS achieves power consumption (Pπ) of 0.83 mW, compared with its rigid counterpart, for which Pπ is decreased by a factor of 18. The proposed device could withstand 100 consecutive bending operations without noticeable degradation in TOS performance, indicating excellent mechanical stability. These results provide a new perspective for designing and fabricating flexible TOSs for flexible optoelectronic systems in future emerging applications.

AI-Assisted Disease Monitoring Using Stretchable Polymer-Based Sensors

Flexible sensors have attracted significant attention for medical applications. Herein, an AI-assisted stretchable polymer-based (AISP) sensor has been developed based on the Beer-Lambert law for disease monitoring and telenursing. Benefiting from the use of superior polymer materials, the AISP sensor features a high tensile strain of up to 100%, durability of >10,000 tests, excellent waterproofness, and no effect of temperature (1.6-60.9 °C). Such advantages support the capability that the AISP can be flexibly pasted on the skin surface as a wearable device for real-time monitoring of multiple physiological parameters. An AISP sensor-based swallowing recognition technique has been proposed with a high accuracy of up to 88.89%. Likewise, it has been expanded to a remote nursing assistance system to meet critical patients' physiological requirements and daily care. The hands-free communication experiment and robot control applications have also been successfully conducted based on the constructed system. Such merits demonstrate its potential as a medical toolkit and indicate promise for intelligent healthcare.

A Review of Photonic Sensors Based on Ring Resonator Structures: Three Widely Used Platforms and Implications of Sensing Applications

Optical ring resonators (RRs) are a novel sensing device that has recently been developed for several sensing applications. In this review, RR structures based on three widely explored platforms, namely silicon-on-insulator (SOI), polymers, and plasmonics, are reviewed. The adaptability of these platforms allows for compatibility with different fabrication processes and integration with other photonic components, providing flexibility in designing and implementing various photonic devices and systems. Optical RRs are typically small, making them suitable for integration into compact photonic circuits. Their compactness allows for high device density and integration with other optical components, enabling complex and multifunctional photonic systems. RR devices realized on the plasmonic platform are highly attractive, as they offer extremely high sensitivity and a small footprint. However, the biggest challenge to overcome is the high fabrication demand related to such nanoscale devices, which limits their commercialization.

Closing the Control Loop with Time-Variant Embedded Soft Sensors and Recurrent Neural Networks

Embedded soft sensors can significantly impact the design and control of soft-bodied robots. Although there have been considerable advances in technology behind these novel sensing materials, their application in real-world tasks, especially in closed-loop control tasks, has been severely limited. This is mainly because of the challenge involved with modeling a nonlinear time-variant sensor embedded in a complex soft-bodied system. This article presents a learning-based approach for closed-loop force control with embedded soft sensors and recurrent neural networks (RNNs). We present learning protocols for training a class of RNNs called long short-term memory (LSTM) that allows us to develop accurate and robust state estimation models of these complex dynamical systems within a short period of time. Using this model, we develop a simple feedback force controller for a soft anthropomorphic finger even with significant drift and hysteresis in our feedback signal. Simulation and experimental studies are conducted to analyze the capabilities and generalizability of the control architecture. Experimentally, we are able to develop a closed-loop controller with a control frequency of 25 Hz and an average accuracy of 0.17 N. Our results indicate that current soft sensing technologies can already be used in real-world applications with the aid of machine learning techniques and an appropriate training methodology.

Application of High-Photoelasticity Polyurethane to Tactile Sensor for Robot Hands

We developed a tactile sensor for robot hands that can measure normal force (F_Z) and tangential forces (F_X and F_Y) using photoelasticity. This tactile sensor has three photodiodes and three light-emitting diode (LED) white light sources. The sensor is composed of multiple elastic materials, including a highly photoelastic polyurethane sheet, and the sensor can detect both normal and tangential forces through the deformation, ben sding, twisting, and extension of the elastic materials. The force detection utilizes the light scattering resulting from birefringence.

High-Performance Flexible Piezoresistive Pressure Sensor Printed with 3D Microstructures

Flexible pressure sensors have been widely used in health detection, robot sensing, and shape recognition. The micro-engineered design of the intermediate dielectric layer (IDL) has proven to be an effective way to optimize the performance of flexible pressure sensors. Nevertheless, the performance development of flexible pressure sensors is limited due to cost and process difficulty, prepared by inverted mold lithography. In this work, microstructured arrays printed by aerosol printing act as the IDL of the sensor. It is a facile way to prepare flexible pressure sensors with high performance, simplified processes, and reduced cost. Simultaneously, the effects of microstructure size, PDMS/MWCNTs film, microstructure height, and distance between the microstructures on the sensitivity and response time of the sensor are studied. When the microstructure size, height, and distance are 250 µm, 50 µm, and 400 µm, respectively, the sensor shows a sensitivity of 0.172 kPa^-1 with a response time of 98.2 ms and a relaxation time of 111.4 ms. Studies have proven that the microstructured dielectric layer printed by aerosol printing could replace the inverted mold technology. Additionally, applications of the designed sensor are tested, such as the finger pressing test, elbow bending test, and human squatting test, which show good performance.

PhotoElasticFinger: Robot Tactile Fingertip Based on Photoelastic Effect

The sense of touch is fundamental for a one-to-one mapping between the environment and a robot that physically interacts with the environment. Herein, we describe a tactile fingertip design that can robustly detect interaction forces given data collected from a camera. This design is based on the photoelastic effect observed in silicone matter. Under the force applied to the silicone rubber, owing to the stress-induced birefringence, the light propagating within the silicone rubber is subjected to the angular phase shift, where the latter is proportional to the increase in the image brightness in the camera frames. We present the calibration and test results of the photoelastic sensor design on a bench using a robot arm and with a certified industrial force torque sensor. We also discuss the applications of this sensor design and its potential relationship with human mechano-transduction receptors. We achieved a force sensing range of up to 8 N with a force resolution of around 0.5 N. The photoelastic tactile fingertip is suitable for robot grasping and might lead to further progress in robust tactile sensing.

Strain-ultrasensitive surface wrinkles for visual optical sensors

Wearable tactile sensors have found widespread applications in human health monitoring, motion monitoring, human-machine interactions, and artificial prostheses. Herein, we demonstrate a new and feasible strategy for wearable optical sensors based on surface wrinkles that are ultrasensitive to strain using a bilayer wrinkling system, in which the relevance between strain and the optical signal can be founded on surface wrinkles. The strain (S⃑(ε, θ_S)), the wrinkled topography (W⃑(A, θ_W)), and the reflected optical signal (O⃑(δ, θ_O)) are correlated with each other, allowing simultaneous measurement of the strain magnitude and direction due to the vector property of optical signals. In addition, interactively visualized detection of slight strain has been achieved by a conspicuous structural color change, successfully amplifying the strain signal owing to the ultra-sensitivity of wrinkles and the nonlinearity of the optical signal. The sensor also exhibits electrical safety and immunity to electromagnetic interference and thus may find potential applications in detecting various complex slight strains, such as subtle human motion or object deformation.

Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin

Collaborative robots are expected to physically interact with humans in daily living and the workplace, including industrial and healthcare settings. A key related enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic fibre Bragg grating transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A convolutional neural network deep learning algorithm and a multigrid neuron integration process were implemented to decode the fibre Bragg grating sensor outputs for inference of contact force magnitude and localization through the skin surface. Results of 35 mN (interquartile range 56 mN) and 3.2 mm (interquartile range 2.3 mm) median errors were achieved for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards artificial intelligence based integrated skins enabling safe human–robot cooperation via machine intelligence.

Bioinspired Stretchable Fiber-Based Sensor toward Intelligent Human-Machine Interactions

Wearable integrated sensing devices with flexible electronic elements exhibit enormous potential in human-machine interfaces (HMI), but they have limitations such as complex structures, poor waterproofness, and electromagnetic interference. Herein, inspired by the profile of Lindernia nummularifolia (LN), a bionic stretchable optical strain (BSOS) sensor composed of an LN-shaped optical fiber incorporated with a stretchable substrate is developed for intelligent HMI. Such a sensor enables large strain and bending angle measurements with temperature self-compensation by the intensity difference of two fiber Bragg gratings' (FBGs') center wavelength. Such configurations enable an excellent tensile strain range of up to 80%, moreover, leading to ultrasensitivity, durability (≥20,000 cycles), and waterproofness. The sensor is also capable of measuring different human activities and achieving HMI control, including immersive virtual reality, robot remote interactive control, and personal hands-free communication. Combined with the machine learning technique, gesture classification can be achieved using muscle activity signals captured from the BSOS sensor, which can be employed to obtain the motion intention of the prosthetic. These merits effectively indicate its potential as a solution for medical care HMI and show promise in smart medical and rehabilitation medicine.

Electrooculography and Tactile Perception Collaborative Interface for 3D Human-Machine Interaction

The human-machine interface (HMI) previously relied on a single perception interface that cannot realize three-dimensional (3D) interaction and convenient and accurate interaction in multiple scenes. Here, we propose a collaborative interface including electrooculography (EOG) and tactile perception for fast and accurate 3D human-machine interaction. The EOG signals are mainly used for fast, convenient, and contactless 2D (XY-axis) interaction, and the tactile sensing interface is mainly utilized for complex 2D movement control and Z-axis control in the 3D interaction. The honeycomb graphene electrodes for the EOG signal acquisition and tactile sensing array are prepared by a laser-induced process. Two pairs of ultrathin and breathable honeycomb graphene electrodes are attached around the eyes for monitoring nine different eye movements. A machine learning algorithm is designed to train and classify the nine different eye movements with an average prediction accuracy of 92.6%. Furthermore, an ultrathin (90 μm), stretchable (∼1000%), and flexible tactile sensing interface assembled by a pair of 4 × 4 planar electrode arrays is attached to the arm for 2D movement control and Z-axis interaction, which can realize single-point, multipoint and sliding touch functions. Consequently, the tactile sensing interface can achieve eight directions control and even more complex movement trajectory control. Meanwhile, the flexible and ultrathin tactile sensor exhibits an ultrahigh sensitivity of 1.428 kPa^-1 in the pressure range 0-300 Pa with long-term response stability and repeatability. Therefore, the collaboration between EOG and the tactile perception interface will play an important role in rapid and accurate 3D human-machine interaction.

Elastic Plasmonic-Enhanced Fabry-Pérot Cavities with Ultrasensitive Stretching Tunability

The emerging stretchable photonics field faces challenges, like the robust integration of optical elements into elastic matrices or the generation of large optomechanical effects. Here, the first stretchable plasmonic-enhanced and wrinkled Fabry-Pérot (FP) cavities are demonstrated, which are composed of self-embedded arrays of Au nanostructures at controlled depths into elastomer films. The novel self-embedding process is triggered by the Au nanostructures' catalytic activity, which locally increases the polymer curing rate, thereby inducing a mechanical stress that simultaneously pulls the Au nanostructures into the polymer and forms a wrinkled skin layer. This geometry yields unprecedented optomechanical effects produced by the coupling of the broad plasmonic modes of the Au nanostructures and the FP modes, which are modulated by the wrinkled optical cavity. As a result, film stretching induces drastic changes in both the spectral position and intensity of the plasmonic-enhanced FP resonances due to the simultaneous cavity thickness reduction and cavity wrinkle flattening, thus increasing the cavity finesse. These optomechanical effects are exploited to demonstrate new strain-sensing approaches, achieving a strain detection limit of 0.006%, i.e., 16-fold lower than current optical strain-detection schemes.

Recent Development of Flexible Tactile Sensors and Their Applications

With the rapid development of society in recent decades, the wearable sensor has attracted attention for motion-based health care and artificial applications. However, there are still many limitations to applying them in real life, particularly the inconvenience that comes from their large size and non-flexible systems. To solve these problems, flexible small-sized sensors that use body motion as a stimulus are studied to directly collect more accurate and diverse signals. In particular, tactile sensors are applied directly on the skin and provide input signals of motion change for the flexible reading device. This review provides information about different types of tactile sensors and their working mechanisms that are piezoresistive, piezocapacitive, piezoelectric, and triboelectric. Moreover, this review presents not only the applications of the tactile sensor in motion sensing and health care monitoring, but also their contributions in the field of artificial intelligence in recent years. Other applications, such as human behavior studies, are also suggested.

Anisotropic conductive networks for multidimensional sensing

In the past decade, flexible physical sensors have attracted great attention due to their wide applications in many emerging areas including health-monitoring, human-machine interfaces, smart robots, and entertainment. However, conventional sensors are typically designed to respond to a specific stimulus or a deformation along only one single axis, while directional tracking and accurate monitoring of complex multi-axis stimuli is more critical in practical applications. Multidimensional sensors with distinguishable signals for simultaneous detection of complex postures and movements in multiple directions are highly demanded for the development of wearable electronics. Recently, many efforts have been devoted to the design and fabrication of multidimensional sensors that are capable of distinguishing stimuli from different directions accurately. Benefiting from their unique decoupling mechanisms, anisotropic architectures have been proved to be promising structures for multidimensional sensing. This review summarizes the present state and advances of the design and preparation strategies for fabricating multidimensional sensors based on anisotropic conducting networks. The fabrication strategies of different anisotropic structures, the working mechanism of various types of multidimensional sensing and their corresponding unique applications are presented and discussed. The potential challenges faced by multidimensional sensors are revealed to provide an insightful outlook for the future development.

Smart Skin: Vision-Based Soft Pressure Sensing System for In-Home Hand Rehabilitation

We introduce a novel in-home hand rehabilitation system for monitoring hand motions and assessing grip forces of stroke patients. The overall system is composed of a sensing device and a computer vision system. The sensing device is a lightweight cylindrical object for easy grip and manipulation, which is covered by a passive sensing layer called "Smart Skin." The Smart Skin is fabricated using soft silicone elastomer, which contains embedded microchannels partially filled with colored fluid. When the Smart Skin is compressed by grip forces, the colored fluid rises and fills in the top surface display area. Then, the computer vision system captures the image of the display area through a red-green-blue camera, detects the length change of the liquid through image processing, and eventually maps the liquid length to the calibrated force for estimating the gripping force. The passive sensing mechanism of the proposed Smart Skin device works in conjunction with a single camera setup, making the system simple and easy to use, while also requiring minimum maintenance effort. Our system, on one hand, aims to support home-based rehabilitation therapy with minimal or no supervision by recording the training process and the force data, which can be automatically conveyed to physical therapists. In contrast, the therapists can also remotely instruct the patients with their training prescriptions through online videos. This study first describes the design, fabrication, and calibration of the Smart Skin, and the algorithm for image processing, and then presents experimental results from the integrated system. The Smart Skin prototype shows a relatively linear relationship between the applied force and the length change of the liquid in the range of 0-35 N. The computer vision system shows the estimation error <4% and a relatively high stability in estimation under different hand motions.

Progress in micro/nano sensors and nanoenergy for future AIoT-based smart home applications

Self-sustainable sensing systems composed of micro/nano sensors and nano-energy harvesters contribute significantly to developing the internet of things (IoT) systems. As one of the most promising IoT applications, smart home relies on implementing wireless sensor networks with miniaturized and multi-functional sensors, and distributed, reliable, and sustainable power sources, namely energy harvesters with a variety of conversion mechanisms. To extend the capabilities of IoT in the smart home, a technology fusion of IoT and artificial intelligence (AI), called the artificial intelligence of things (AIoT), enables the detection, analysis, and decision-making functions with the aids of machine learning assisted algorithms to form a smart home based intelligent system. In this review, we introduce the conventional rigid microelectromechanical system (MEMS) based micro/nano sensors and energy harvesters, followed by presenting the advances in the wearable counterparts for better human interactions. We then discuss the viable integration approaches for micro/nano sensors and energy harvesters to form self-sustainable IoT systems. Whereafter, we emphasize the recent development of AIoT based systems and the corresponding applications enabled by the machine learning algorithms. Smart home based healthcare technology enabled by the integrated multi-functional sensing platform and bioelectronic medicine is also presented as an important future direction, as well as wearable photonics sensing system as a complement to the wearable electronics sensing system.

Quasi-Passive Resistive Exosuit for Space Activities: Proof of Concept

The limits of space travel are continuously evolving, and this creates increasingly extreme challenges for the crew’s health that must be addressed by the scientific community. Long-term exposure to micro-gravity, during orbital flights, contributes to muscle strength degradation and increases bone density loss. In recent years, several exercise devices have been developed to counteract the negative health effects of zero-gravity on astronauts. However, the relatively large size of these devices, the need for a dedicated space and the exercise time-frame for each astronaut, does not make these devices the best choice for future long range exploration missions. This paper presents a quasi-passive exosuit to provide muscle training using a small, portable, proprioceptive device. The exosuit promotes continuous exercise, by resisting the user’s motion, during routine all-day activity. This study assesses the effectiveness of the resistive exosuit by evaluating its effects on muscular endurance during a terrestrial walking task. The experimental assessment on biceps femoris and vastus lateralis, shows a mean increase in muscular activation of about 97.8% during five repetitions of 3 min walking task at 3 km/h. The power frequency analysis shows an increase in muscular fatigue with a reduction of EMG median frequency of about 15.4% for the studied muscles.

High-efficiency vertical fibre-to-polymer waveguide coupling scheme for scalable polymer photonic circuits

Polymer photonic circuits offer a versatile platform for various applications, including communication, sensing and optical signal processing. Though polymers offer broadband, linear and nonlinear optical properties, the coupling between an optical fibre and a polymer waveguide has been a challenge. In this work, we propose and demonstrate a wafer-scale vertical coupling scheme for polymer waveguides. The scheme uses a silicon nitride grating coupler with an inverse taper to couple between an optical fibre and a SU8 polymer waveguide. We demonstrate a maximum coupling efficiency of -3.55 dB in the C-band and -2.92 dB in the L-band with a 3-dB bandwidth of 74 and 80 nm, respectively. A detailed design and simulation, fabrication, and characterisation results are presented. The scheme demonstrates a scalable and efficient surface grating approach for polymer photonic integrated circuits.

Heterogeneous sensing in a multifunctional soft sensor for human-robot interfaces

Soft sensors have been playing a crucial role in detecting different types of physical stimuli to part or the entire body of a robot, analogous to mechanoreceptors or proprioceptors in biology. Most of the currently available soft sensors with compact form factors can detect only a single deformation mode at a time due to the limitation in combining multiple sensing mechanisms in a limited space. However, realizing multiple modalities in a soft sensor without increasing its original form factor is beneficial, because even a single input stimulus to a robot may induce a combination of multiple modes of deformation. Here, we report a multifunctional soft sensor capable of decoupling combined deformation modes of stretching, bending, and compression, as well as detecting individual deformation modes, in a compact form factor. The key enabling design feature of the proposed sensor is a combination of heterogeneous sensing mechanisms: optical, microfluidic, and piezoresistive sensing. We characterize the performance on both detection and decoupling of deformation modes, by implementing both a simple algorithm of threshold evaluation and a machine learning technique based on an artificial neural network. The proposed soft sensor is able to estimate eight different deformation modes with accuracies higher than 95%. We lastly demonstrate the potential of the proposed sensor as a method of human-robot interfaces with several application examples highlighting its multifunctionality.

Geometrically Structured Nanomaterials for Nanosensors, NEMS, and Nanosieves

Recently, geometrically structured nanomaterials have received great attention due to their unique physical and chemical properties, which originate from the geometric variation in such materials. Indeed, the use of various geometrically structured nanomaterials has been actively reported in enhanced-performance devices in a wide range of applications. Recent significant progress in the development of geometrically structured nanomaterials and associated devices is summarized. First, a brief introduction of advanced nanofabrication methods that enable the fabrication of various geometrically structured nanomaterials is given, and then the performance enhancements achieved in devices utilizing these nanomaterials, namely, i) physical and gas nanosensors, ii) nanoelectromechanical devices, and iii) nanosieves are described. For the device applications, a systematic summary of their structures, working mechanisms, fabrication methods, and output performance is provided. Particular focus is given to how device performance can be enhanced through the geometric structures of the nanomaterials. Finally, perspectives on the development of novel nanomaterial structures and associated devices are presented.

Motion Detection Using Tactile Sensors Based on Pressure-Sensitive Transistor Arrays

In recent years, to develop more spontaneous and instant interfaces between a system and users, technology has evolved toward designing efficient and simple gesture recognition (GR) techniques. As a tool for acquiring human motion, a tactile sensor system, which converts the human touch signal into a single datum and executes a command by translating a bundle of data into a text language or triggering a preset sequence as a haptic motion, has been developed. The tactile sensor aims to collect comprehensive data on various motions, from the touch of a fingertip to large body movements. The sensor devices have different characteristics that are important for target applications. Furthermore, devices can be fabricated using various principles, and include piezoelectric, capacitive, piezoresistive, and field-effect transistor types, depending on the parameters to be achieved. Here, we introduce tactile sensors consisting of field-effect transistors (FETs). GR requires a process involving the acquisition of a large amount of data in an array rather than a single sensor, suggesting the importance of fabricating a tactile sensor as an array. In this case, an FET-type pressure sensor can exploit the advantages of active-matrix sensor arrays that allow high-array uniformity, high spatial contrast, and facile integration with electrical circuitry. We envision that tactile sensors based on FETs will be beneficial for GR as well as future applications, and these sensors will provide substantial opportunities for next-generation motion sensing systems.

Linear piezoresistive strain sensor based on graphene/g-C3N4/PDMS heterostructure

Here we report a novel hybrid material consists of 2D graphitic carbon nitride (g-C₃N₄) and graphene heterostructure that exhibits piezoresistivity superior to graphene and potentially being used as a strain sensor. The g-C₃N₄ that contains periodically spaced triangular nanopores is used for improving the piezoresistivity of the sensor imparting change in the polarization upon application of strain. In this work, we have investigated graphene/g-C₃N₄ interfaced materials and quantified its piezoresistive effects through experimental analysis and density functional theory (DFT) based computational studies provide insights into the electronic structures of the hybrid interfaces. We have observed a linear response in electrical resistance for a wide range of uniaxial strains up to ∼25%. The observed increase in resistance upon application of strain corroborates with our computational finding of strain-dependent band gap opening. Further, it has been realized that band-gap opening occurs exclusively in the graphitic layer of the composite materials under strain. However, the g-C₃N₄ bands remain intact at the interface. The linearity and a considerably small gauge factor (1.89) make graphene/g-C₃N₄ a promising heterostructure material unlike conventional metal gauge sensor in wide strain pressure sensor devices.

Mechanical Sensing for Lower Limb Soft Exoskeletons: Recent Progress and Challenges

Soft exoskeletons hold promise for facilitating monitoring and assistance in case of light impairment and for prolonging independent living. In contrast to rigid material-based exoskeletons, they strongly demand for new approaches of soft sensing and actuation solutions. This chapter overviews soft exoskeletons in contrast to rigid exoskeletons and focuses on the recent advancements on the movement monitoring in lower limb soft exoskeletons. Compliant materials and soft tactile sensing approaches can be utilized to build smart sensorized garments for joint angle measurements (needed for both control and monitoring). However, currently there are still several open challenges derived from the needed close interaction between the human body and the soft exoskeleton itself, especially related to how sensing function and robustness are strongly affected by wearability, which will need to be overcome in the near future.

Fabrication and Dynamic Modeling of Bidirectional Bending Soft Actuator Integrated with Optical Waveguide Curvature Sensor

Soft robots exhibit many exciting properties due to their softness and body compliance. However, to interact with the environment safely and to perform a task effectively, a soft robot faces a series of challenges such as dexterous motion, proprioceptive sensing, and robust control of its deformable bodies. To address these issues, this article presents a method for fabrication and dynamic modeling of a novel bidirectional bending soft pneumatic actuator that embeds a curvature proprioceptive sensor. The bidirectional bending deformation was generated by two similar chambers with a sinusoidal shape for reducing the internal dampness during bending deformation. An optical waveguide made from flexible poly (methyl methacrylate) material that is immune to the inlet pressure was embedded into the actuator body to measure its bending angle. A dynamic modeling framework based on step response and parameter fitting was proposed to establish a simple differential equation that can describe the nonlinear behavior of the soft actuator. Hence, a sliding mode controller is designed based on this differential equation and the Taylor expansion. The proposed dynamical model and the sliding mode controller were validated by trajectory tracking experiments. The performance of the bidirectional bending soft actuator, such as the linear output of the curvature sensor in different inflating patterns, the proprioceptive sensitiveness to the external environment, the output force, and large bending range under relatively small pressure, was evaluated by relevant experimental paradigms. Prototypes from the novel design and fabrication process demonstrated the soft actuator's potential applications in industrial grasping and hand rehabilitation.

Graphene-based optical waveguide tactile sensor for dynamic response

Optical tactile sensors based on a directional coupler have been widely investigated because of their many advantages. However, one important requirement limits their wide application: the refractive index of the upper superstrate must be equal to or larger than that of the optical waveguide core. To overcome this disadvantage, an optical waveguide tactile sensor using graphene is proposed and its operational feasibility was validated experimentally. The pressure-dependent lateral deformation of the low-index prism-like microstructure on an elastomer superstrate has a key role in optically measuring the mechanical pressure. By mechanically varying the lateral deformation area, the waveguide core-graphene-polydimethylsiloxane (PDMS) interface area was adjusted and the amount of light absorption by graphene became tunable, even when the refractive index of the superstrate was lower than that of the waveguide core. The dynamic response of the sensor was accurately matched to the repeated pressing and release time of the pressure, and exhibited a real-time response to multi-stepped mechanical pressing and releasing using a piezoelectric motor. The proposed graphene-based optical tactile sensor is foundational to the use of a wide range of materials for overcoming the shortcoming of a directional coupler-based optical tactile sensor.

Toward Perceptive Soft Robots: Progress and Challenges

In the past few years, soft robotics has rapidly become an emerging research topic, opening new possibilities for addressing real-world tasks. Perception can enable robots to effectively explore the unknown world, and interact safely with humans and the environment. Among all extero- and proprioception modalities, the detection of mechanical cues is vital, as with living beings. A variety of soft sensing technologies are available today, but there is still a gap to effectively utilize them in soft robots for practical applications. Here, the developments in soft robots with mechanical sensing are summarized to provide a comprehensive understanding of the state of the art in this field. Promising sensing technologies for mechanically perceptive soft robots are described, categorized, and their pros and cons are discussed. Strategies for designing soft sensors and criteria to evaluate their performance are outlined from the perspective of soft robotic applications. Challenges and trends in developing multimodal sensors, stretchable conductive materials and electronic interfaces, modeling techniques, and data interpretation for soft robotic sensing are highlighted. The knowledge gap and promising solutions toward perceptive soft robots are discussed and analyzed to provide a perspective in this field.

Elastomer thin-film pressure sensor based on embedded photonic tunnel-junction arrays

We propose an elastomer thin-film pressure sensor enabled by pressure-sensitive optical signals through vertical photonic tunnel-junction couplers. We provide the operation principle, design, fabrication, and test results from a 50 μm thick polydimethylsiloxane sheet accommodating embedded vertical photonic tunnel-junction couplers. The result with a 5 mm long device shows a differential optical power change that is ∼140% of the incident power under moderate external pressure of ∼40  kPa, thereby clearly demonstrating a robust pressure-sensing capability realized in a highly flexible, lightweight, transferrable, optically transparent, and bio-compatible thin-film material. Therefore, the proposed approach potentially enables versatile pressure and touch sensors for many applications in practice.

Construction and Functionality of a Ceramic Resonant Pressure Sensor for Operation at Elevated Temperatures

Piezoelectric ceramic resonant pressure sensors have shown potential as sensing elements for harsh environments, such as elevated temperatures. For operating temperatures exceeding ~250 °C, conventional and widely used Pb(Zr,Ti)O₃ (PZT) piezoelectrics should be replaced. Here, a ceramic pressure sensor from low-temperature co-fired ceramics (LTCC) was constructed by integrating a piezoelectric actuator made from bismuth ferrite (BiFeO₃) on a diaphragm. This ferroelectric material was selected because of its high Curie temperature (T_C = 825 °C) and as a lead-free piezoelectric extensively investigated for high-temperature applications. In order to construct a sensor with suitable pressure sensitivity, numerical simulations were used to define the optimum construction dimensions. The functionality of the pressure sensor was tested up to 201 °C. The measurements confirmed a pressure sensitivity, i.e., resonance frequency shift of the sensor per unit of pressure, of -8.7 Hz/kPa up to 171 °C. It was suggested that the main reason for the hindered operation at the elevated temperatures could lie in the thermo-mechanical properties of the diaphragm and the adhesive bonding at the actuator-diaphragm interconnection.

Self-Powered Real-Time Arterial Pulse Monitoring Using Ultrathin Epidermal Piezoelectric Sensors

Continuous monitoring of an arterial pulse using a pressure sensor attached on the epidermis is an important technology for detecting the early onset of cardiovascular disease and assessing personal health status. Conventional pulse sensors have the capability of detecting human biosignals, but have significant drawbacks of power consumption issues that limit sustainable operation of wearable medical devices. Here, a self-powered piezoelectric pulse sensor is demonstrated to enable in vivo measurement of radial/carotid pulse signals in near-surface arteries. The inorganic piezoelectric sensor on an ultrathin plastic achieves conformal contact with the complex texture of the rugged skin, which allows to respond to the tiny pulse changes arising on the surface of epidermis. Experimental studies provide characteristics of the sensor with a sensitivity (≈0.018 kPa^-1 ), response time (≈60 ms), and good mechanical stability. Wireless transmission of detected arterial pressure signals to a smart phone demonstrates the possibility of self-powered and real-time pulse monitoring system.

A paper-based touch sensor with an embedded micro-probe array fabricated by double-sided laser printing

Touch sensor is one of the key components for human interfacing devices. However, although various touch sensors have been demonstrated, their sophisticated fabrication processes and complicated structures make them expensive and delicate, and thus they are not considered to be practical for wide application in daily life. Herein, we present a low-cost and scalable paper-based touch sensor suitable for practical applications. The sensor is based on the novel structure of embedded silver nanowire micro-probe arrays in a paper substrate, which exhibits high sensitivity to multiple touch inputs and compact structure with a total thickness of ca. 100 μm. Silver nanowire electrodes on two sides are manufactured at the same time via an original double-sided laser printing technique. Since this technique is mask-free, solvent-free and highly efficient, it is very suitable for paper substrates that cannot endure solvent processing. The sensing properties of the sensor in various extreme situations are examined and the spatial distributions of touch pressure are detected by arranging the sensing units in arrays. Demonstration examples of the touch sensor and pressure mapping are presented, and finally, the successful application of the sensor array in an electronic lock system is shown to further illustrate its applicability.

Recent Advancements in Flexible and Stretchable Electrodes for Electromechanical Sensors: Strategies, Materials, and Features

Stretchable and flexible sensors attached onto the surface of the human body can perceive external stimuli, thus attracting extensive attention due to their lightweight, low modulus, low cost, high flexibility, and stretchability. Recently, a myriad of efforts have been devoted to improving the performance and functionality of wearable sensors. Herein, this review focuses on recent remarkable advancements in the development of flexible and stretchable sensors. Multifunction of these wearable sensors is realized by incorporating some desired features (e.g., self-healing, self-powering, linearity, and printing). Next, focusing on the characteristics of carbon nanomaterials, nanostructured metal, conductive polymer, or their hybrid composites, two major strategies (e.g., materials that stretch and structures that stretch) and diverse design approaches have been developed to achieve highly flexible and stretchable electrodes. Strain sensing performances of recently reported sensors indicate that the appropriate choice of geometric engineering as well as intrinsically stretchable materials is essential for high-performance strain sensing. Finally, some important directions and challenges of a fully sensor-integrated wearable platform are proposed to realize their potential applications for human motion monitoring and human-machine interfaces.

Flexible and stretchable nanowire-coated fibers for optoelectronic probing of spinal cord circuits

Studies of neural pathways that contribute to loss and recovery of function following paralyzing spinal cord injury require devices for modulating and recording electrophysiological activity in specific neurons. These devices must be sufficiently flexible to match the low elastic modulus of neural tissue and to withstand repeated strains experienced by the spinal cord during normal movement. We report flexible, stretchable probes consisting of thermally drawn polymer fibers coated with micrometer-thick conductive meshes of silver nanowires. These hybrid probes maintain low optical transmission losses in the visible range and impedance suitable for extracellular recording under strains exceeding those occurring in mammalian spinal cords. Evaluation in freely moving mice confirms the ability of these probes to record endogenous electrophysiological activity in the spinal cord. Simultaneous stimulation and recording is demonstrated in transgenic mice expressing channelrhodopsin 2, where optical excitation evokes electromyographic activity and hindlimb movement correlated to local field potentials measured in the spinal cord.

Tribotronic Transistor Array as an Active Tactile Sensing System

Large-scale tactile sensor arrays are of great importance in flexible electronics, human-robot interaction, and medical monitoring. In this paper, a flexible 10 × 10 tribotronic transistor array (TTA) is developed as an active tactile sensing system by incorporating field-effect transistor units and triboelectric nanogenerators into a polyimide substrate. The drain-source current of each tribotronic transistor can be individually modulated by the corresponding external contact, which has induced a local electrostatic potential to act as the conventional gate voltage. By scaling down the pixel size from 5 × 5 to 0.5 × 0.5 mm², the sensitivities of single pixels are systematically investigated. The pixels of the TTA show excellent durability, independence, and synchronicity, which are suitable for applications in real-time tactile sensing, motion monitoring, and spatial mapping. The integrated tribotronics provides an unconventional route to realize an active tactile sensing system, with prospective applications in wearable electronics, human-machine interfaces, fingerprint identification, and so on.

Topography-specific isotropic tunneling in nanoparticle monolayer with sub-nm scale crevices

Material used in flexible devices may experience anisotropic strain with identical magnitude, outputting coherent signals that tend to have a serious impact on device reliability. In this work, the surface topography of the nanoparticles (NPs) is proposed to be a parameter to control the performance of strain gauge based on tunneling behavior. In contrast to anisotropic tunneling in a monolayer of spherical NPs, electron tunneling in a monolayer of urchin-like NPs actually exhibits a nearly isotropic response to strain with different loading orientations. Isotropic tunneling of the urchin-like NPs is caused by the interlocked pikes of these urchin-like NPs in a random manner during external mechanical stimulus. Topography-dependent isotropic tunneling in two dimensions reported here opens a new opportunity to create highly reliable electronics with superior performance.

Flexible Capacitive Tactile Sensor Based on Micropatterned Dielectric Layer

Flexible tactile sensors are considered as an effective way to realize the sense of touch, which can perform the synchronized interactions with surrounding environment. Here, the utilization of bionic microstructures on natural lotus leaves is demonstrated to design and fabricate new-type of high-performance flexible capacitive tactile sensors. Taking advantage of unique surface micropattern of lotus leave as the template for electrodes and using polystyrene microspheres as the dielectric layer, the proposed devices present stable and high sensing performance, such as high sensitivity (0.815 kPa^-1 ), wide dynamic response range (from 0 to 50 N), and fast response time (≈38 ms). In addition, the flexible capacitive sensor is not only applicable to pressure (touch of a single hair), but also to bending and stretching forces. The results indicate that the proposed capacitive tactile sensor is a promising candidate for the future applications in electronic skins, wearable robotics, and biomedical devices.

Highly Sensitive, Flexible, and Wearable Pressure Sensor Based on a Giant Piezocapacitive Effect of Three-Dimensional Microporous Elastomeric Dielectric Layer

We report a flexible and wearable pressure sensor based on the giant piezocapacitive effect of a three-dimensional (3-D) microporous dielectric elastomer, which is capable of highly sensitive and stable pressure sensing over a large tactile pressure range. Due to the presence of micropores within the elastomeric dielectric layer, our piezocapacitive pressure sensor is highly deformable by even very small amounts of pressure, leading to a dramatic increase in its sensitivity. Moreover, the gradual closure of micropores under compression increases the effective dielectric constant, thereby further enhancing the sensitivity of the sensor. The 3-D microporous dielectric layer with serially stacked springs of elastomer bridges can cover a much wider pressure range than those of previously reported micro-/nanostructured sensing materials. We also investigate the applicability of our sensor to wearable pressure-sensing devices as an electronic pressure-sensing skin in robotic fingers as well as a bandage-type pressure-sensing device for pulse monitoring at the human wrist. Finally, we demonstrate a pressure sensor array pad for the recognition of spatially distributed pressure information on a plane. Our sensor, with its excellent pressure-sensing performance, marks the realization of a true tactile pressure sensor presenting highly sensitive responses to the entire tactile pressure range, from ultralow-force detection to high weights generated by human activity.

Linearly and Highly Pressure-Sensitive Electronic Skin Based on a Bioinspired Hierarchical Structural Array

Pressure-sensitive electronic skin composed of a hierarchical structural array exhibits outstanding linear and high sensitivity in the pressure range exerted by gentle touch. By virtue of monolayer graphene acting as electrode material, this device can be operated with low voltage. Especially, its high transparency enables an accurate placement of the device on the target position when it is used for health monitoring.

Magnetic Nanocomposite Cilia Tactile Sensor

A multifunctional biomimetic nanocomposite tactile sensor is developed that can detect shear and vertical forces, feel texture, and measure flow with extremely low power consumption. The sensor's high performance is maintained within a wide operating range that can be easily adjusted. The concept works on rigid and flexible substrates and the sensors can be used in air or water without any modifications.

Recent Progress in Electronic Skin

The skin is the largest organ of the human body and can sense pressure, temperature, and other complex environmental stimuli or conditions. The mimicry of human skin's sensory ability via electronics is a topic of innovative research that could find broad applications in robotics, artificial intelligence, and human-machine interfaces, all of which promote the development of electronic skin (e-skin). To imitate tactile sensing via e-skins, flexible and stretchable pressure sensor arrays are constructed based on different transduction mechanisms and structural designs. These arrays can map pressure with high resolution and rapid response beyond that of human perception. Multi-modal force sensing, temperature, and humidity detection, as well as self-healing abilities are also exploited for multi-functional e-skins. Other recent progress in this field includes the integration with high-density flexible circuits for signal processing, the combination with wireless technology for convenient sensing and energy/data transfer, and the development of self-powered e-skins. Future opportunities lie in the fabrication of highly intelligent e-skins that can sense and respond to variations in the external environment. The rapidly increasing innovations in this area will be important to the scientific community and to the future of human life.

Revealing bending and force in a soft body through a plant root inspired approach

An emerging challenge in soft robotics research is to reveal mechanical solicitations in a soft body. Nature provides amazing clues to develop unconventional components that are capable of compliant interactions with the environment and living beings, avoiding mechanical and algorithmic complexity of robotic design. We inspire from plant-root mechanoperception and develop a strategy able to reveal bending and applied force in a soft body with only two sensing elements of the same kind, and a null computational effort. The stretching processes that lead to opposite tissue deformations on the two sides of the root wall are emulated with two tactile sensing elements, made of soft and stretchable materials, which conform to reversible changes in the shape of the body they are built in and follow its deformations. Comparing the two sensory responses, we can discriminate the concave and the convex side of the bent body. Hence, we propose a new strategy to reveal in a soft body the maximum bending angle (or the maximum deflection) and the externally applied force according to the body's mechanical configuration.