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Flexible tactile sensors with multifunctional sensing functions have attracted much attention due to their wide applications in artificial limbs, intelligent robots, human‐machine interfaces, and health monitoring devices. Here, a multifunctional flexible tactile sensor based on resistive effect for simultaneous sensing of pressure and temperature is reported. The sensor features a simple design with patterned metal film on a soft substrate with cavities and protrusions. The decoupling of pressure and temperature sensing is achieved by the reasonable arrangement of metal layers in the patterned metal film. Systematically experimental and numerical studies are carried out to reveal the multifunctional sensing mechanism and show that the proposed sensor exhibits good linearity, fast response, high stability, good mechanical flexibility, and good microfabrication compatibility. Demonstrations of the multifunctional flexible tactile sensor to monitor touch, breathing, pulse and objects grabbing/releasing in various application scenarios involving coupled temperature/pressure stimuli illustrate its excellent capability of measuring pressure and temperature simultaneously. These results offer an effective tool for multifunctional sensing of pressure and temperature and create engineering opportunities for applications of wearable health monitoring and human‐machine interfaces. [ABSTRACT FROM AUTHOR]

The emerging field of flexible tactile sensing systems, equipped with multi-physical tactile sensing capabilities, holds vast potential across diverse domains such as medical monitoring, robotics, and human–computer interaction. In response to the prevailing challenges associated with the limited integration and sensitivity of flexible tactile sensors, this paper introduces a versatile tactile sensing system capable of concurrently monitoring temperature and pressure. The temperature sensor employs carbon nanotube/graphene conductive paste as its sensitive material, while the pressure sensor integrates an ionic gel containing boron nitride as its sensitive layer. Through the application of cost-effective screen printing technology, we have successfully manufactured a flexible dual-mode sensor with exceptional performance, featuring high sensitivity (804.27 kPa − 1 ), a broad response range (50 kPa), rapid response time (17 ms), and relaxation time (34 ms), alongside exceptional durability over 5000 cycles. Furthermore, the resistance temperature coefficient of the sensor within the temperature range of 12.5 °C to 93.7 °C is −0.17% °C−1. The designed flexible dual-mode tactile sensing system enables the real-time detection of pressure and temperature information, presenting an innovative approach to electronic skin with multi-physical tactile sensing capabilities. [ABSTRACT FROM AUTHOR]

The past decades have seen the rapid development of tactile sensors in material, fabrication, and mechanical structure design. The advancement of tactile sensors has heightened the expectation of sensor functions, and thus put forward a higher demand for data processing. However, conventional analysis techniques have not kept pace with the tactile sensor development and still suffer from some severe drawbacks, like cumbersome models, poor efficiency, and expensive costs. Machine learning, with its prominent ability for big data analysis and fast processing speed, can offer many possibilities for tactile data analysis. Herein, the machine learning techniques employed for processing tactile signals are reviewed. Supervised learning and unsupervised learning for analog signals are covered, and processing spike signals with machine learning are summarized. Furthermore, the applications in robotic tactile perception and human activity monitoring are presented. Finally, the current challenges and future prospects in sensors, data, algorithms, and benchmarks are discussed. [ABSTRACT FROM AUTHOR]

In recent years, extensive research has been conducted on the development of high-performance flexible tactile sensors, pursuing the next generation of highly intelligent electronics with diverse potential applications in self-powered wearable sensors, human–machine interactions, electronic skin, and soft robotics. Among the most promising materials that have emerged in this context are functional polymer composites (FPCs), which exhibit exceptional mechanical and electrical properties, enabling them to be excellent candidates for tactile sensors. Herein, this review provides a comprehensive overview of recent advances in FPCs-based tactile sensors, including the fundamental principle, the necessary property parameter, the unique device structure, and the fabrication process of different types of tactile sensors. Examples of FPCs are elaborated with a focus on miniaturization, self-healing, self-cleaning, integration, biodegradation, and neural control. Furthermore, the applications of FPC-based tactile sensors in tactile perception, human–machine interaction, and healthcare are further described. Finally, the existing limitations and technical challenges for FPCs-based tactile sensors are briefly discussed, offering potential avenues for the development of electronic products. [ABSTRACT FROM AUTHOR]

Herein, a multimodal tactile sensing module that can improve the dexterous manipulation capabilities of robots with parallel grippers is reported. The tactile sensor consists of a 4 × 4 matrix 3‐axis force sensor array (with spacings of 2 mm) and a single‐temperature sensor. The tactile sensor uses inorganic silicon and gold as materials for the detection of strain and temperature and a polymer‐based elastomer to encapsulate the sensing layer. The sensing module is equipped with a readout circuitry for signal processing. Within the measurable force range (≈1.5 N) of the sensor cell, a prototype module exhibits a repeatability error within 2%, a hysteresis error within 3%, and a resolution as small as 10 mN. Furthermore, each sensor cell independently measures 3‐axis forces with a cross‐talk error of approximately 3%. The temperature sensor exhibits linear output properties in the approximate range of 5–75 °C. Experiments are performed by mounting the module on a parallel gripper to grasp a paper cup and a reflex hammer toy. According to the experimental results, the sensor can accurately detect the state of contact with an object by analyzing three tactile modalities (i.e., 3‐axis force distribution, vibration, and temperature). [ABSTRACT FROM AUTHOR]

Flexible sensors are the essential foundations of pressure sensing, microcomputer sensing systems, and wearable devices. The flexible tactile sensor can sense stimuli by converting external forces into electrical signals. The electrical signals are transmitted to a computer processing system for analysis, realizing real-time health monitoring and human motion detection. According to the working mechanism, tactile sensors are mainly divided into four types—piezoresistive, capacitive, piezoelectric, and triboelectric tactile sensors. Conventional silicon-based tactile sensors are often inadequate for flexible electronics due to their limited mechanical flexibility. In comparison, polymeric nanocomposites are flexible and stretchable, which makes them excellent candidates for flexible and wearable tactile sensors. Among the promising polymers, conjugated polymers (CPs), due to their unique chemical structures and electronic properties that contribute to their high electrical and mechanical conductivity, show great potential for flexible sensors and wearable devices. In this paper, we first introduce the parameters of pressure sensors. Then, we describe the operating principles of resistive, capacitive, piezoelectric, and triboelectric sensors, and review the pressure sensors based on conjugated polymer nanocomposites that were reported in recent years. After that, we introduce the performance characteristics of flexible sensors, regarding their applications in healthcare, human motion monitoring, electronic skin, wearable devices, and artificial intelligence. In addition, we summarize and compare the performances of conjugated polymer nanocomposite-based pressure sensors that were reported in recent years. Finally, we summarize the challenges and future directions of conjugated polymer nanocomposite-based sensors. [ABSTRACT FROM AUTHOR]

Recent advancement in wearable and robot-assisted healthcare technology gives rise to the demand for smart interfaces that allow more efficient human-machine interaction. In this paper, a hydrogel-based soft sensor for subtle touch detection is proposed. Adopting the working principle of a biomedical imaging technology known as electrical impedance tomography (EIT), the sensor produces images that display the electrical conductivity distribution of its sensitive region to enable touch detection. The sensor was made from a natural gelatin hydrogel whose electrical conductivity is considerably less than that of human skin. The low conductivity of the sensor enabled a touch-detection mechanism based on a novel short-circuiting approach, which resulted in the reconstructed images being predominantly affected by the electrical contact between the sensor and fingertips, rather than the conventionally used piezoresistive response of the sensing material. The experimental results indicated that the proposed sensor was promising for detecting subtle contacts without the necessity of exerting a noticeable force on the sensor. [ABSTRACT FROM AUTHOR]

Nature has proved that multiple sense and processing capabilities are critical for target recognition and race survival. As such, advanced robots that perform missions in an unstructured environment highly need organism‐similar multimodal sensing and processing systems for sophisticated unstructured environmental stimuli. Herein, recent progress in multimodal sensing and processing systems for advanced robotics is reviewed. Multimodal sensors including tactile sensors that capture surface properties of objects (i.e., thermal conductivity, temperature, softness, and electron affinity), visual sensors that capture the color and size of objects, and gas sensors that capture object smell are summarized. The multimodal data fusion algorithms that process multimodal signals from multimodal sensors to achieve object recognition and decision making are also presented. The challenges and future development of multimodal sensors and data fusion algorithms are further discussed. Advances in these areas open new avenues for advanced robotics applications in human–robot collaboration, rescue missions, garbage sorting, and intelligent prosthetics. [ABSTRACT FROM AUTHOR]

Nature has proved that multiple sense and processing capabilities are critical for target recognition and race survival. As such, advanced robots that perform missions in an unstructured environment highly need organism‐similar multimodal sensing and processing systems for sophisticated unstructured environmental stimuli. Herein, recent progress in multimodal sensing and processing systems for advanced robotics is reviewed. Multimodal sensors including tactile sensors that capture surface properties of objects (i.e., thermal conductivity, temperature, softness, and electron affinity), visual sensors that capture the color and size of objects, and gas sensors that capture object smell are summarized. The multimodal data fusion algorithms that process multimodal signals from multimodal sensors to achieve object recognition and decision making are also presented. The challenges and future development of multimodal sensors and data fusion algorithms are further discussed. Advances in these areas open new avenues for advanced robotics applications in human–robot collaboration, rescue missions, garbage sorting, and intelligent prosthetics.

The development of pressure sensors of high sensitivity and stable robustness over a broad range is indispensable for the future progress of electronic skin applicable to the detection of normal and shear pressures of various dynamic human motions. Herein, we present a flexible capacitive tactile sensing array that incorporates a porous dielectric layer with micro-patterned structures on the surface to enable the sensitive detection of normal and shear pressures. The proposed sensing array showed great pressure-sensing performance in the experiments, with a broad sensing range from several kPa to 150 kPa of normal pressure and 20 kPa of shear pressure. Sensitivities of 0.54%/kPa at 10 kPa and below, 0.45%/kPa between 10 kPa and 80 kPa, and 0.12%/kPa at 80 kPa and above were achieved for normal pressures. Meanwhile, for shear pressures, sensitivities up to 1.14%/kPa and 1.08%/kPa in x and y directions, respectively, and below 10 kPa, 0.73%/kPa, and 0.75%/kPa under shear pressure over 10 kPa were also validated. The performance of the finger-attached sensing array was also demonstrated, demonstrating which was a potential electronic skin to use in all kinds of wearable devices, including prosthetic hands, surgical robots, and other pressure monitoring systems. [ABSTRACT FROM AUTHOR]

One major challenge in upper limb prostheses is providing sensory feedback to amputees. Reproducing the spiking patterns of human primary tactile afferents can be considered as the first step for this challenging problem. In this study, a novel biomimetic circuit for SA-I and RA-I afferents is proposed to functionally replicate the spiking response of the biological tactile afferents to indentation stimuli. The circuit has been designed, laid out, and simulated in TSMC 180nm CMOS technology with a 1.8V supply voltage. A pair of SA-I and RA-I afferent circuits consume $3.5\mu \text{W}$ of power. The occupied silicon area is $180\mu \text{m}\,\,\times 220\mu \text{m}$ for 32 afferents. To provide the inputs for circuit testing, a patch of skin with a grid of mechanoreceptors is simulated and tested by an edge stimulus presented at different orientations. Experimental data are collected using indentation of 3D-printed edges at different orientations on a tactile sensor mounted on a robotic arm. Inspired by innervation patterns observed in biology, the artificial afferents are connected to several neighboring mechanoreceptors with different weights to form complex receptive fields which cover the entire mechanoreceptor grid. Machine learning algorithms are applied offline to classify the edge orientations based on the pattern of neural responses. Our results show that the complex receptive fields arising from the innervation pattern led to smaller circuit area and lower power consumption, while facilitating data encoding from high-resolution sensors. The proposed biomimetic circuit and tactile encoding example demonstrate potential applications in modern tactile sensing modules for developing novel bio-robotic and prosthetic technologies. [ABSTRACT FROM AUTHOR]

Electronic skins are essential for real-time health monitoring and tactile perception in robots. Although the use of soft elastomers and microstructures have improved the sensitivity and pressure-sensing range of tactile sensors, the intrinsic viscoelasticity of soft polymeric materials remains a long-standing challenge resulting in cyclic hysteresis. This causes sensor data variations between contact events that negatively impact the accuracy and reliability. Here, we introduce the Tactile Resistive Annularly Cracked E-Skin (TRACE) sensor to address the inherent trade-off between sensitivity and hysteresis in tactile sensors when using soft materials. We discovered that piezoresistive sensors made using an array of three-dimensional (3D) metallic annular cracks on polymeric microstructures possess high sensitivities (> 107 Ω ⋅ kPa-1), low hysteresis (2.99 ± 1.37%) over a wide pressure range (0-20 kPa), and fast response (400 Hz). We demonstrate that TRACE sensors can accurately detect and measure the pulse wave velocity (PWV) when skin mounted. Moreover, we show that these tactile sensors when arrayed enabled fast reliable one-touch surface texture classification with neuromorphic encoding and deep learning algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we propose a set of novel tactile descriptors to enable robotic systems to extract robust tactile information during tactile object explorations, regardless of the number of the tactile sensors, sensing technologies, type of exploratory movements, and duration of the objects’ surface exploration. The performance and robustness of the tactile descriptors are verified by testing on four different sensing technologies (dynamic pressure sensors, accelerometers, capacitive sensors, and impedance electrode arrays) with two robotic platforms (one anthropomorphic hand and one humanoid), and with a large set of objects and materials. Using our proposed tactile descriptors, the Shadow Hand, which has multimodal robotic skin on its fingertips, successfully classified 120 materials (100% accuracy) and 30 in-hand objects (98% accuracy) with regular and irregular textural structure by executing human-like active exploratory movements on their surface. The robustness of the proposed descriptors was assessed further during the large object discrimination with a humanoid. With a large sensing area on its upper body, the humanoid classified 120 large objects with multiple weights and various textures while the objects slid between its sensitive hands, arms, and chest. The achieved 90% recognition rate shows that the proposed tactile descriptors provided robust tactile information from the large number of tactile signals for identifying large objects via their surface texture regardless of their weight. [ABSTRACT FROM AUTHOR]

This article presents a sensor for detecting the distribution of forces on a surface. The device with nine buttons consisted of an elastomer-based layer as a touch interface resting on a substrate of patterned metallized paper. The elastomer-based layer included a three-by-three array of deformable, hemispherical elements/reliefs, facing down toward an array of interdigitated capacitive sensing units on patterned metallized paper. Each hemispherical element is 20 mm in diameter and 8 mm in height. When a user applied pressure to the elastomer-based layer, the contact area between the hemispherical elements and the interdigitated capacitive sensing units increased with the deformation of the hemispherical elements. To enhance the sensitivity of the sensors, embedded particles of hydrogel in the elastomer-based layer increased the measured electrical responses. The measured capacitance increased because the effective dielectric permittivity of the hydrogel was greater than that of air. Electromechanical characterization verified that the hydrogel-filled elastomer was more sensitive to force at a low range of loads (23.4 pF/N) than elastomer alone without embedded hydrogel (3.4 pF/N), as the hydrogel reduced the effective elastic modulus of the composite material by a factor of seven. A simple demonstration suggests that the force-sensing array has the potential to contribute to wearable and soft robotic devices. [ABSTRACT FROM AUTHOR]

A tactile sensor is an indispensable component for electronic skin, mimicking the sensing function of organism skin. Various sensing materials and microstructures have been adopted in the fabrication of tactile sensors. Herein, we propose a highly sensitive flexible tactile sensor composed of nanocomposites with pyramid and irregularly rough microstructures and implement a comparison of piezoresistive properties of nanocomposites with varying weight proportions of multi-wall nanotubes and carbon black particles. In addition to the simple and low-cost fabrication method, the tactile sensor can reach high sensitivity of 3.2 kPa−1 in the range of

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.

In the field of safety and communication of human-robot interaction (HRI), using large-scale electronic skin will be the tendency in the future. The force-sensitive piezoresistive material is the key for piezoresistive electronic skin. In this paper, a non-array large scale piezoresistive tactile sensor and its corresponding calibration methods were presented. Because of the creep inconsistency of large scale piezoresistive material, a creep tracking compensation method based on K-means clustering and fuzzy pattern recognition was proposed to improve the detection accuracy. With the compensated data, the inconsistency and nonlinearity of the sensor was calibrated. The calibration process was divided into two parts. The hierarchical clustering algorithm was utilized firstly to classify and fuse piezoresistive property of different regions over the whole sensor. Then, combining the position information, the force detection model was constructed by Back-Propagation (BP) neural network. At last, a novel flexible tactile sensor for detecting contact position and force was designed as an example and tested after being calibrated. The experimental results showed that the calibration methods proposed were effective in detecting force, and the detection accuracy was improved. [ABSTRACT FROM AUTHOR]

Remarkable research efforts have been devoted to replicate the tactile sensitivity of human skin. Unfortunately, so far flexible pressure sensors reported barely fit the tactile requirements for fingertips, which could endure a pressure over 100 kPa and also can sense a gentle touch. It is vital to develop flexible pressure sensors which can ensure high sensitivity and wide operation range simultaneously, to satisfy the demands of mimicking the pressure sensing function of fingertips. In this work, a mini-size, light-weight but high-performance graphene film based pressure sensor is presented. Owing to the advanced structure with fluctuations on surface and fluffy-layered structure in cross-section of the graphene film, this pressure sensor shows an extraordinary performance of high sensitivity of 10.39 kPa-1 (0–2 kPa), ultra-wide operation range up to 200 kPa, impressively stable repeatability, high working frequency, rapid response and recovery time. Moreover, the demonstrated results of the detection of traditional Chinese medicine wrist-pulse waveform and the bionic fingertip tactile sensors, suggest the great application potential of the obtain device in biomedical field and bionic skins field. • Free-standing graphene film as active material of pressure sensors. • Widest operation range among flexible piezoresistive pressure sensors. • High sensitivity of 10.39 kPa-1 in 0–2 kPa. • Practicable applications for whist pulse detection and bionic fingertips. [ABSTRACT FROM AUTHOR]

A tactile sensor is an indispensable component for electronic skin, mimicking the sensing function of organism skin. Various sensing materials and microstructures have been adopted in the fabrication of tactile sensors. Herein, we propose a highly sensitive flexible tactile sensor composed of nanocomposites with pyramid and irregularly rough microstructures and implement a comparison of piezoresistive properties of nanocomposites with varying weight proportions of multi-wall nanotubes and carbon black particles. In addition to the simple and low-cost fabrication method, the tactile sensor can reach high sensitivity of 3.2 kPa−1 in the range of <1 kPa and fast dynamic response of 217 ms (loading) and 81 ms (recovery) at 40 kPa pressure. Moreover, body movement monitoring applications have been carried out utilizing the flexible tactile sensor. A sound monitoring application further indicates the potential for applications in electronic skin, human–computer interaction, and physiological detection. [ABSTRACT FROM AUTHOR]

Electronic skin is an important means through which robots can obtain external information. A novel flexible tactile sensor capable of simultaneously detecting the contact position and force was proposed in this paper. The tactile sensor had a three-layer structure. The upper layer was a specially designed conductive film based on indium-tin oxide polyethylene terephthalate (ITO-PET), which could be used for detecting contact position. The intermediate layer was a piezoresistive film used as the force-sensitive element. The lower layer was made of fully conductive material such as aluminum foil and was used only for signal output. In order to solve the inconsistencies and nonlinearity of the piezoresistive properties for large areas, a Radial Basis Function (RBF) neural network was used. This includes input, hidden, and output layers. The input layer has three nodes representing position coordinates, X, Y, and resistor, R. The output layer has one node representing force, F. A sensor sample was fabricated and experiments of contact position and force detection were performed on the sample. The results showed that the principal function of the tactile sensor was feasible. The sensor sample exhibited good consistency and linearity. The tactile sensor has only five lead wires and can provide the information support necessary for safe human—computer interactions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]