Large-Area, Crosstalk-Free, Flexible Tactile Sensor Matrix Pixelated by Mesh Layers

Toward an AI Era: Advances in Electronic Skins

Electronic skins (e-skins) have seen intense research and rapid development in the past two decades. To mimic the capabilities of human skin, a multitude of flexible/stretchable sensors that detect physiological and environmental signals have been designed and integrated into functional systems. Recently, researchers have increasingly deployed machine learning and other artificial intelligence (AI) technologies to mimic the human neural system for the processing and analysis of sensory data collected by e-skins. Integrating AI has the potential to enable advanced applications in robotics, healthcare, and human-machine interfaces but also presents challenges such as data diversity and AI model robustness. In this review, we first summarize the functions and features of e-skins, followed by feature extraction of sensory data and different AI models. Next, we discuss the utilization of AI in the design of e-skin sensors and address the key topic of AI implementation in data processing and analysis of e-skins to accomplish a range of different tasks. Subsequently, we explore hardware-layer in-skin intelligence before concluding with an analysis of the challenges and opportunities in the various aspects of AI-enabled e-skins.

Nanoengineering Ultrathin Flexible Pressure Sensors with Superior Sensitivity and Wide Range via Nanocomposite Structures

Flexible pressure sensors have attracted great interest due to their bendable, stretchable, and lightweight characteristics compared to rigid pressure sensors. However, the contradictions among sensitivity, detection limit, thickness, and detection range restrict the performance of flexible pressure sensors and the scope of their applications, especially for scenarios requiring conformal fitting, such as rough surfaces such as the human skin. This paper proposes a novel flexible pressure sensor by combining the nanoengineering strategy and nanocomposite structures. The nanoengineering strategy utilizes the bending deformation of nanofilm instead of the compression of the active layer to achieve super high sensitivity and low detection limit; meanwhile, the nanocomposite structures introduce distributed microbumps that delay the adhesion of nanofilm to enlarge the detection range. As a result, this device not only ensures an ultrathin thickness of 1.6 μm and a high sensitivity of 84.29 kPa-1 but also offers a large detection range of 20 kPa and an ultralow detection limit of 0.07 Pa. Owing to the ultrathin thickness as well as high performance, this device promotes applications in detecting fingertip pressure, flexible mechanical gripping, and so on, and demonstrates significant potential in wearable electronics, human-machine interaction, health monitoring, and tactile perception. This device offers a strategy to resolve the conflicts among thickness, sensitivity, detection limit, and detection range; therefore, it will advance the development of flexible pressure sensors and contribute to the community and other related research fields.

Bioinspired Suspended Sensing Membrane Array with Modulable Wedged-Conductive Channels for Crosstalk-Free and High-Resolution Detection

High spatial-resolution detection is essential for biomedical applications and human-machine interaction. However, as the sensor array density increases, the miniaturization will lead to interference between adjacent units and deterioration in sensing performance. Here, inspired by the cochlea's sensing structure, a high-density flexible pressure sensor array featuring with suspended sensing membrane with sensitivity-enhanced customized channels is presented for crosstalk-free and high-resolution detection. By imitating the basilar membrane attached to spiral ligaments, a sensing membrane is fixed onto a high-stiffness substrate with cavities, forming a stable braced isolation to provide an excellent crosstalk-free capability (crosstalk coefficient: 47.24 dB) with high-density integration (100 units within 1 cm2). Similar to the opening of ion channels in hair cells, the wedge-type expansion of the embedded cracks introduced by stress concentration structures enables a high sensitivity (0.19 kPa-1) and a large measuring range (400 kPa). Finally, it demonstrates promising applications in distributed displays and the condition monitoring of medical-surgical intubation.

Crosstalk-Free Position Mapping for One-Step Reconstruction of Surface Topological Information via Eigenfrequency-Registered Wearable Interface

Exploring flexible tactile sensors capable of recognizing surface information is significant for the development of virtual reality, artificial intelligence, soft robotics, and human-machine interactions (HMI). However, it is still a challenge for current tactile sensors to efficiently recognize the surface pattern information while maintaining the simplicity of the overall system. In this study, cantilever beam-like magnetized micropillars (MMPs) with height gradients are assembled as a position-registered array for rapid recognition of surface pattern information. After crossing the surface location with convex patterns, the deformed MMPs undergo an intrinsic oscillating process to induce damped electrical signals, which can then be converted to a frequency domain for eigenfrequency extraction. Via precisely defining the specific eigenfrequencies of different MMPs, position mapping is realized in crosstalk-free behavior even though all signals are processed by one communication channel and a pair of electrodes. With a customized LabVIEW program, the surface information (e.g., letters, numbers, and Braille) can be accurately reconstructed by the frequency sequence produced in a single scanning procedure. We expect that the proposed interface can be a convenient and powerful platform for intelligent surface information perception and an HMI system in the future.

Outstanding Synergy of Sensitivity and Linear Range Enabled by Multigradient Architectures

Flexible pressure sensors are devices that mimic the sensory capabilities of natural human skin and enable robots to perceive external stimuli. One of the main challenges is maintaining high sensitivity over a broad linear pressure range due to poor structural compressibility. Here, we report a flexible pressure sensor with an ultrahigh sensitivity of 153.3 kPa-1 and linear response over an unprecedentedly broad pressure range from 0.0005 to 1300 kPa based on interdigital-shaped, multigradient architectures, featuring modulus, conductivity, and microstructure gradients. Such multigradient architectures and interdigital-shaped configurations enable effective stress transfer and conductivity regulation, evading the pressure sensitivity-linear range trade-off dilemma. Together with high pressure resolution, high frequency response, and good reproducibility over the ultrabroad linear range, proof-of-concept applications such as acoustic wave detection, high-resolution pressure measurement, and healthcare monitoring in diverse scenarios are demonstrated.

Nonlinearity synergy: An elegant strategy for realizing high-sensitivity and wide-linear-range pressure sensing

Flexible pressure sensors are indispensable components in various applications such as intelligent robots and wearable devices, whereas developing flexible pressure sensors with both high sensitivity and wide linear range remains a great challenge. Here, we present an elegant strategy to address this challenge by taking advantage of a pyramidal carbon foam array as the sensing layer and an elastomer spacer as the stiffness regulator, realizing an unprecedentedly high sensitivity of 24.6 kPa-1 and an ultra-wide linear range of 1.4 MPa together. Such a wide range of linearity is attributed to the synergy between the nonlinear piezoresistivity of the sensing layer and the nonlinear elasticity of the stiffness regulator. The great application potential of our sensor in robotic manipulation, healthcare monitoring, and human-machine interface is demonstrated. Our design strategy can be extended to the other types of flexible sensors calling for both high sensitivity and wide-range linearity, facilitating the development of high-performance flexible pressure sensors for intelligent robotics and wearable devices.

All Resistive Pressure-Temperature Bimodal Sensing E-Skin for Object Classification

Electronic skin (E-skin) with multimodal sensing ability demonstrates huge prospects in object classification by intelligent robots. However, realizing the object classification capability of E-skin faces severe challenges in multiple types of output signals. Herein, a hierarchical pressure-temperature bimodal sensing E-skin based on all resistive output signals is developed for accurate object classification, which consists of laser-induced graphene/silicone rubber (LIG/SR) pressure sensing layer and NiO temperature sensing layer. The highly conductive LIG is employed as pressure-sensitive material as well as the interdigital electrode. Benefiting from high conductivity of LIG, pressure perception exhibits an excellent sensitivity of -34.15 kPa-1 . Meanwhile, a high temperature coefficient of resistance of -3.84%°C-1 is obtained in the range of 24-40 °C. More importantly, based on only electrical resistance as the output signal, the bimodal sensing E-skin with negligible crosstalk can simultaneously achieve pressure and temperature perception. Furthermore, a smart glove based on this E-skin enables classifying various objects with different shapes, sizes, and surface temperatures, which achieves over 92% accuracy under assistance of deep learning. Consequently, the hierarchical pressure-temperature bimodal sensing E-skin demonstrates potential application in human-machine interfaces, intelligent robots, and smart prosthetics.

Recent Advances in Flexible Piezoresistive Arrays: Materials, Design, and Applications

Spatial distribution perception has become an important trend for flexible pressure sensors, which endows wearable health devices, bionic robots, and human-machine interactive interfaces (HMI) with more precise tactile perception capabilities. Flexible pressure sensor arrays can monitor and extract abundant health information to assist in medical detection and diagnosis. Bionic robots and HMI with higher tactile perception abilities will maximize the freedom of human hands. Flexible arrays based on piezoresistive mechanisms have been extensively researched due to the high performance of pressure-sensing properties and simple readout principles. This review summarizes multiple considerations in the design of flexible piezoresistive arrays and recent advances in their development. First, frequently used piezoresistive materials and microstructures are introduced in which various strategies to improve sensor performance are presented. Second, pressure sensor arrays with spatial distribution perception capability are discussed emphatically. Crosstalk is a particular concern for sensor arrays, where mechanical and electrical sources of crosstalk issues and the corresponding solutions are highlighted. Third, several processing methods are also introduced, classified as printing, field-assisted and laser-assisted fabrication. Next, the representative application works of flexible piezoresistive arrays are provided, including human-interactive systems, healthcare devices, and some other scenarios. Finally, outlooks on the development of piezoresistive arrays are given.

Machine Learning-Enhanced Flexible Mechanical Sensing

To realize a hyperconnected smart society with high productivity, advances in flexible sensing technology are highly needed. Nowadays, flexible sensing technology has witnessed improvements in both the hardware performances of sensor devices and the data processing capabilities of the device's software. Significant research efforts have been devoted to improving materials, sensing mechanism, and configurations of flexible sensing systems in a quest to fulfill the requirements of future technology. Meanwhile, advanced data analysis methods are being developed to extract useful information from increasingly complicated data collected by a single sensor or network of sensors. Machine learning (ML) as an important branch of artificial intelligence can efficiently handle such complex data, which can be multi-dimensional and multi-faceted, thus providing a powerful tool for easy interpretation of sensing data. In this review, the fundamental working mechanisms and common types of flexible mechanical sensors are firstly presented. Then how ML-assisted data interpretation improves the applications of flexible mechanical sensors and other closely-related sensors in various areas is elaborated, which includes health monitoring, human-machine interfaces, object/surface recognition, pressure prediction, and human posture/motion identification. Finally, the advantages, challenges, and future perspectives associated with the fusion of flexible mechanical sensing technology and ML algorithms are discussed. These will give significant insights to enable the advancement of next-generation artificial flexible mechanical sensing.

Flexible and Stretchable Carbon-Based Sensors and Actuators for Soft Robots

In recent years, the emergence of low-dimensional carbon-based materials, such as carbon dots, carbon nanotubes, and graphene, together with the advances in materials science, have greatly enriched the variety of flexible and stretchable electronic devices. Compared with conventional rigid devices, these soft robotic sensors and actuators exhibit remarkable advantages in terms of their biocompatibility, portability, power efficiency, and wearability, thus creating myriad possibilities of novel wearable and implantable tactile sensors, as well as micro-/nano-soft actuation systems. Interestingly, not only are carbon-based materials ideal constituents for photodetectors, gas, thermal, triboelectric sensors due to their geometry and extraordinary sensitivity to various external stimuli, but they also provide significantly more precise manipulation of the actuators than conventional centimeter-scale pneumatic and hydraulic robotic actuators, at a molecular level. In this review, we summarize recent progress on state-of-the-art flexible and stretchable carbon-based sensors and actuators that have creatively added to the development of biomedicine, nanoscience, materials science, as well as soft robotics. In the end, we propose the future potential of carbon-based materials for biomedical and soft robotic applications.

Black phosphorous-based human-machine communication interface

Assistive technology involving auditory feedback is generally utilized by those who are visually impaired or have speech and language difficulties. Therefore, here we concentrate on an auditory human-machine interface that uses audio as a platform for conveying information between visually or speech-disabled users and society. We develop a piezoresistive tactile sensor based on a black phosphorous and polyaniline (BP@PANI) composite by the facile chemical oxidative polymerization of aniline on cotton fabric. Taking advantage of BP's puckered honeycomb lattice structure and superior electrical properties as well as the vast wavy fabric surface, this BP@PANI-based tactile sensor exhibits excellent sensitivity, low-pressure sensitivity, reasonable response time, and good cycle stability. For a real-world application, a prototype device employs six BP@PANI tactile sensors that correspond to braille characters and can convert pressed text into audio on reading or typing to assist visually or speech-disabled persons. Overall, this research offers promising insight into the material candidates and strategies for the development of auditory feedback devices based on layered and 2D materials for human-machine interfaces.

Carbon nanotube-graphene hybrids for soft electronics, sensors, and actuators

Soft devices that are mechanically flexible and stretchable are considered as the building blocks for various applications ranging from wearable devices to robotics. Among the many candidate materials for constructing soft devices, carbon nanomaterials such as carbon nanotubes (CNTs) and graphene have been actively investigated owing to their outstanding characteristics, including their intrinsic flexibility, tunable conductivity, and potential for large-area processing. In particular, hybrids of CNTs and graphene can improve the performance of soft devices and provide them with novel capabilities. In this review, the advances in CNT-graphene hybrid-based soft electrodes, transistors, pressure and strain sensors, and actuators are discussed, highlighting the performance improvements of these devices originating from the synergistic effects of the hybrids of CNT and graphene. The integration of multidimensional heterogeneous carbon nanomaterials is expected to be a promising approach for accelerating the development of high-performance soft devices. Finally, current challenges and future opportunities are summarized, from the processing of hybrid materials to the system-level integration of multiple components.

Dual-Scale Porous Composite for Tactile Sensor with High Sensitivity over an Ultrawide Sensing Range

Porous structures have been utilized in tactile sensors to improve sensitivity owing to their excellent deformability. Recently, tactile sensors using porous structures have been used in practical applications, such as bio-signal monitoring. However, highly sensitive responses are limited to the low-pressure range, and their sensitivity significantly decreases in a higher-pressure range. Several approaches for developing tactile sensors with high sensitivity overing a wide pressure range have been proposed; however, achieving high sensitivity and wide sensing range remains a crucial challenge. This report presents a carbon nanotube (CNT)-coated CNT-polydimethylsiloxane (PDMS) composite having dual-scale pores for tactile sensors with high sensitivity over a wide pressure range. The porous polymer frame formed with dense pores of dual sizes facilitates the closure of large and small pores at low and high pressures, respectively. This results in an apparent increase in the number of contact points between the CNT-CNT at the pores even under a wide pressure range. Furthermore, the piezoresistivity of the CNT-PDMS composite contributes to achieving a high sensitivity of the tactile sensor over a wide pressure range. Based on these mechanisms, various human movements over a broad pressure spectrum are monitored to investigate the practical usefulness of the sensor.

Crosstalk-Free, High-Resolution Pressure Sensor Arrays Enabled by High-Throughput Laser Manufacturing

Simultaneously achieving high spatial resolution and low crosstalk interference has been a fundamental challenge for flexible pressure sensor arrays. Here the authors present a high-resolution flexible pressure sensor array fabricated through a two-step laser manufacturing process, where individual sensing pixels and their interconnects are sequentially defined by laser-induced graphenization and ablation to minimize crosstalk interferences. The geometry of the interconnects is optimized through theoretical modeling and experimental validation. Characterization results show that the new device design induces a remarkable reduction of the crosstalk coefficient, from -8.21 to -43.63 dB, of the 0.7 mm-resolution sensor arrays, and the crosstalk suppression is particularly beneficial for application scenarios involving pressure sensing on soft surfaces (e.g., human skin and organs). Applications of the sensor array in tactile pattern recognition and minimally-invasive cancer surgery are demonstrated.

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.