Simultaneously Detecting Subtle and Intensive Human Motions Based on a Silver Nanoparticles Bridged Graphene Strain Sensor

Recent Progress on Flexible Self-Powered Tactile Sensing Platforms for Health Monitoring and Robotics

Over the past decades, tactile sensing technology has made significant advances in the fields of health monitoring and robotics. Compared to conventional sensors, self-powered tactile sensors do not require an external power source to drive, which makes the entire system more flexible and lightweight. Therefore, they are excellent candidates for mimicking the tactile perception functions for wearable health monitoring and ideal electronic skin (e-skin) for intelligent robots. Herein, the working principles, materials, and device fabrication strategies of various self-powered tactile sensing platforms are introduced first. Then their applications in health monitoring and robotics are presented. Finally, the future prospects of self-powered tactile sensing systems are discussed.

Flexible Strain Sensors Based on an Interlayer Synergistic Effect of Nanomaterials for Continuous and Noninvasive Blood Pressure Monitoring

The continuous, noninvasive monitoring of human blood pressure (BP) through the accurate detection of pulse waves has extremely stringent requirements on the sensitivity and stability of flexible strain sensors. In this study, a new ultrasensitive flexible strain sensor based on the interlayer synergistic effect was fabricated through drop-casting and drying silver nanowires and graphene films on polydimethylsiloxane substrates and was further successfully applied for continuous monitoring of BP. This strain sensor exhibited ultrahigh sensitivity with a maximum gauge factor of 34357.2 (∼700% sensitivity enhancement over other major sensors), satisfactory response time (∼85 ms), wide strange range (12%), and excellent stability. An interlayer fracture mechanism was proposed to elucidate the working principle of the strain sensor. The real-time BP values can be obtained by analyzing the relationship between the BP and the pulse transit time. To verify our strain sensor for real-time BP monitoring, our strain sensor was compared with a conventional electrocardiogram-photoplethysmograph method and a commercial cuff-based device and showed similar measurement results to BP values from both methods, with only minor differences of 0.693, 0.073, and 0.566 mmHg in the systolic BP, diastolic BP, and mean arterial pressure, respectively. Furthermore, the reliability of the strain sensors was validated by testing 20 human subjects for more than 50 min. This ultrasensitive strain sensor provides a new pathway for continuous and noninvasive BP monitoring.

High-density, highly sensitive sensor array of spiky carbon nanospheres for strain field mapping

While accurate mapping of strain distribution is crucial for assessing stress concentration and estimating fatigue life in engineering applications, conventional strain sensor arrays face a great challenge in balancing sensitivity and sensing density for effective strain mapping. In this study, we present a Fowler-Nordheim tunneling effect of monodispersed spiky carbon nanosphere array on polydimethylsiloxane as strain sensor arrays to achieve a sensitivity up to 70,000, a sensing density of 100 pixel cm-2, and logarithmic linearity over 99% within a wide strain range of 0% to 60%. The highly ordered assembly of spiky carbon nanospheres in each unit also ensures high inter-unit consistency (standard deviation ≤3.82%). Furthermore, this sensor array can conformally cover diverse surfaces, enabling accurate acquisition of strain distributions. The sensing array offers a convenient approach for mapping strain fields in various applications such as flexible electronics, soft robotics, biomechanics, and structure health monitoring.

Flexible tactile sensors with interlocking serrated structures based on stretchable multiwalled carbon nanotube/silver nanowire/silicone rubber composites

Flexible tactile sensors have attracted significant interest because of their application scope in the fields of biomedicine, motion detection, and human-computer interaction. However, the development of tactile sensors with high sensitivity and flexibility remains a critical challenge. This study develops a patterned, stretchable, and fully elastomeric multiwalled carbon nanotube (MWCNT)/silver nanowire (Ag NW)/silicone rubber (SR) composite. The addition of Ag NWs to MWCNTs enhances the transmission path of the conductive network, yielding a CNT/Ag NW/SR composite with a sensitivity coefficient of 40. This characteristic renders it suitable for use as a piezoresistive sensing material. The interlocking sawtooth structure can convert the mechanical stimuli of the sensor to the tensile strain of the composite, thereby enhancing its sensitivity and flexibility. Experimental results indicate that the developed tactile sensor exhibited a sensitivity of 2.82 N-1 at 0-0.5 N and 1.51 N-1 at 0.5-2 N. These haptic sensors also demonstrate good dynamic response, repeatability, and long life. Furthermore, experimental results show that these haptic sensors exhibit high reproducibility, fast dynamic response, and good mechanical and electrical stability. Because of these exceptional properties, the as-prepared sensor can be applied in the development of smart robots, prosthetics, and wearable devices.

Soft Electronics for Health Monitoring Assisted by Machine Learning

Due to the development of the novel materials, the past two decades have witnessed the rapid advances of soft electronics. The soft electronics have huge potential in the physical sign monitoring and health care. One of the important advantages of soft electronics is forming good interface with skin, which can increase the user scale and improve the signal quality. Therefore, it is easy to build the specific dataset, which is important to improve the performance of machine learning algorithm. At the same time, with the assistance of machine learning algorithm, the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis. The soft electronics and machining learning algorithms complement each other very well. It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future. Therefore, in this review, we will give a careful introduction about the new soft material, physiological signal detected by soft devices, and the soft devices assisted by machine learning algorithm. Some soft materials will be discussed such as two-dimensional material, carbon nanotube, nanowire, nanomesh, and hydrogel. Then, soft sensors will be discussed according to the physiological signal types (pulse, respiration, human motion, intraocular pressure, phonation, etc.). After that, the soft electronics assisted by various algorithms will be reviewed, including some classical algorithms and powerful neural network algorithms. Especially, the soft device assisted by neural network will be introduced carefully. Finally, the outlook, challenge, and conclusion of soft system powered by machine learning algorithm will be discussed.

Ultra-sensitive, Multi-directional Flexible Strain Sensors Based on an MXene Film with Periodic Wrinkles

The fast-growing motion capturing/monitoring technique has raised a great demand for flexible strain sensors. For capturing complex motions (e.g., facial motion), both the strain amplitude and direction should be accurately detected. Although some reported sensors based on anisotropic conductive networks are proved to show accurate localization of strain directions, it is still a great challenge to achieve both high sensitivity and a high sensing range in these designs. Here, a self-assembled Ti₃C₂T_x MXene film with parallel and periodic wrinkles is fabricated on a stretchable poly(dimethylsiloxane) substrate for constructing multi-directional strain sensors. During stretching, relative slip and crack will occur between the stacked MXene nanosheets, which contribute to high structural sensitivity in the MXene film. Meanwhile, the wrinkled structure contributes to high stretchability. As a result, the sensor based on the film with one-dimensional periodic wrinkles shows a large sensing range (>50%) and a gauge factor of 45. Furthermore, the sensor can accurately detect both the strain amplitude and direction by using the MXene film with two-dimensional wrinkles. It shows distinguishable electrical responses when detecting different-amplitude human/robot motions such as joint bending and walking. Additionally, the directions in complex human motions (e.g., facial motion) can also be well-tracked. This work provides an effective strategy to detect multi-directional motions.

An Ultra-Sensitive and Multifunctional Electronic Skin with Synergetic Network of Graphene and CNT

Electronic skin (e-skin) has attracted tremendous interest due to its diverse potential applications, including in physiological signal detection, health monitoring, and artificial throats. However, the major drawbacks of traditional e-skin are the weak adhesion of substrates, incompatibility between sensitivity and stretchability, and its single function. These shortcomings limit the application of e-skin and increase the complexity of its multifunctional integration. Herein, the synergistic network of crosslinked SWCNTs within and between multilayered graphene layers was directly drip coated onto the PU thin film with self-adhesion to fabricate versatile e-skin. The excellent mechanical properties of prepared e-skin arise from the sufficient conductive paths guaranteed by SWCNTs in small and large deformation under various strains. The prepared e-skin exhibits a low detection limit, as small as 0.5% strain, and compatibility between sensitivity and stretchability with a gauge factor (GF) of 964 at a strain of 0-30%, and 2743 at a strain of 30-60%. In physiological signals detection application, the e-skin demonstrates the detection of subtle motions, such as artery pulse and blinking, as well as large body motions, such as knee joint bending, elbow movement, and neck movement. In artificial throat application, the e-skin integrates sound recognition and sound emitting and shows clear and distinct responses between different throat muscle movements and different words for sound signal acquisition and recognition, in conjunction with superior sound emission performance with a sound spectrum response of 71 dB (f = 12.5 kHz). Overall, the presented comprehensive study of novel materials, structures, properties, and mechanisms offers promising potential in physiological signals detection and artificial throat applications.

Highly stretchable and sensitive strain sensors based on modified PDMS and hybrid particles of AgNWs/graphene

High-performance strain sensors have received extensive attention due to their wide range of applications in pulsebeat detection, speech recognition, motion detection, and blood pressure monitoring. However, it is difficult to simultaneously attain high sensitivity and excellent stretchability. In this work, a strain sensor based on modified polydimethylsiloxane (PDMS) and conductive hybrid particles of silver nanowires (AgNWs)/graphene was successfully fabricated. A facile solvothermal polymerization process was used to change the structure of cross-linking networks and to obtain the PDMS elastomer with excellent stretchability. The application of the modified PDMS endows the strain sensor with a large strain range (∼20%), which is 100% higher than that of the strain sensor with unmodified PDMS. The AgNWs/graphene hybrid particles were prepared by a simple coprecipitation, reduction, and drying method. AgNWs serve as bridges between graphene sheets, endowing the strain sensor with a large gauge factor (GF = 400). The stability of the strain sensor was also verified. Besides, the strain sensor was successfully used in fields such as finger bending and speech recognition. Considering its high sensitivity, excellent stretchability, and high working stability, the sensor has great potential in health monitoring and motion detection.

Graphene-based strain sensor with sandwich structure and its application in bowel sounds monitoring

Surgery is one of the primary treatment modalities for gastrointestinal tumors but can lead to postoperative ileus (POI), which can aggravate pain and increase costs. The incidence of POI can be effectively reduced by monitoring bowel sounds to assist doctors in deciding the timing of transoral feeding. In this study, we prepared a flexible strain sensor based on a graphene composite material and tested the feasibility of sensor monitoring of bowel sounds using simultaneous stethoscope and sensor monitoring. We found that the time of hearing the bowel sounds (12.0–12.1 s) corresponded to the time of waveform change monitored by the sensor (12.036 s), and the sound tone magnitude corresponded to the waveform amplitude. This proves that the application of sensors to monitor bowel sounds is feasible, which opens up a new field for the application of graphene sensors and provides a new way for clinicians to judge the condition of the intestine.

Combining medicine and materials science. First application of graphene strain sensors for monitoring bowel sounds

High-Performance Strain Sensors Based on Au/Graphene Composite Films with Hierarchical Cracks for Wide Linear-Range Motion Monitoring

Stretchable strain sensors based on nanomaterial thin films have aroused extensive interest for the strain perception of smart skins. However, it still remains challenging to have them achieve high sensitivity over wide linear working ranges. Herein, we propose a facile strategy to fabricate stretchable strain sensors based on Au/graphene composite films (AGCFs) with hierarchical cracks and demonstrate their superior sensing performances. The polydimethylsiloxane substrates were covered with self-assembled graphene films (SAGFs) and sputtered with Au, and then prestretching was applied to introduce hierarchical cracks. The AGCF strain sensors exhibited high sensitivity (gauge factor (GF) ≈ 153) and favorable linearity (R² ≈ 0.9975) in the wide working range (0-20%) with ultralow overshooting (∼1.7% at 20%), fast response (<42.5 ms), and also excellent cycling stability (1500 cycles). Besides, these patternable sensors could further achieve higher GF (∼320) via pattern designing. The dominant effect of the intermediate wrinkled SAGFs in forming hierarchical cracks was studied, and the linear sensing mechanism of the as-formed fractal microstructures was also revealed in detail. Moreover, the AGCF strain sensors were tested for motion monitoring of the human body and electronic bird. Due to the remarkable versatility, scalable fabrication, and integration capability, these sensors demonstrate great potential to construct smart skins.

Modeling Tunable Fracture in Hydrogel Shell Structures for Biomedical Applications

Hydrogels are nowadays widely used in various biomedical applications, and show great potential for the making of devices such as biosensors, drug- delivery vectors, carriers, or matrices for cell cultures in tissue engineering, etc. In these applications, due to the irregular complex surface of the human body or its organs/structures, the devices are often designed with a small thickness, and are required to be flexible when attached to biological surfaces. The devices will deform as driven by human motion and under external loading. In terms of mechanical modeling, most of these devices can be abstracted as shells. In this paper, we propose a mixed graph-finite element method (FEM) phase field approach to model the fracture of curved shells composed of hydrogels, for biomedical applications. We present herein examples for the fracture of a wearable biosensor, a membrane-coated drug, and a matrix for a cell culture, each made of a hydrogel. Used in combination with experimental material testing, our method opens a new pathway to the efficient modeling of fracture in biomedical devices with surfaces of arbitrary curvature, helping in the design of devices with tunable fracture properties.

High-Sensitivity and Extreme Environment-Resistant Sensors Based on PEDOT:PSS@PVA Hydrogel Fibers for Physiological Monitoring

The rapid development of flexible electronic devices has caused a boom in researching flexible sensors based on hydrogels, but most of the flexible sensors can only work at room temperature, and they are difficult to adapt to extremely cold or dry environments. Here, the flexible hydrogel fibers (PEDOT:PSS@PVA) with excellent resistance to extreme environments have been prepared by adding glycerin (GL) to the mixture of poly(vinyl alcohol) (PVA) and poly 3,4-dioxyethylene thiophene:polystyrene sulfonic acid (PEDOT:PSS) because GL molecules can form dynamic hydrogen bonds with an elastic matrix of PVA molecules. It is found that the prepared sensor exhibits very good flexibility and mechanical strength, and the ultimate tensile strength can reach up to 13.76 MPa when the elongation at break is 519.9%. Furthermore, the hydrogel fibers possess excellent water retention performance and low-temperature resistance. After being placed in the atmospheric environment for 1 year, the sensor still shows good flexibility. At a low temperature of -60 °C, the sensor can stably endure 1000 repeated stretches and shrinks (10% elongation). In addition to the response to a large strain, this fiber sensor can also detect extremely small strains as low as 0.01%. It is proved that complex human movements such as knuckle bending, vocalization, pulse, and others can be monitored perfectly by this fiber sensor. The above results mean that the PEDOT:PSS@PVA fiber sensor has great application prospects in physiological monitoring.

The Progress of Research into Flexible Sensors in the Field of Smart Wearables

In modern society, technology associated with smart sensors made from flexible materials is rapidly evolving. As a core component in the field of wearable smart devices (or 'smart wearables'), flexible sensors have the advantages of excellent flexibility, ductility, free folding properties, and more. When choosing materials for the development of sensors, reduced weight, elasticity, and wearer's convenience are considered as advantages, and are suitable for electronic skin, monitoring of health-related issues, biomedicine, human-computer interactions, and other fields of biotechnology. The idea behind wearable sensory devices is to enable their easy integration into everyday life. This review discusses the concepts of sensory mechanism, detected object, and contact form of flexible sensors, and expounds the preparation materials and their applicability. This is with the purpose of providing a reference for the further development of flexible sensors suitable for wearable devices.

Multiscale and hierarchical wrinkle enhanced graphene/Ecoflex sensors integrated with human-machine interfaces and cloud-platform

Current state-of-the-art stretchable/flexible sensors have received stringent demands on sensitivity, flexibility, linearity, and wide-range measurement capability. Herein, we report a methodology of strain sensors based on graphene/Ecoflex composites by modulating multiscale/hierarchical wrinkles on flexible substrates. The sensor shows an ultra-high sensitivity with a gauge factor of 1078.1, a stretchability of 650%, a response time of ~140 ms, and a superior cycling durability. It can detect wide-range physiological signals including vigorous body motions, pulse monitoring and speech recognition, and be used for monitoring of human respirations in real-time using a cloud platform, showing a great potential for the healthcare internet of things. Complex gestures/sign languages can be precisely detected. Human-machine interface is demonstrated by using a sensor-integrated glove to remotely control an external manipulator to remotely defuse a bomb. This study provides strategies for real-time/long-range medical diagnosis and remote assistance to perform dangerous tasks in industry and military fields.

Recent progress of fiber-based transistors: materials, structures and applications

Wearable electronics on fibers or fabrics assembled with electronic functions provide a platform for sensors, displays, circuitry, and computation. These new conceptual devices are human-friendly and programmable, which makes them indispensable for modern electronics. Their unique properties such as being adaptable in daily life, as well as being lightweight and flexible, have enabled many promising applications in robotics, healthcare, and the Internet of Things (IoT). Transistors, one of the fundamental blocks in electronic systems, allow for signal processing and computing. Therefore, study leading to integration of transistors with fabrics has become intensive. Here, several aspects of fiber-based transistors are addressed, including materials, system structures, and their functional devices such as sensory, logical circuitry, memory devices as well as neuromorphic computation. Recently reported advances in development and challenges to realizing fully integrated electronic textile (e-textile) systems are also discussed.

Quantifying the Piezoresistive Mechanism in High-Performance Printed Graphene Strain Sensors

Printed strain sensors will be important in applications such as wearable devices, which monitor breathing and heart function. Such sensors need to combine high sensitivity and low resistance with other factors such as cyclability, low hysteresis, and minimal frequency/strain-rate dependence. Although nanocomposite sensors can display a high gauge factor (G), they often perform poorly in the other areas. Recently, evidence has been growing that printed, polymer-free networks of nanoparticles, such as graphene nanosheets, display very good all-round sensing performance, although the details of the sensing mechanism are poorly understood. Here, we perform a detailed characterization of the thickness dependence of piezoresistive sensors based on printed networks of graphene nanosheets. We find both conductivity and gauge factor to display percolative behavior at low network thickness but bulk-like behavior for networks above ∼100 nm thick. We use percolation theory to derive an equation for gauge factor as a function of network thickness, which well-describes the observed thickness dependence, including the divergence in gauge factor as the percolation threshold is approached. Our analysis shows that the dominant contributor to the sensor performance is not the effect of strain on internanosheet junctions but the strain-induced modification of the network structure. Finally, we find these networks display excellent cyclability, hysteresis, and frequency/strain-rate dependence as well as gauge factors as high as 350.

Cost-Effective Fabrication of Transparent Strain Sensors via Micro-Scale 3D Printing and Imprinting

The development of strain sensors with high sensitivity and stretchability is essential for health monitoring, electronic skin, wearable devices, and human-computer interactions. However, sensors that combine high sensitivity and ultra-wide detection generally require complex preparation processes. Here, a novel flexible strain sensor with high sensitivity and transparency was proposed by filling a multiwalled carbon nanotube (MWCNT) solution into polydimethylsiloxane (PDMS) channel films fabricated via an electric field-driven (EFD) 3D printing and molding hybrid process. The fabricated flexible strain sensor with embedded MWCNT networks had superior gauge factors of 90, 285, and 1500 at strains of 6.6%, 14%, and 20%, respectively. In addition, the flexible strain sensors with an optical transparency of 84% offered good stability and durability with no significant change in resistance after 8000 stretch-release cycles. Finally, the fabricated flexible strain sensors with embedded MWCNT networks showed good practical performance and could be attached to the skin to monitor various human movements such as wrist flexion, finger flexion, neck flexion, blinking activity, food swallowing, and facial expression recognition. These are good application strategies for wearable devices and health monitoring.

The Identification Nanoparticle Sensor Using Back Propagation Neural Network Optimized by Genetic Algorithm

This study draws attention towards the application of identification nanoparticle (NPs) sensor based on back propagation (BP) neural network optimized by genetic algorithm (GA) in the early diagnosis of cancer cells. In this study, the traditional and optimized BP neural networks are compared in terms of error between the actual value and the predictive value, and they are further applied to the NP sensor for early diagnosis of cancer cells. The results show that the root mean square (RMS) and mean absolute error (MAE) of the optimized BP neural network are comparatively much smaller than the traditional ones. The particle size of silicon-coated fluorescent NPs is about 105 nm, and the relative fluorescence intensity of silicon-coated fluorescent NPs decreases slightly, maintaining the accuracy value above 80%. In the fluorescence imaging, it is found that there is obvious green fluorescence on the surface of the cancer cells, and the cancer cells still emit bright green fluorescence under the dark-field conditions. In this study, a phenolic resin polymer CMK-2 with a large surface area is successfully combined with Au. NPs with good dielectric property and bioaffinity are selectively bonded to the modified electrode through a sulfur-gold bond to prepare NP sensor. The sensor shows good stability, selectivity, and anti-interference property, providing a new method for the detection of early cancer cells.

Detecting subtle yet fast skeletal muscle contractions with ultrasoft and durable graphene-based cellular materials

Human bodily movements are primarily controlled by the contractions of skeletal muscles. Unlike joint or skeletal movements that are generally performed in the large displacement range, the contractions of the skeletal muscles that underpin these movements are subtle in intensity yet high in frequency. This subtlety of movement makes it a formidable challenge to develop wearable and durable soft materials to electrically monitor such motions with high fidelity for the purpose of, for example, muscle/neuromuscular disease diagnosis. Here we report that an intrinsically fragile ultralow-density graphene-based cellular monolith sandwiched between silicone rubbers can exhibit a highly effective stress and strain transfer mechanism at its interface with the rubber, with a remarkable improvement in stretchability (>100%). In particular, this hybrid also exhibits a highly sensitive, broadband-frequency electrical response (up to 180 Hz) for a wide range of strains. By correlating the mechanical signal of muscle movements obtained from this hybrid material with electromyography, we demonstrate that the strain sensor based on this hybrid material may provide a new, soft and wearable mechanomyography approach for real-time monitoring of complex neuromuscular–skeletal interactions in a broad range of healthcare and human–machine interface applications. This work also provides a new architecture-enabled functional soft material platform for wearable electronics.

Hydrogels and Their Role in Biosensing Applications

Hydrogels play an important role in the field of biomedical research and diagnostic medicine. They are emerging as a powerful tool in the context of bioanalytical assays and biosensing. In this context, this review gives an overview of different hydrogels and the role they adopt in a range of applications. Not only are hydrogels beneficial for the immobilization and embedding of biomolecules, but they are also used as responsive material, as wearable devices, or as functional material. In particular, the scientific and technical progress during the last decade is discussed. The newest hydrogel types, their synthesis, and many applications are presented. Advantages and performance improvements are described, along with their limitations.

Synthesis, Characterization, Applications, and Toxicity of Green Synthesized Nanoparticles

Nanotechnology is a cutting-edge area with numerous industrial applications. Nanoparticles are structures that have dimensions ranging from 1-100 nm which exhibit significantly different mechanical, optical, electrical, and chemical properties when compared with their larger counterparts. Synthetic routes that use natural sources, such as plant extracts, honey, and microorganisms are environmentally friendly and low-cost methods that can be used to obtain nanoparticles. These methods of synthesis generate products that are more stable and less toxic than those obtained using conventional methods. Nanoparticles formed by titanium dioxide, zinc oxide, silver, gold, and copper, as well as cellulose nanocrystals are among the nanostructures obtained by green synthesis that have shown interesting applications in several technological industries. Several analytical techniques have also been used to analyze the size, morphology, hydrodynamics, diameter, and chemical functional groups involved in the stabilization of the nanoparticles as well as to quantify and evaluate their formation. Despite their pharmaceutical, biotechnological, cosmetic, and food applications, studies have detected their harmful effects on human health and the environment; and thus, caution must be taken in uses involving living organisms. The present review aims to present an overview of the applications, the structural properties, and the green synthesis methods that are used to obtain nanoparticles, and special attention is given to those obtained from metal ions. The review also presents the analytical methods used to analyze, quantify, and characterize these nanostructures.

Materials, Electrical Performance, Mechanisms, Applications, and Manufacturing Approaches for Flexible Strain Sensors

With the recent great progress made in flexible and wearable electronic materials, the upcoming next generation of skin-mountable and implantable smart devices holds extensive potential applications for the lifestyle modifying, including personalized health monitoring, human-machine interfaces, soft robots, and implantable biomedical devices. As a core member within the wearable electronics family, flexible strain sensors play an essential role in the structure design and functional optimization. To further enhance the stretchability, flexibility, sensitivity, and electricity performances of the flexible strain sensors, enormous efforts have been done covering the materials design, manufacturing approaches and various applications. Thus, this review summarizes the latest advances in flexible strain sensors over recent years from the material, application, and manufacturing strategies. Firstly, the critical parameters measuring the performances of flexible strain sensors and materials development contains different flexible substrates, new nano- and hybrid- materials are introduced. Then, the developed working mechanisms, theoretical analysis, and computational simulation are presented. Next, based on different material design, diverse applications including human motion detection and health monitoring, soft robotics and human-machine interface, implantable devices, and biomedical applications are highlighted. Finally, synthesis consideration of the massive production industry of flexible strain sensors in the future; different fabrication approaches that are fully expected are classified and discussed.

Self-Repairing, Large Linear Working Range Shape Memory Carbon Nanotubes/Ethylene Vinyl Acetate Fiber Strain Sensor for Human Movement Monitoring

Flexible strain sensors have shown great application value in wearable devices. In the past decades, researchers have spent numerous efforts on developing high-stretchability, excellent dynamic durability, and large linear working range flexible strain sensors and shaped a series of important research results. However, the viscoelasticity of the elastic polymer is always a big challenge to develop a flexible sensor. Here, to overcome this challenge, we developed a novel self-repairing carbon nanotubes/ethylene vinyl acetate (CNTs/EVA) fiber strain sensor prepared by embedding the CNTs on the surface of the swollen shape memory EVA fiber via the ultrasonic method. The CNTs/EVA fiber strain sensors responded with significant results, with high stretchability (190% strain), large linear working range (up to 88% strain), excellent dynamic durability (5000 cycles), and fast response speed (312 ms). In addition, the permanently damaged conductive network of the strain sensors, caused by the viscoelasticity of elastic polymer, can restore above the transforming temperature of the shape memory CNTs/EVA fiber. Moreover, the performance of the restored strain sensors was almost as same as that of the original strain sensors. Furthermore, human health monitoring tests show that the CNTs/EVA fiber has a broad application prospect for human health monitoring in wearable electronic devices.

Understanding the Cycling Performance Degradation Mechanism of a Graphene-Based Strain Sensor and an Effective Corresponding Improvement Solution

Graphene-based strain sensors have attracted tremendous interest due to their potential application as intelligent wearable sensing devices. However, for graphene-based strain sensors, it is found that the sensing property at the beginning of the tensile cycle is not stable. Concretely, the peak resistance value gradually declines in the first dozens of cycles in every cyclic test. This is a problem that obviously affects the measurement accuracy but is rarely investigated so far. In this paper, this phenomenon is for the first time systematically studied. According to the reliable experimental results, it can be concluded that the decline of resistance is caused by the evolution of wrinkle morphologies in the graphene layer, which is essentially attributed to the temporary slippage of the graphene sheets under external stress. Based on the analyzed mechanism, a targeted improvement solution was proposed and verified. By the combined effects of polydopamine and Ni²⁺, the slippage among the rGO sheets was suppressed and a strain sensor with excellent sensing stability was obtained as expected. Furthermore, the sensitivity of the modified sensor was six times higher than that of the pristine one due to the change in the crack form, demonstrating it to be an effective method to obtain a graphene-based strain sensor with comprehensively high performance.

Superelastic, Sensitive, and Low Hysteresis Flexible Strain Sensor Based on Wave-Patterned Liquid Metal for Human Activity Monitoring

Flexible strain sensors have been widely used in wearable electronic devices for body physical parameter capturing. However, regardless of the stretchability of the sensing material, the resolution of small strain changes or the hysteresis between loading/unloading states has always limited the various applications of these sensors. In this paper, a microfluidic flexible strain sensor was achieved by introducing liquid metal eutectic gallium indium (EGaIn) embedded into a wave-shaped microchannel elastomeric matrix (300 μm width × 70 μm height). The microfluidic sensor can withstand a strain of up to 320%, and the hysteresis performance was also improved from 6.79 to 1.02% by the wave-patterned structure which can restrain the viscoelasticity of the elastomer effectively. Moreover, an enhanced wave-shaped strain sensor was fabricated by increasing the length of the microfluidic channel; it has high sensitivity (GF = 4.91) and resolution, and even as low as 0.09% strain change could be detected, which is capable of resolving microdeformation; besides, the enhanced wave-shaped strain sensor exhibits quick response time (t = 116 ms), long-term stability, and durability under periodic dynamic load. As an example of potential applications, the enhanced flexible sensor showed excellent mechanical compliance and was successfully applied as a conceptual wearable device for distinctively monitoring various kinds of human body and robot activities, such as the different states of the finger, neck, breathing chest, robot's joint, and so forth. The flexible wave-shaped strain sensor has great promising applications for wearable electronics, motion recognition, healthcare, and soft robotics.

Wearable Electronics Based on 2D Materials for Human Physiological Information Detection

Recently, advancement in materials production, device fabrication, and flexible circuit has led to the huge prosperity of wearable electronics for human healthcare monitoring and medical diagnosis. Particularly, with the emergence of 2D materials many merits including light weight, high stretchability, excellent biocompatibility, and high performance are used for those potential applications. Thus, it is urgent to review the wearable electronics based on 2D materials for the detection of various human signals. In this work, the typical graphene-based materials, transition-metal dichalcogenides, and transition metal carbides or carbonitrides used for the wearable electronics are discussed. To well understand the human physiological information, it is divided into two dominated categories, namely, the human physical and the human chemical signals. The monitoring of body temperature, electrograms, subtle signals, and limb motions is described for the physical signals while the detection of body fluid including sweat, breathing gas, and saliva is reviewed for the chemical signals. Recent progress and development toward those specific utilizations are highlighted in the Review with the representative examples. The future outlook of wearable healthcare techniques is briefly discussed for their commercialization.

Moisture-Resilient Graphene-Dyed Wool Fabric for Strain Sensing

E-textile consisting of natural fabrics has become a promising material to construct wearable sensors due to its comfortability and breathability on the human body. However, the reported fabric-based e-textile materials, such as graphene-treated cotton, silk, and flax, generally suffer from the electrical and mechanical instability in long-term wearing. In particular, fabrics on the human body have to endure heat variation, moisture evaporation from metabolic activities, and even the immersion with body sweat. To face the above challenges, here we report a wool-knitted fabric sensor treated with graphene oxide (GO) dyeing followed by l-ascorbic acid (l-AA) reduction (rGO). This rGO-based strain sensor is highly stretchable, washable, and durable with rapid sensing response. It exhibits excellent linearity with more than 20% elongation and, most importantly, withstand moisture from 30 to 90% (or even immersed with water) and still maintains good electrical and mechanical properties. We further demonstrate that, by integrating this proposed material with the near-field communication (NFC) system, a batteryless, wireless wearable body movement sensor can be constructed. This material can find wide use in smart garment applications.

Wearable Strain Sensors Using Light Transmittance Change of Carbon Nanotube-Embedded Elastomers with Microcracks

A number of flexible and stretchable strain sensors based on piezoresistive and capacitive principles have been recently developed. However, piezoresistive sensors suffer from poor long-term stability and considerable hysteresis of signals. On the other hand, capacitive sensors exhibit limited sensitivity and strong electromagnetic interference from the neighboring environment. In order to resolve these problems, a novel stretchable strain sensor based on the modulation of optical transmittance of carbon nanotube (CNT)-embedded Ecoflex is introduced in this paper. Within the film of multiwalled CNTs embedded in the Ecoflex substrate, the microcracks are propagated under tensile strain, changing the optical transmittance of the film. The proposed sensor exhibits good stretchability (ε ≈ 400%), high linearity (R² > 0.98) in the strain range of ε = 0-100%, excellent stability, high sensitivity (gauge factor ≈ 30), and small hysteresis (∼1.8%). The sensor was utilized to detect the bending of the finger and wrist for the control of a robot arm. Furthermore, the applications of this sensor to the real-time posture monitoring of the neck and to the detection of subtle human motions were demonstrated.

Development of a Biosensor Based on Graphene for Detection of Physiological Signals

At present, graphene has been widely used in flexible sensors, however, it is still a problem to prepare graphene-based sensors by a simple and low-cost method. In this paper, graphene nanoplatelets (GNPs) are prepared by thermal expansion method, and a capacitance plate is prepared by sealing a GNPs sheet with polyurethane (PU) medical film. Then two capacitor plates are overlapped each other, and the two sides are sealed with a transparent tape to form a GNPs capacitance sensor. In comparison with existing graphene-based sensors, the fabrication method of the GNPs capacitance sensor is simple and low-cost. What is more, the physiological signals can be measured effectively by the GNPs capacitance sensor. The sensor has been used to measure the signal of finger bending motion and pulse wave signal. The results show that the GNPs capacitance sensor is a promising sensor for effective measurement of physiological signals.

Highly Conductive PVA/Ag Coating by Aqueous in Situ Reduction and Its Stretchable Structure for Strain Sensor

Highly stretchable fiber-based strain sensor is essential to develop various applications in intelligent textiles, biomedical electronics, and integrated circuits. Although several fiber-based strain sensors have been reported, attaining the balance between excellent stretchability, high conductivity, and controllable sensitivity remains challenging. Herein, we present a facile approach for fabricating highly conductive, stretchable, and sensitive fiber strain sensors by synthesizing poly(vinyl alcohol)/Ag nanoparticle composite coating through aqueous in situ reduction on a stretchable fiber with a braided structure. The conductive coating with a flexible structure shows an ultrahigh conductivity of 120 903 S/cm. The unique braided structure and dense conductive Ag network enable the strain sensor to simultaneously exhibit 150% of strain sensing, controllable gauge factor from 1.85 to 8.14 within 65% strain, and a rapid response time of 75 ms. Meanwhile, long-term durability and low hysteresis are other initial features of the fiber-based strain sensor. Most importantly, the fiber-based strain sensor is capable of detecting human motions, including vocal cord vibration, finger movements, walking, and running, exhibiting significant potential in real-time monitoring and intelligent textiles.

Two-Sided Topological Architecture on a Monolithic Flexible Substrate for Ultrasensitive Strain Sensors

Flexible ultrasensitive strain sensors are highly desirable in view of their widespread applications in wearable electronics, health monitoring systems, and smart robots, where subtle strain detection is required. However, traditional fabrication of such sensors was done to prepare sensitive layers on bare or single-sided structural substrates, leading to limited sensitivity. Herein, a stretchable resistive-type strain sensor was demonstrated by self-assembling conductive networks onto a monolithic polydimethylsiloxane substrate with a two-sided topological design, for example, a sinusoid/auxetic binary architecture. The sensitivity of the obtained sensor was greatly improved by 22-fold as compared to the traditional counterpart with a bare substrate. The remarkably good agreement between the experimental results and finite element analysis predictions confirmed that the superior sensitivity is a synergistic effect of local strain enhancement derived from the topological structure on the foreside and an additional strain concentration and a reduced Poisson's ratio from the auxetic arrays on the backside. Furthermore, this sensor can withstand an extreme mechanical force (>750 N) because of the shear stiffening characteristic of the auxetic structure. Benefiting from the characteristics of ultrahigh sensitivity (gauge factor ∼1744 at 5%), low detection limit (<0.05%), and long-term durability (>500 loading cycles), this as-prepared sensor shows promise in practical applications of high-performance wearable electronics.

Ultrastretchable Conductive Polymer Complex as a Strain Sensor with a Repeatable Autonomous Self-Healing Ability

Wearable strain sensors are essential for the realization of applications in the broad fields of remote healthcare monitoring, soft robots, and immersive gaming, among many others. These flexible sensors should be comfortably adhered to the skin and capable of monitoring human motions with high accuracy, as well as exhibiting excellent durability. However, it is challenging to develop electronic materials that possess the properties of skin-compliant, elastic, stretchable, and self-healable. This work demonstrates a new regenerative polymer complex composed of poly(2-acrylamido-2-methyl-1-propanesulfonic acid), polyaniline, and phytic acid as a skin-like electronic material. It exhibits ultrahigh stretchability (1935%), repeatable autonomous self-healing ability (repeating healing efficiency >98%), quadratic response to strain ( R² > 0.9998), and linear response to flexion bending ( R² > 0.9994), outperforming current reported wearable strain sensors. The deprotonated polyelectrolyte, multivalent anion, and doped conductive polymer, under ambient conditions, synergistically construct a regenerative dynamic network of polymer complex cross-linked by hydrogen bonds and electrostatic interactions, which enables ultrahigh stretchability and repeatable self-healing. Sensitive strain-responsive geometric and piezoresistive mechanisms of the material owing to the homogeneous and viscoelastic nature provide excellent linear responses to omnidirectional tensile strain and bending deformations. Furthermore, this material is scalable and simple to process in an environmentally friendly manner, paving the way for the next-generation flexible electronics.

Highly Sensitive, Ultrastretchable Strain Sensors Prepared by Pumping Hybrid Fillers of Carbon Nanotubes/Cellulose Nanocrystal into Electrospun Polyurethane Membranes

Advanced flexible strain sensors for human motion detection and other potential use have attracted great attention in recent years. However, the preparation of strain sensor with both high sensitivity and large workable strain range remains a challenge. In this work, the carbon nanotube (CNT) suspensions with the assistance of cellulose nanocrystals (CNC) were directly pumped into the porous electrospun thermoplastic polyurethanes (TPU) membranes through a simple filtration process to prepare the flexible strain sensors in one step. The sensitivity and workable strain range of the strain sensors are tunable by changing the mass ratios of CNTs/CNC and the total amount of hybrid fillers. With increase in the total amount of fillers, a change of filler layer from droplet to completely continuous film was observed, resulting in a sharp increase of strain sensitivity. By combining the ultraelasticity of the TPU material and the high sensitivity of hybrid fillers, the strain sensor with large workable strain range (>500%) and high sensitivity (gauge factor = 321) was successfully prepared. Its applications in visual control and full-range human body motion detection were demonstrated, showing its tremendous potential applications in future intelligent electronics.

Heterogeneous Strain Distribution of Elastomer Substrates To Enhance the Sensitivity of Stretchable Strain Sensors

Stretchable strain sensors, which convert mechanical stimuli into electrical signals, largely fuel the growth of wearable bioelectronics due to the ubiquitous, health-related strain in biological systems. In contrast to rigid conventional strain sensors, stretchable strain sensors present advantages of conformality and stretchability, solving the mechanical mismatch between electronics and the human body. However, the great challenge of stretchable strain sensors lies in achieving high sensitivity, which is required for both signal fidelity and cost considerations. Recent advances to solve this sensitivity challenge have focused on material optimization, in search of the optimum combination of conductive active materials and elastomer substrates among a myriad of artificial or natural materials. However, high sensitivity with a gauge factor larger than 50 remains a grand challenge, especially within large-strain regions. Here we present heterogeneous strain distribution of elastomer substrates as a powerful strategy to significantly enhance the sensitivity of stretchable strain sensors. The theoretical foundation of this strategy is mathematically proven on the basis of Ohm's law in electrics and mechanics of materials. First, the extent of the sensitivity enhancement is proved to be determined by the local strain in resistance-testing segments of heterogeneous strain sensors. Next, the local strain is proved to be quantitatively decided by material properties such as section area and Young's modulus. Thus, the necessary and sufficient condition to achieve high sensitivity in heterogeneous strain sensors is that the Young's modulus reciprocal or section area reciprocal in the resistance-testing segment is larger than the mean value. This provides a theoretical design guideline to achieve high sensitivity via heterogeneous strain distribution. On the basis of this guideline, we systematically summarize concrete instances of heterogeneity-induced sensitivity improvement in stretchable strain sensors, in sequence of increasing dimensionality. A typical example of a one-dimensional heterogeneous strain sensor is a structured fiber with microbeads, where the varied section area along the fiber axis results in heterogeneous strain and sensitivity improvement. Two-dimensional heterogeneous sensors in the form of thin films contain thickness gradient sensors and auxetic mechanical metamaterial sensors. The former exhibit heterogeneous section area via the self-pinning method, while the latter show heterogeneity in both the strain direction and amplitude, leading to a 24-fold improvement in sensitivity. Three-dimensional strain sensors include rationally structured sensors for out-of-plane force detection and asymmetric active materials in electronic whiskers. The resultant enhanced sensitivity in these heterogeneous strain sensors is beneficial for applications such as continuous health monitoring, biomedical diagnostics, and replacement prosthetics, taking advantage of augmented detection accuracy and declined device cost. Finally, we discuss possible future work in exploiting heterogeneous strain distributions, involving extended methodology to achieve heterogeneity, employing suppressed strain for stretchable electrodes, cyclic durability for long-term applications, and multifunctional system-level integration. We believe that this strategy of using heterogeneous strain distribution to enhance sensitivity can strongly promote the development of stretchable strain sensors for both practical and theoretical requirements.

Highly sensitive strain sensors based on hollow packaged silver nanoparticle-decorated three-dimensional graphene foams for wearable electronics

Silver nanoparticle-decorated three-dimensional graphene foams were prepared and packaged with half-cured PMDS films, forming a special “hollow packaged” structure that exhibited high sensitivity for wearable strain sensor applications.

Multifunctional Mechanical Sensors for Versatile Physiological Signal Detection

Recently, flexible and wearable mechanical sensors have attracted great attention because of their potential applications in monitoring various physiological signals. However, conventional mechanical sensors rarely have both pressure and strain sensing abilities that can meet the demands of both subtle and large human motion detection. Besides, the mechanical sensors with tunable sensitivity or measuring range are also essential for their practical applications. Herein, the graphene ink dip-coating method with merits of time saving, low cost, and large scale was used to fabricate the foam-structured graphene sensors with both pressure and strain sensing performance. Because of high elasticity of styrene butadiene rubber (SBR) substrates and stacked graphene flakes, the tunable mechanical sensors exhibit a high gauge factor (GF) and large measuring range for specific human motion detection. The pressure sensor shows a GF of 2.02 kPa^-1 with a pressure range up to 172 kPa, and the strain sensor displays a GF of 250 with a strain range up to 86%. On the one hand, various detections of subtle vital signals with small strain change were demonstrated by the pressure sensor because of its flexibility and high sensitivity. On another hand, the strain sensor with large strain change shows excellent ability to detect various large human motions including the bending of neck, finger, wrist, and knee. Interestingly, both the pressure sensor and strain sensor exhibit great capability for recognizing 26 letters written by hand. The working mechanism based on the contact area variation was also investigated by the morphology evolution and resistance model. We suppose that the foam-structured graphene mechanical sensors would be promising in wearable electronics for human healthcare and activity monitoring in the future.

Graphene Textile Strain Sensor with Negative Resistance Variation for Human Motion Detection

Recently, wearable devices have been attracting significantly increased interest in human motion detection and human physiological signal monitoring. Currently, it is still a great challenge to fabricate strain sensors with high performance and good fit to the human body. In this work, we fabricated a close-fitting and wearable graphene textile strain sensor based on a graphene textile without polymer encapsulation. Graphene oxide acts as a colorant to dye the polyester fabric and is reduced at high temperature, which endows the graphene textile strain sensor with excellent performance. Compared with the previously reported strain sensors, our strain sensor exhibits a distinctive negative resistance variation with increasing strain. In addition, the sensor also demonstrates fascinating performance, including high sensitivity, long-term stability, and great comfort. Based on its superior performance, the graphene textile strain sensor can be knitted on clothing for detecting both subtle and large human motions, showing the tremendous potential for applications in wearable electronics.

3D Printing Technologies for Flexible Tactile Sensors toward Wearable Electronics and Electronic Skin

3D printing has attracted a lot of attention in recent years. Over the past three decades, various 3D printing technologies have been developed including photopolymerization-based, materials extrusion-based, sheet lamination-based, binder jetting-based, power bed fusion-based and direct energy deposition-based processes. 3D printing offers unparalleled flexibility and simplicity in the fabrication of highly complex 3D objects. Tactile sensors that emulate human tactile perceptions are used to translate mechanical signals such as force, pressure, strain, shear, torsion, bend, vibration, etc. into electrical signals and play a crucial role toward the realization of wearable electronics and electronic skin. To date, many types of 3D printing technologies have been applied in the manufacturing of various types of tactile sensors including piezoresistive, capacitive and piezoelectric sensors. This review attempts to summarize the current state-of-the-art 3D printing technologies and their applications in tactile sensors for wearable electronics and electronic skin. The applications are categorized into five aspects: 3D-printed molds for microstructuring substrate, electrodes and sensing element; 3D-printed flexible sensor substrate and sensor body for tactile sensors; 3D-printed sensing element; 3D-printed flexible and stretchable electrodes for tactile sensors; and fully 3D-printed tactile sensors. Latest advances in the fabrication of tactile sensors by 3D printing are reviewed and the advantages and limitations of various 3D printing technologies and printable materials are discussed. Finally, future development of 3D-printed tactile sensors is discussed.