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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 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]

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]

Multimodal force identification by electronic skin (E‐skin) provides comprehensive and precise tactile information that can enhance elaborated functions of fine tactile discrimination, robotic manipulation, and gesture recognition. However, it remains a great challenge to realize such complicated functions from a highly simplified E‐skin sensing system. Here, mimicking the multi‐mechanoreceptor synergistic effect in human skin, a simple, thin, soft, intelligent tactile sensor composed of an asymmetrically arrangement of strain sensing units array for multimodal tactile information decoding is reported. The E‐skin type tactile sensor exhibits good performance with excellent sensitivity for shear force (2.5 N–1), vertical force (0.11 kPa–1), that enables 3D force refactoring, as well as accurate recognition of sliding force for direction tracking. Another unique feature of the E‐skin type tactile sensor is the side force screen effect, that allows the tactile sensor to yield great accuracy and a gauge factor of 1492 in strain measuring. Furthermore, integration of the sensors into E‐skin array offers the capability of capturing dynamic and real‐time stress distribution on the hand in various conditions. This work provides a new route for complex force‐sensing from the simple structure and shows great potential in robotics, human‐machine interface, and virtual reality/augmented reality (VR/AR). [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]

Wearable piezoresistive sensors are being developed as electronic skins (E‐skin) for broad applications in human physiological monitoring and soft robotics. Tactile sensors with sufficient sensitivities, durability, and large dynamic ranges are required to replicate this critical component of the somatosensory system. Multiple micro/nanostructures, materials, and sensing modalities have been reported to address this need. However, a trade‐off arises between device performance and device complexity. Inspired by the microstructure of the spinosum at the dermo epidermal junction in skin, a low‐cost, scalable, and high‐performance piezoresistive sensor is developed with high sensitivity (0.144 kPa‐1), extensive sensing range (0.1–15 kPa), fast response time (less than 150 ms), and excellent long‐term stability (over 1000 cycles). Furthermore, the piezoresistive functionality of the device is realized via a flexible transparent electrode (FTE) using a highly stable reduced graphene oxide self‐wrapped copper nanowire network. The developed nanowire‐based spinosum microstructured FTEs are amenable to wearable electronics applications. [ABSTRACT FROM AUTHOR]

The bio‐inspired sensory memory device functions as a multifunctional artificial perceptual learning system that can effectively analyze and retain multiple sensory signals. In this work, the multiscale hierarchical surface of reed leaves is templated to prepare CNTs/PDMS films, and a new type of electronic skin (E‐skin) is constructed. Due to its unique multi‐scale sensing layer surface, E‐skin exhibits a wide pressure detection range and ultrahigh sensitivity (235.95 kPa−1) and linearity (0.99 under 1.95–12.4 kPa). The memristor serving as artificial synapse is formed with HfO2 film as resistive switch layer, which has remarkable uniformity, large memory window of 102 and excellent plasticity. After integration of E‐skin with artificial synapse, the artificial synapse could be activated by the electrical information from the E‐skin to generate excitatory postsynaptic currents and the pressure information could be well retained by the memristor element. An artificial tactile perceptual neuron system with excellent retention performance, good stability and accurately recognition memory is realized, and meanwhile, the accurate decoding of Morse code by recognizing external pressure is realized. The present work transduces the concept of carbon‐based biology into a silicon‐based electronic device, which is of great significance to the development of hardware architecture in artificial intelligence. [ABSTRACT FROM AUTHOR]

Sensors and algorithms are two fundamental elements to construct intelligent systems. The recent progress in machine learning (ML) has produced great advancements in intelligent systems, owing to the powerful data analysis capability of ML algorithms. However, the performance of most systems is still hindered by sensing techniques that typically rely on rigid and bulky sensor devices, which cannot conform to irregularly curved and dynamic surfaces for high‐quality data acquisition. Skin‐like stretchable sensing technology with unique characteristics, such as high conformability, low modulus, and light weight, has been recently developed to solve this issue. Here, the recent progress in the fusion of emerging stretchable electronics and ML technology, for bioelectrical signal recognition, tactile perception, and multimodal integration is summarized, and the challenges and future developments are further discussed. These efforts aim to accelerate various perception and reasoning tasks for advanced intelligent applications, such as human–machine interfaces, healthcare, and robotics. [ABSTRACT FROM AUTHOR]

Triboelectric electronic skins (E‐skins) can be used as primary interactive devices for human–machine interfaces (HMIs). However, devices for seamless on‐skin operations must be soft and deformable, and attachable to and compatible with the skin. In this paper, a substrate‐free, skin‐compatible, skin‐attachable, mechanically deformable, and self‐powered E‐tattoo sticker consisting of carbon nanotubes (CNTs) and silk nanofibers (SNFs) is presented. The E‐tattoo can be imperceptibly tattooed on the skin and removed with water. When the device touches naked skin, triboelectric signals are generated. Because of the micro‐to‐nano hierarchical pores (with high surface‐to‐volume ratios), contact‐induced electrification generates a power density of ≈6 mW m−2 and pressure sensitivity of ≈0.069 kPa−1. The power generated on the tattooed skin can activate small electronic devices. Moreover, whole‐body joint movements can be monitored and tactile movements can be mapped by reading the generated electrical signals. The presented E‐tattoo system can promote the development of flexible energy and sensor systems for self‐powered, energy‐autonomous, imperceptible E‐skin devices for HMIs and artificial intelligent robotics and prostheses. [ABSTRACT FROM AUTHOR]

In recent years, implantable electronics, electronic skin (e‐skin), and flexible wearable devices have been developed due to their extensive applications in health monitoring, intelligent robots, and human disease treatment. Tactile sensors are the keys necessary to build skin‐inspired electronics. This article reviews the latest progress of e‐skin‐based flexible pressure sensors, such as piezoresistivity, capacitance, triboelectricity, and piezoelectricity from 2018 up to now. The working principles, structure design, active materials, and performance of numerous flexible pressure sensors are covered in detail. Finally, insights are provided and challenges and future perspectives of flexible pressure sensors in practical applications are discussed. [ABSTRACT FROM AUTHOR]

Energy‐harvesting electronic skin (E‐skin) is highly promising for sustainable and self‐powered interactive systems, wearable human health monitors, and intelligent robotics. Flexible/stretchable electrodes and robust energy‐harvesting components are critical in constructing soft, wearable, and energy‐autonomous E‐skin systems. A stretchable energy‐harvesting tactile interactive interface is demonstrated using liquid metal nanoparticles (LM‐NPs)‐based electrodes. This stretchable energy‐harvesting tactile interface relies on triboelectric nanogenerator composed of a galinstan LM‐NP‐based stretchable electrode and patterned elastic polymer friction and encapsulation layer. It provides stable and high open‐circuit voltage (268 V), short‐circuit current (12.06 µA), and transferred charges (103.59 nC), which are sufficient to drive commercial portable electronics. As a self‐powered tactile sensor, it presents satisfactory and repeatable sensitivity of 2.52 V·kPa−1 and is capable of working as a touch interactive keyboard. The demonstrated stretchable and robust energy‐harvesting E‐skin using LM‐NP‐based electrodes is of great significance in sustainable human–machine interactive system, intelligent robotic skin, security tactile switches, etc. [ABSTRACT FROM AUTHOR]

Abstract: Electronic skin (E‐skin) imitates human skin by converting external stimuli into electrical signals. E‐skin requires high flexibility and a high level of device integration. Unlike conventional E‐skin creation methods, a highly sensitive pressure sensor matrix (100 pixels cm−2) made of position‐registered elastic conductive microparticles (MPs) is created. The MPs form a Schottky junction with the bottom electrode and the current through the junction is sensitive to external pressure, forming a simple one‐selector two‐terminal device array. The Schottky junction eliminates the electrical cross talks between the sensor pixels consisting of 64 MPs in each. The flexible pressure sensor matrix is used as an artificial fingertip for Braille reading and as an electronic scale based on detailed force distribution. This work opens up the possibility that assembled MPs, which have been a long‐standing research topic in academia, can be used to make practical electronic devices. [ABSTRACT FROM AUTHOR]

This report demonstrates a wearable elastomer-based electronic skin including resistive sensors for monitoring finger articulation and capacitive tactile pressure sensors that register distributed pressure along the entire length of the finger. Pressure sensitivity in the order of 0.001 to 0.01 kPa−1 for pressures from 5 to 405 kPa, which includes much of the range of human physiological sensing, is achieved by implementing soft, compressible silicone foam as the dielectric and stretchable thin-metal films. Integrating these sensors in a textile glove allows the decoupling of the strain and pressure cross-sensitivity of the tactile sensors, enabling precise grasp analysis. The sensorized glove is implemented in a human-in-the-loop system for controlling the grasp of objects, a critical step toward hand prosthesis with integrated sensing capabilities. [ABSTRACT FROM AUTHOR]

In article number 1800284, Jang‐Yeon Kwon and co‐workers demonstrate highly sensitive tactile sensors using a pyramid‐plug structure that enables them to detect pressure, shear force, and torsion. The wide operating range of the sensor, from soft breathing to arbitrary multiplex touching, makes it particularly promising for future applications. [ABSTRACT FROM AUTHOR]

Sensors that detect and discriminate external mechanical forces are a principal component in the development of electronic tactile systems that can mimic the multifunctional properties of human skin. This study demonstrates a pyramid‐plug structure for highly sensitive tactile sensors that enables them to detect pressure, shear force, and torsion. The device is composed of pyramid‐patterned ionic gel inspired by neural mechanoreceptors and engraved electrodes. Based on a pyramid‐plug structure, the deformation mechanism differs between different types of external mechanical loadings. The sensor provides the high sensitivities of 1.93 kPa−1, 29.88 N−1, and 3.39 (N cm)−1, and a wide range of detection for tactile daily activity. Moreover, this tactile sensor could work through either of the two transduction methods (capacitive transduction and piezoresistive transduction). It is shown that this tactile sensor can be used to monitor changes in electrical signals ranging from those caused by human breathing to those caused by arbitrary multiplex human touching. A pyramid‐plug structure for highly sensitive tactile sensors that enables them to detect pressure, shear force, and torsion is demonstrated. This tactile sensor could work by each of the two transduction methods. The sensor provides the high sensitivities of 1.93 kPa−1, 29.88 N−1, and 3.39 (N cm)−1, and a wide range of detection for tactile daily activity. [ABSTRACT FROM AUTHOR]