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This paper presents a unique design of a single-axis tactile force sensor by a mutual parallel plate and fringing effect of an electric field that is generated between stationary patterned electrodes in the sensor. The proposed sensor can measure the normal and shear forces with high sensitivity and linear response. The capacitive tactile sensor is fabricated by low-cost rapid prototyping techniques using conductive ink for electrode printing that is printed on a polyethylene terephthalate sheet by an inkjet printer. Ecoflex 00-30 and silicone rubber RTV-528 are used as the dielectric medium and dome for force application. A finite element method analysis is performed for deciding the dimensions of the sensor's stationary electrodes. The force measurement ranges of the sensor for the normal and shear axis are 4 N and 2 N, respectively. The proposed tactile sensor shows a highly linear response, which makes it a suitable match for force feedback in robotic surgery. [ABSTRACT FROM AUTHOR]

The dense mechanoreceptors in human fingertips enable texture discrimination. Recent advances in flexible electronics have created tactile sensors that effectively replicate slowly adapting (SA) and rapidly adapting (RA) mechanoreceptors. However, the influence of dermatoglyphic structures on tactile signal transmission, such as the effect of fingerprint ridge filtering on friction-induced vibration frequencies, remains unexplored. A novel multi-layer flexible sensor with an artificially synthesized skin surface capable of replicating arbitrary fingerprints is developed. This sensor simultaneously detects pressure (SA response) and vibration (RA response), enabling texture recognition. Fingerprint ridge patterns from notable historical figures - Rosa Parks, Richard Nixon, Martin Luther King Jr., and Ronald Reagan - are fabricated on the sensor surface. Vibration frequency responses to assorted fabric textures are measured and compared between fingerprint replicas. Results demonstrate that fingerprint topography substantially impacts skin-surface vibrational transmission. Specifically, Parks fingerprint structure conveyed higher frequencies more clearly than those of Nixon, King, or Reagan. This work suggests individual fingerprint ridge morphological variation influences tactile perception and can confer adaptive advantages for fine texture discrimination. The flexible bioinspired sensor provides new insights into human vibrotactile processing by modeling fingerprint-filtered mechanical signals at the finger-object interface.

Purpose: This paper aims to introduce a sensorized surgical grasper with a novel flexible capacitive tactile force sensor integrated within the surgical grasper for minimally invasive surgery (MIS) and robot-assisted MIS (RMIS) procedures. Design/methodology/approach: The proposed sensor offers a unique configuration of sensing electrodes with one top excitation electrode and three bottom electrodes enabling the measurement of normal and shear forces without incorporating any complex decoupling algorithms. The design of the sensor is optimized using finite-element method simulations, ensuring efficiency and reliability. Findings: Experimental validation, real-time sensor response and application in lump detection through stiffness assessment demonstrate the decoupled force response (0–5 N normal range and 0–2 N shear range) with high sensitivity 0.0124/N, repeatability and hysteresis response with 5.65% and 4.7% errors respectively. Originality/value: The compact design of the sensor makes it compliant with surgical graspers and therefore enhances the overall efficiency of robotic surgical procedures. The sensorized surgical grasper is fabricated using conventional machining and rapid prototyping techniques, presenting a cost-effective solution for adoption. [ABSTRACT FROM AUTHOR]

Porous structures such as the dielectric layer have been identified as an effective way to enhance the performance of capacitive tactile sensors and aerogels as three-dimensional structured materials with high porosity and excellent mechanical properties, which have been shown to have the potential to further improve the overall performance of capacitive sensors. However, the inherent low compressive modulus of elastic aerogels limits their functionality, especially when subjected to larger pressure ranges, posing a challenge for extending the working pressure range of aerogel-based sensors. In this work, we combined graphene oxide (GO) with cellulose nanofibers (CNF) and polydimethylsiloxane (PDMS) to form a composite aerogel as the dielectric layer in a capacitive tactile sensor, aiming to overcome the inherent shortcomings associated with conventional aerogels. The results demonstrated that the composite aerogels preserved high porosity and exhibited superior elastic properties to significantly enhance the overall performance of the tactile sensor. The sensor exhibits a sensitivity of up to 1.7 kPa−1, within a working range of 80 kPa, together with a rapid response time of 46 ms and a relaxation time of 92 ms. Additionally, the sensor featured an ultra-low detection limit of 30 Pa and maintained excellent stability under continuous load cycles. The performance and the flexibility of the sensor fit well for tactile perception and wearable detection applications. [ABSTRACT FROM AUTHOR]

The interest in highly sensitive sensors is rapidly increasing for detecting very tiny signals for Internet of Things devices. Here, we achieve ultra-sensitive correlated breathable sensors based on freestanding VO2 membranes. We fabricate the membranes by growing VO2 films onto sacrificial Sr3Al2O6 layer grown on SrTiO3, selectively dissolving the Sr3Al2O6 in water, and then rendering freestanding VO2 membrane on nanomesh. The nanomeshes are extremely flexible, sweat permeable, and readily skin-adhesive. The resistance of the VO2 membranes is reversibly tuned by human's tiny mechanical stimuli and breath stimuli. The stimuli modulate the Peierls dimerization of one-dimensional V−V chains in the VO2 lattice which concomitantly controls the electron correlation and hence resistivity. Since our breathable sensors operate based on quantum-mechanical correlation effects, their sensitivity is 1−2 orders of magnitude higher than conventional tactile and respiratory sensors based on other materials. Thus, the freestanding membranes of correlated oxides on epidermal nanomeshes are multifunctional platforms for developing ultra-sensitive correlated breathable sensors. [ABSTRACT FROM AUTHOR]

Flexible tactile sensors are widely used in aerospace, medical and health monitoring, electronic skin, human–computer interaction, and other fields due to their unique advantages, thus becoming a research hotspot. The goal is to develop a flexible tactile sensor characterized by outstanding sensitivity, extensive detection range and linearity, elevated spatial resolution, and commendable adaptability. Among several strategies like capacitive, piezoresistive, and triboelectric tactile sensors, etc., we focus on piezoelectric tactile sensors because of their self-powered nature, high sensitivity, and quick response time. These sensors can respond to a wide range of dynamic mechanical stimuli and turn them into measurable electrical signals. This makes it possible to accurately detect objects, including their shapes and textures, and for them to sense touch in real time. This work encapsulates current advancements in flexible piezoelectric tactile sensors, focusing on enhanced material properties, optimized structural design, improved fabrication techniques, and broadened application domains. We outline the challenges facing piezoelectric tactile sensors to provide inspiration and guidance for their future development. [ABSTRACT FROM AUTHOR]

Treating ankle fractures in athletes, commonly resulting from training injuries, remains a significant challenge. Current approaches to managing both non-surgical and postoperative foot and ankle disorders have focused on integrating sensory systems into orthotic devices. Recent analyses have identified several gaps in rehabilitation strategies, especially regarding gait pattern reformation during recovery. This work aims to enhance rehabilitation effectiveness for patients with ankle injuries by controlling load distribution and monitoring joint flexion/extension angles, as well as the reactive forces during therapeutic exercises and walking. We developed an exoskeleton device model using SolidWorks 2024 software, based on data from two patients: one healthy and one with an ankle fracture. Pressure measurements in the posterior limb region were taken using the F-Socket system and a custom electromechanical sensor designed by the authors. The collected data were analyzed using the butterfly parameterization method. This research led to the development of an adaptive exoskeleton device that provided pressure distribution data, gait cycle graphs, and a diagram correlating foot angles with the duration of exoskeleton use. The device demonstrated improvement in the patients' conditions, facilitating a more normalized gait pattern. A reduction in the load applied to the ankle joint was also observed, with the butterfly parameter confirming the device's correct operation. [ABSTRACT FROM AUTHOR]

Maintenance and service are important tasks for any industrial enterprise. This article presents a methodology for technical maintenance that employs a smart glove equipped with tactile sensors, an electronic unit responsible for processing and transmitting information, and a unit designed to interpret the results. Tactile sensors are graphene-based. The main idea of the method is to use sensors to record the strength of contact between the operator's fingertips and the equipment. Afterwards, these values are recorded, transferred to processing, and the output signal from the sensors is compared with the steps of various repair works. The work contains methods for creating each component of the glove, their effectiveness is evaluated, and experiments are described to assess the feasibility of using the developed device for the maintenance and repair of equipment. The device discussed in this work is a wearable device. The obtained results demonstrate the applicability of the smart glove for equipment maintenance and repair. [ABSTRACT FROM AUTHOR]

This study aims to establish an equivalent parallel capacitance model for a copper/polydimethylsiloxane (Cu/PDMS) capacitive flexible pressure sensor and modulate its relative permittivity to optimize pressure sensing performance. The Cu/PDMS composite material is an ideal dielectric layer for sensors due to its high dielectric constant and tunable elasticity. By adjusting the different mixing ratios of PDMS and copper particles in micro size, the components and structure properties of the composite material can be modified, thereby affecting the electrical and mechanical performance of the sensor. We used finite element analysis (FEA) to model the sensor structure and studied the capacitance changes under various normal loading conditions to assess its sensitivity and distribution characteristics. Experimental results show that the sensor has good sensitivity and repeatability in the pressure range of 0 to 50 kPa. Additionally, we explored the effect of the addition of carbon black particles. It could be inferred that the added carbon black can enhance electrical properties due to its conductivity, which would be consequenced by the distribution optimization of Cu particles for carbon black's low density, and it can mechanically restore some flexibility up to nearly 20%. Through these studies, our work can provide theoretical support for the design and application of flexible pressure sensors. [ABSTRACT FROM AUTHOR]

Sensor miniaturization offers significant advantages, including enhanced SoC integration efficiency, reduced cost, and lightweight design. While the roll-to-roll printed electronics fabrication process is advantageous for the mass production of sensors compared to the traditional MEMS technology, producing sensors that require air gap-based 3D structures remains challenging. This study proposes an integration of roll-to-roll gravure printing with a transferring and bonding method for touch sensor fabrication. Unlike previously reported methods for sacrificial layer removal, this approach prevents stiction issues, thus enabling sensor miniaturization and providing the flexibility to select materials that minimize sensitivity degradation during scaling. For the lower part of the sensor, Ag and BaSO4 were roll-to-roll gravure-printed on a flexible PET substrate to form the bottom electrode and dielectric layer, followed by BaSO4 spin coating on the sensor's anchor area to form a spacer. For the upper part, a water-soluble PVP sacrificial layer was roll-to-roll gravure-printed on another flexible PET substrate, followed by spin coating Ag and SU-8 to form the top electrode and the structural layer, respectively. The sacrificial layer of the upper part was removed with water to delaminate the top electrode and structural layer from the substrate, then transferred and bonded onto the spacer of the lower part. Touch sensors of three different sizes were fabricated, and their performances were comparatively analyzed along with that of an epoxy resin-based sensor, demonstrating that our sensor attained miniaturization while achieving relatively high sensitivity. [ABSTRACT FROM AUTHOR]

With the advent of the intelligent era, flexible piezoelectric tactile sensors, as key components for sensing information and transmitting signals, have received worldwide attention. However, piezoelectric pressure sensors are still currently limited, which severely restricts their practical applications. Furthermore, the demonstrations conducted in labs are not accurate to real-world scenarios. Thus, there is an urgent need to further optimize the intrinsic piezoelectric performance and usage characteristics to meet application requirements. As a representative piezoelectric, polyvinylidene fluoride (PVDF) exhibits significant advantages in terms of excellent flexibility, chemical stability, high electromechanical conversion, low cost, and appropriate acoustic impedance, which allow it to serve as the core matrix in flexible pressure sensors. This paper aims to summarize very recent progress in flexible piezoelectric sensors based on PVDF, including their composition modulation, structure optimization, and applications. Based on a comprehensive summary of recent representative studies, we propose rational perspectives and strategies regarding PVDF-based piezoelectric sensors and provide some new insights for the research and industrial communities. [ABSTRACT FROM AUTHOR]

Cooperative robots that perform safety functions as part of cooperative work with humans have been recently drawing attention. Proximity and tactile sensors that can be retrofitted to a robot's surface are important safety measures for existing robots that are not manufactured as cooperative robots to be used as cooperative robots. In this paper, a string‐like self‐capacitance‐based proximity and tactile sensor that can be easily wrapped around various types of existing robots is proposed. The novel and useful point in this paper is that it can be easily mounted on various robots by a flexible string‐like proximity and tactile sensor. The sensor module can be adjusted to the required length by connecting different numbers of modules depending on the mounting surface. As a demonstration, six prototype sensor modules were connected by each connector and wrapped around a robotic arm. The sensor modules on the robot's surface could detect an object within its proximity range and detect the rough pressure after contact. In addition, the robotic arm with the sensor modules could be controlled in real time using the data obtained from the sensor that are object detection data at proximity range. These results confirm that the proposed sensor module can be used in the proximity and tactile sensors of existing robots. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The TacTip is a cost-effective, 3D-printed optical tactile sensor commonly used in deep learning and reinforcement learning for robotic manipulation. However, its specialized structure, which combines soft materials of varying hardnesses, makes it challenging to simulate the distribution of numerous printed markers on pins. This paper aims to create an interpretable, AI-applicable simulation of the deformation of TacTip under varying pressures and interactions with different objects, addressing the black-box nature of learning and simulation in haptic manipulation. The research focuses on simulating the TacTip sensor's shape using a fully tunable, chain-based mathematical model, refined through comparisons with real-world measurements. We integrated the WRS system with our theoretical model to evaluate its effectiveness in object pose estimation. The results demonstrated that the prediction accuracy for all markers across a variety of contact scenarios exceeded 92%. [ABSTRACT FROM AUTHOR]

Tactile sensing is currently a research hotspot in the fields of intelligent perception and robotics. The method of converting external stimuli into electrical signals for sensing is a very effective strategy. Herein, we proposed a self-powered, flexible, transparent tactile sensor integrating sliding and proximity sensing (SFTTS). The principle of electrostatic induction and contact electrification is used to achieve tactile response when external objects approach and slide. Experiments show that the material type, speed, and pressure of the perceived object can cause the changes of the electrical signal. In addition, fluorinated ethylene propylene (FEP) is used as the contact electrification layer, and indium tin oxide (ITO) is used as the electrostatic induction electrode to achieve transparency and flexibility of the entire device. By utilizing the transparency characteristics of this sensor to integrate with optical cameras, it is possible to achieve integrated perception of tactile and visual senses. This has great advantages for applications in the field of intelligent perception and is expected to be integrated with different types of optical sensors in the future to achieve multimodal intelligent perception and sensing technology, which will contribute to the intelligence and integration of robot sensing. [ABSTRACT FROM AUTHOR]

A novel cellulose hydrogel (MWCNTs/CNWs/PAM/SA) was prepared using a simple double cross-linked network synthesis method. It have good mechanical adaptability, high conductivity sensitivity (GF = 5.65, 53 ms), and low hysteresis (<11%). Additionally, it exhibits a sensitive response to water molecules as well as temperature-stimulated shape memory behavior. Hydrogels are designed as flexible tactile sensors that can accurately recognize and monitor electrical signals from different gesture movements and temperature changes. It was also assembled as a friction nanogenerator (TENG) that continuously generates a stable open circuit voltage (28 V) for self-powered small electronic devices. This provides the opportunity for accurate detection and fast feedback for flexible tactile sensors, green energy harvesting and power applications for small self-powered sensors, and may be a general approach to synthetic materials suitable for the development of future flexible electronic devices. [Display omitted] • MWCNTs and CNWs were introduced into PAM/SA hydrogels, which significantly improved the conductivity of the hydrogels. • The CWCNTs/CNWs/PAM/SA hydrogel tactile sensors can accurately recognize various gestures and temperature signals. • Hydrogel can be assembled into TENG for self-powered LEDs. This provides a strategy for green sustainable energy harvesting. Conductive hydrogels have been widely applied in human–computer interaction, tactile sensing, and sustainable green energy harvesting. Herein, a double cross-linked network composite hydrogel (MWCNTs/CNWs/PAM/SA) by constructing dual enhancers acting together with PAM/SA was constructed. By systematically optimizing the compositions, the hydrogel displayed features advantages of good mechanical adaptability, high conductivity sensitivity (GF = 5.65, 53 ms), low hysteresis (<11 %), and shape memory of water molecules and temperature. The nanocellulose crystals (CNWs) were bent and entangled with the backbone of the polyacrylamide/ sodium alginate (PAM/SA) hydrogel network, which effectively transferred the external mechanical forces to the entire physical and chemical cross-linking domains. Multi-walled carbon nanotubes (MWCNTs) were filled into the cross-linking network of the hydrogel to enhance the conductivity of the hydrogel effectively. Notably, hydrogels are designed as flexible tactile sensors that can accurately recognize and monitor electrical signals from different gesture movements and temperature changes. It was also assembled as a friction nanogenerator (TENG) that continuously generates a stable open circuit voltage (28 V) for self-powered small electronic devices. This research provides a new prospect for designing nanocellulose and MWCNTs reinforced conductive hydrogels via a facile method. [ABSTRACT FROM AUTHOR]

The fabrication of soft fluid‐filled systems with mm or sub‐mm scale features such as tuneable lenses, microfluidic tactile sensors, and electrohydraulic zipping actuators often relies on manual filling. This final step of injecting fluid limits throughput and repeatability. This study presents an additive manufacturing process to create complex stretchable systems in which the liquid is directly printed as part of the fabrication process. The devices actuate straight out of the printing setup, with no further filling or sealing steps. In our fully printed approach for multi‐layered structures, the key steps are the deposition of precisely shaped liquid droplets with sub‐µL resolution, followed by their encapsulation using a freezing process to allow printing or spraying over the temporarily solid fluid drops. Printing both the fluid and the structure has advantages of: a) no filing channel, enabling very high fill‐factors; b) design freedom as each device in array can be filled with a different volume; c) accuracy in filling. We demonstrate this process by printing arrays of 5 mm diameter stretchable hydraulically amplified taxels (HAXELs), consisting of nine flexible layers, with the working fluid included as part of the printing process. [ABSTRACT FROM AUTHOR]

Restricted by the limited interaction area of native AR glasses, creating sketches is a challenge in it. Existing solutions attempt to use mobile devices (e.g., tablets) or mid-air hand gestures to expand the interactive spaces and as the 2D/3D sketching input interfaces for AR glasses. Between them, mobile devices allow for accurate sketching but are often heavy to carry. Sketching with bare hands is zero-burden but can be inaccurate due to arm instability. In addition, mid-air sketching can easily lead to social misunderstandings and its prolonged use can cause arm fatigue. In this work, we present WristSketcher, a new AR system based on a flexible sensing wristband that enables users to place multiple virtual plane canvases in the real environment and create 2D dynamic sketches based on them, featuring an almost zero-burden authoring model for accurate and comfortable sketch creation in real-world scenarios. Specifically, we streamlined the interaction space from the mid-air to the surface of a lightweight sensing wristband, and implemented AR sketching and associated interaction commands by developing a gesture recognition method based on the sensing pressure points. We designed a set of interactive gestures consisting of Long Press, Tap and Double Tap based on a heuristic study involving 26 participants. These gestures are correspondingly mapped to various command interactions using a combination of multi-touch and hotspots. Moreover, we endow our WristSketcher with the ability of animation creation, allowing it to create dynamic and expressive sketches. Experimental results demonstrate that our WristSketcher (i) recognizes users' gesture interactions with a high accuracy of 95.9%; (ii) achieves higher sketching accuracy than Freehand sketching; (iii) achieves high user satisfaction in ease of use, usability and functionality; and (iv) shows innovation potentials in art creation, memory aids, and entertainment applications. [ABSTRACT FROM AUTHOR]

Artificial skin has shown great potential in robot perception and human healthcare. It provides multifunctional tactile sensing, including 3D shape reconstruction, contact feedback, and temperature perception, where the 3D reconstruction function is indispensable for dexterous hands in tactile cognition and interaction. Vision‐based tactile sensor (VTS) is an innovative bionic tactile sensor and supports high‐resolution, high‐precision, and high‐density tactile reconstruction compared with electronic tactile sensors. Considering the unique contribution of visuo‐tactile sensing to artificial skin, this review focuses on the 3D reconstruction techniques of the VTS. 3D reconstruction methods are classified into five categories based on sensing modalities, hardware categories, and modeling approaches: 1) photometric stereo, 2) binocular depth calibration, 3) optical flow, 4) deep learning, and 5) ToF (time of flight). In addition, the association and difference of reconstruction methods are analyzed from the hardware perspective, and the development and technological details of 3D reconstruction are summarized. On this basis, the challenges and development direction are discussed. This review can be viewed as a technology guide to provide references for interested researchers. Furthermore, it is expected to promote the extensive application of the VTS in artificial skins. [ABSTRACT FROM AUTHOR]

Tactile perception plays a crucial role in the perception of products and consumer preferences. This perception process is structured in hierarchical layers comprising a sensory layer (soft and smooth) and an affective layer (comfort and luxury). In this study, we attempted to predict the evaluation score of sensory and affective tactile perceptions of materials using a biomimetic multimodal tactile sensor that mimics the active touch behavior of humans and measures physical parameters such as force, vibration, and temperature. We conducted sensory and affective descriptor evaluations on 32 materials, including cosmetics, textiles, and leather. Using the physical parameters obtained by the biomimetic multimodal tactile sensor as explanatory variables, we predicted the scores of the sensory and affective descriptors in 10 regression models. The bagging regressor demonstrated the best performance, achieving a coefficient of determination (R2) of >0.6 for fourteen of nineteen sensory and eight of twelve affective descriptors. The present model exhibited particularly high prediction accuracy for sensory descriptors such as "moist" and "elastic", and for affective descriptors such as "pleasant" and "like". These findings suggest a method to support efficient tactile design in product development across various industries by predicting tactile descriptor scores using physical parameters from a biomimetic tactile sensor. [ABSTRACT FROM AUTHOR]

The rapid advancement of tactile electronic skin (E-skin) has highlighted the effectiveness of incorporating bionic, force-sensitive microstructures in order to enhance sensing performance. Among these, cilia-like microstructures with high aspect ratios, whose inspiration is mammalian hair and the lateral line system of fish, have attracted significant attention for their unique ability to enable E-skin to detect weak signals, even in extreme conditions. Herein, this review critically examines recent progress in the development of cilia-inspired bionic tactile E-skin, with a focus on columnar, conical and filiform microstructures, as well as their fabrication strategies, including template-based and template-free methods. The relationship between sensing performance and fabrication approaches is thoroughly analyzed, offering a framework for optimizing sensitivity and resilience. We also explore the applications of these systems across various fields, such as medical diagnostics, motion detection, human–machine interfaces, dexterous robotics, near-field communication, and perceptual decoupling systems. Finally, we provide insights into the pathways toward industrializing cilia-inspired bionic tactile E-skin, aiming to drive innovation and unlock the technology's potential for future applications. [ABSTRACT FROM AUTHOR]

Affordable high-resolution cameras and state-of-the-art computer vision techniques have led to the emergence of various vision-based tactile sensors. However, current vision-based tactile sensors mainly depend on geometric optics or marker tracking for tactile assessments, resulting in limited performance. To solve this dilemma, we introduce optical interference patterns as the visual representation of tactile information for flexible tactile sensors. We propose a novel tactile perception method and its corresponding sensor, combining structural colors from flexible blazed gratings with deep learning. The richer structural colors and finer data processing foster the tactile estimation performance. The proposed sensor has an overall normal force magnitude accuracy of 6 mN, a planar resolution of 79 μm and a contact-depth resolution of 25 μm. This work presents a promising tactile method that combines wave optics, soft materials and machine learning. It performs well in tactile measurement, and can be expanded into multiple sensing fields. [ABSTRACT FROM AUTHOR]

An origami-based tactile sensory ring utilizing multilayered conductive paper substrates presents an innovative approach to wearable health applications. By harnessing paper's flexibility and employing origami folding, the sensors integrate structural stability and self-packaging without added encapsulation layers. Knot-shaped designs create loop-based systems that secure conductive paper strips and protect sensing layers. Demonstrating a sensitivity of 3.8 kPa−1 at subtle pressures (0–0.05 kPa), the sensors detect both minimal stimuli and high-pressure inputs. Electrical modeling of various origami configurations identifies designs with optimized performance with a pentagon knot offering higher sensitivity to support high-sensitivity needs. Meanwhile a square knot provides greater precision and quicker recovery, balancing sensitivity and stability for real-time feedback devices. The enhanced elastic modulus from folds remains within human skin's elasticity range, ensuring comfort. Applications include grip strength monitoring and pulse rate detection from the thumb, capturing pulse transit time (PTT), an essential cardiovascular biomarker. This design shows the potential of origami-based tactile sensors in creating versatile, cost-effective wearable health monitoring systems. [ABSTRACT FROM AUTHOR]

3D printing presents a promising avenue for developing personalized healthcare devices. Among 3D printing techniques, direct ink writing (DIW) stands out for its versatility in fabricating wearable sensors for real‐time health monitoring. DIW not only enables the utilization of diverse materials but also offers the flexibility to produce various sensors quickly. In this study, a novel wearable tactile sensor with a customizable active layer realized through the DIW employing two distinct conductive inks with differing rheological and electrical properties is introduced. The resulting 3D‐printed active layers are flexible and micro‐structured, which facilitate real‐time physiological signal recording in health monitoring applications. By incorporating hierarchical microdomes atop a flat substrate, the dynamic response of the active layer is significantly enhanced. Additionally, the trapped pores within the 3D‐printed structures contribute to improved sensor performance in static tests. The 3D‐printed active layers exhibit excellent linearity and resolution in the range from 1 to 30 N, demonstrating their suitability for diverse applications tailored to specific requirements. This study offers a cost‐effective approach for fabricating tactile sensors customized for various wearable medical applications. [ABSTRACT FROM AUTHOR]

Skin-like sensors capable of detecting multiple stimuli simultaneously have great potential in cutting-edge human-machine interaction. However, realizing multimodal tactile recognition beyond human tactile perception still faces significant challenges. Here, an extreme environments-adaptive multimodal triboelectric sensor was developed, capable of detecting pressure/temperatures beyond the range of human perception. Based on triboelectric nanogenerator technology, an asymmetric structure capable of independently outputting dual signals was designed to improve perception sensitivity. By converting the signals and the stimuli into feature matrices, parallel perception of complex objects (with a recognition rate of 94%) and temperature at high temperatures was achieved. The proposed multimodal triboelectric tactile sensor represents progress in maximum detection range and rapid response, realizing the upper limit of human skin's high-temperature sensing (60 °C) with a working temperature of 200 °C. The proposed self-powered multimodal sensing system offers a wider range of possibilities for human/robot/environment interaction applications. Existing tactile sensors struggle with high-temperature environments. Here, authors developed a triboelectric tactile sensor with an asymmetric structure and heat-resistant materials, enabling 94% object recognition rate, fast response times, and stable performance up to 200 °C. [ABSTRACT FROM AUTHOR]

This review focuses on touching-based underwater robotic perception and manipulation, and provides a comprehensive overview of the current research landscape. We begin by examining underwater tactile sensors, discussing their basic types and recent advancements that have facilitated their integration into underwater robotic manipulation. Additionally, we explore the development of force control algorithms for underwater manipulators and grippers, emphasizing their critical role in underwater environments. Furthermore, we analyze the application of force control algorithms in underwater robotic manipulation, considering different autonomy levels, basic manipulation tasks, and specific operational scenarios. Through this investigation, we identify existing limitations and propose future research directions aimed at enhancing the operational capabilities of underwater vehicle manipulator systems (UVMS) and expanding their application range. Finally, this review highlights key challenges and outlines pathways for advancing the field. [ABSTRACT FROM AUTHOR]

In-hand manipulation with Cartesian-force-control-based pushing primitives is introduced to achieve the precise placement of an object in a desired position at a manufacturing site. In the bin picking process, achieving the desired grasping posture is challenging due to limitations in the sensing and control of the robotic arm, interference from clustered objects, and unintended collisions, which hinder achieving the planned pose. Even under such conditions, in cases that require precise operations, such as manufacturing processes, maintaining a desired placement posture is crucial for the precise placement of objects into the machine slot. In this paper, a pushing primitive incorporating force feedback control is applied to ensure that the gripper is consistently positioned at the edge of the grasped object regardless of the initial grasping position by utilizing the surrounding environment of the processing machine. Modeling the exact contact friction between the gripper and the grasped object is challenging; therefore, instead of relying on a motion planning approach, we addressed the problem using a control method that leverages feedback from the external force information of the robot manipulator. Additional sensors such as external cameras or tactile sensors in the gripper are not required. The pushing primitive is executed by applying a force greater than the frictional force between the gripper and the grasped object, leveraging the surrounding environment. Experimental verification confirmed that the proposed method achieves precise placement into the machine slot, regardless of initial grasping positions. It also proved to be effective on an actual testbed. [ABSTRACT FROM AUTHOR]

The rapid development of nanotechnology has significantly revolutionized wearable electronics and expanded their functionality. Through introducing innovative solutions for energy harvesting and autonomous sensing, this research presents a cost‐effective strategy to enhance the performance of triboelectric nanogenerators (TENGs). The TENG was fabricated from polyvinylidene fluoride (PVDF) and N, N′‐poly(methyl methacrylate) (PMMA) blend with a porous structure via a novel optimized quenching method. The developed approach results in a high β‐phase content (85.7%) PVDF/3wt.%PMMA porous blend, known for its superior piezoelectric properties. PVDF/3wt.%PMMA modified porous TENG demonstrates remarkable electrical output, with a dielectric constant of 40 and an open‐circuit voltage of approximately 600 V. The porous matrix notably increases durability, enduring over 36 000 operational cycles without performance degradation. Moreover, practical applications were explored in this research, including powering LEDs and pacemakers with a maximum power output of 750 mW m−2. Also, TENG served as a self‐powered tactile sensor for robotic applications in various temperature conditions. The work highlights the potential of the PVDF/PMMA porous blend to utilize the next‐generation self‐powered sensors and power small electronic devices. [ABSTRACT FROM AUTHOR]

Force plates are used to measure postural control. However, force plates differ with regard to the type of sensors and the position of the sensors. The purpose of the study was to introduce a method for testing the comparability of two force plates with different force transducers regarding their center of pressure (CoP) capturing. Two portable force plates (Kistler Model 9260AA vs. AMTI AccuSway-Optimized ACS-O) were compared. To produce repeatable, close to identical CoP data, a two-point suspension pendulum was used. The deflection angle of the pendulum was kept constant as well as the time of capturing the swing (30 s) and the frequency of capturing the data (1000 Hz). To test for comparability, the captured data was z-transformed and superimposed. Furthermore, interclass correlation coefficient (ICC) estimates, and their 95 % confidence intervals (CI) were calculated. The ICC for the two tested force plates were "excellent" (x-axis: ICC = 0.990 (95 % CI [0.990–0.990]), y-axis: ICC = 0.987 (95 % CI [0.987–0.988])). Thus, the presented method with the two-point suspension pendulum generated repeatable and almost identical oscillations in the x- and y-axis to calculate the CoP. Data will be made available on request. • The pendulum model is an appropriate method to compared shear forces between different force plates. • Postural control of individuals in a dynamic condition provides reliable results in terms of the measurement methodology. • To test the two force plates with the pendulum model variability inherent in biological systems can be neglected. [ABSTRACT FROM AUTHOR]

Ionic hydrogels are uniquely suited as force‐sensing layers because of their good biocompatibility and controlled electromechanical properties. The emerging piezoionic effect allows them to sense the position of pressure, but the low response rate limits their applications. Herein, this work focuses on modulating the response time of piezoionic outputs through crosslinking. The underlying mechanism is investigated through the perspective of deformation recovery rate and ion migration behavior in the ionic hydrogels. As a result, the developed piezoionic sensors are capable of distinguishing static forces in the range of 0.1–5 s while monitoring dynamic force, breaking the limitations of conventional self‐powered pressure sensors that have trouble tracking static forces. Furthermore, by utilizing the piezoionic effect to convert the touch indentation into transverse gradient ionic potential, the constructed piezoionic sensors achieve accurate monitoring of finger pressing position and sliding trajectory. As a proof‐of‐concept, pattern unlocking in security authentication is successfully validated based on the developed piezoionic sensors. This design strategy of modulating ionic tactile sensor by crosslinking is expected to provide a fresh path for the large‐scale flexible human‐machine interfaces. [ABSTRACT FROM AUTHOR]

With the rapid development of intelligent wearable technology, multimodal tactile sensors capable of data acquisition, decoupling of intermixed signals, and information processing have attracted increasing attention. Herein, a decoupled temperature–pressure dual‐mode sensor is developed based on single‐walled carbon nanotubes (SWCNT) and poly(3,4‐ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS) decorated porous melamine foam (MF), integrating with a deep learning algorithm to obtain a multimodal input terminal. Importantly, the synergistic effect of PEDOT:PSS and SWCNT facilitates the sensor with ideal decoupling capability and sensitivity toward both temperature (38.2 µV K−1) and pressure (10.8% kPa−1) based on the thermoelectric and piezoresistive effects, respectively. Besides, the low thermal conductivity and excellent compressibility of MF also endow it with the merits of a low‐temperature detection limit (0.03 K), fast pressure response (120 ms), and long‐term stability. Benefiting from the outstanding sensing characteristics, the assembled sensor array showcases good capacity for identifying spatial distribution of temperature and pressure signals. With the assistance of a deep learning algorithm, it displays high recognition accuracy of 99% and 98% corresponding to "touch" and "press" actions, respectively, and realizes the encrypted transmission of information and accurate identification of random input sequences, providing a promising strategy for the design of high‐accuracy multimodal sensing platform in human–machine interaction. [ABSTRACT FROM AUTHOR]

Tactile intent recognition systems, which are highly desired to satisfy human's needs and humanized services, shall be accurately understanding and identifying human's intent. They generally utilize time‐driven sensor arrays to achieve high spatiotemporal resolution, however, which encounter inevitable challenges of low scalability, huge data volumes, and complex processing. Here, an event‐driven intent recognition touch sensor (IR touch sensor) with in‐sensor computing capability is presented. The merit of event‐driven and in‐sensor computing enables the IR touch sensor to achieve ultrahigh resolution and obtain complete intent information with intrinsic concise data. It achieves critical signal extraction of action trajectories with a rapid response time of 0.4 ms and excellent durability of >10 000 cycles, bringing an important breakthrough of tactile intent recognition. Versatile applications prove the integrated functions of the IR touch sensor for great interactive potential in all‐weather environments regardless of shading, dynamics, darkness, and noise. Unconscious and even hidden action features can be perfectly extracted with the ultrahigh recognition accuracy of 98.4% for intent recognition. The further auxiliary diagnostic test demonstrates the practicability of the IR touch sensor in telemedicine palpation and therapy. This groundbreaking integration of sensing, data reduction, and ultrahigh‐accuracy recognition will propel the leapfrog development for conscious machine intelligence. [ABSTRACT FROM AUTHOR]

Flexible sensors have been applied to accurately identify the basic features of various solid objects. However, a significant obstacle is the accurate identification of liquids, due to it is impossible to exert force directly on those. Here, an optical‐thermal flexible tactile sensor is designed for liquid recognition, which integrates PEDOT:PSS/SrTiO3 thermoelectric foam and ZnS‐CaZnOS mechanoluminescent (ML) film coated with thermoplastic polyurethane (TPU), enabling the simultaneous detection of thermal and optical changes with low interference, via its exceptional mechanical stimuli‐caused light and superior thermoelectric voltage, respectively. In addition, the TPU coating imparts the device with excellent hydrophobic and oleophobic properties, enhancing its durability in complex conditions. This flexible sensor, possessing high stability under thermal and mechanical cycles, can distinguish different pure solvents and turbid suspensions, achieving a high‐fine recognition accuracy of 95% and 97.5%, respectively, with the aid of the fusion algorithm of multimodal sensory data based on the thermal and optical outputs. This capability of the device can underscore the practical utility of humanoid robots to identify hazardous liquids in some scenarios like safety inspection and kitchen condiments, which addresses the critical gaps in current sensory technologies by providing a robust, sensitive, and multifunctional strategy for accurate liquid recognition. [ABSTRACT FROM AUTHOR]

Multimodal tactile sensors, as key information input channel in human‐machine interactions, have faced the significant challenges including high power‐consumption, multimodal data fusion, and wireless transmission. In this work, a battery‐free multimodal wireless tactile sensor (TC‐MWTS) based on tribo‐capacitive coupled effect for normal and shear force fusion sensing is proposed, which is enabled by a 3D structure combining a triboelectric sensor and a capacitive sensor coupled with an inductive coil. A triboelectric sensor equipped with contact‐discharge structures exhibits 25‐fold wireless signal enhancement compared to conventional triboelectric sensors. Based on the characteristics of dual time‐frequency domain information existing in the wireless signals, both normal and shear forces can simultaneously be converted into voltage amplitude V and eigenfrequency f, respectively, without crosstalk and complex decoupling signals. The TC‐MWTS exhibits a maximum sensitivity of 2.47 V kPa−1 for normal force from 2 to 30 kPa and a sensitivity of 0.28 MHz N−1 for shear force between 0.3 and 1.0 N. Finally, the excellent sensing capability of TC‐MWTS to sense complex multidimensional forces in human‐machine interaction is demonstrated. This work innovatively proposes a new mechanism and methodology for effectively fusing and processing multimodal tactile information, which may drive the tremendous development of low‐power multimodal tactile sensing system. [ABSTRACT FROM AUTHOR]

The rapid development of thermoelectric‐piezoresistive dual‐mode sensors has opened new avenues for enhancing the functionality, miniaturization, and integration of flexible tactile sensors. However, existing research primarily focuses on decoupling temperature and pressure responses, which leaves a significant gap in optimizing sensor performance and exploring multifunctional applications. To address this limitation, a composite aerogel with a layered porous structure is developed, integrating carbon nanotubes and MXene as conductive materials and reinforced with cellulose nanofibers. The innovative design, characterized by ultra‐low thermal conductivity along with superior electrical and thermoelectric properties, allows the resulting sensor to monitor temperature and pressure stimuli without interference through thermoelectric and piezoresistive mechanisms. Demonstrated results reveal exceptional sensing capabilities, including a minimum detectable temperature variation of 0.03 K and a pressure detection limit of 0.3 Pa. The sensor exhibits high sensitivities of 33.5 µV K−1 and −45.2% kPa−1, along with stability across both temperature and pressure stimuli. Furthermore, the unique multi‐modal sensing mechanism supports various applications, such as thermoelectric energy harvesting, material recognition, complex information transmission, smart wearable devices, electronic skin, and human‐computer interaction interfaces. This research presents a robust solution for designing high‐performance dual‐modal tactile sensors and significantly advances their practical applications across multiple domains. [ABSTRACT FROM AUTHOR]

We report on the evaluation and measurement of a MEMS tactile sensor designed to mimic the temporal feature detection of human tactile sensation. The proposed sensor consists of a strain-resistive gauge and a piezoelectric thin-film capacitor on a microcantilever embedded in an elastomer. The cantilever is deflected by a force, which is detected simultaneously by the two separate sensing elements: the strain gauge and the piezoelectric thin film (piezoelectric sensor). The DC resistance change of the strain gauge is detected in time synchrony with the applied force. On the other hand, the piezoelectric sensor outputs a voltage owing to the formation of a polarized charge in response to the time variation of the applied force, and thus shows a time response different from that of the strain gauge. These could potentially reproduce the timeresponsive nature of the human tactile function, which has receptive fields with different stimulus adaptation speeds. In this work, we demonstrated that different time response patterns can be obtained from each sensing element for the application of a single force or vibration. [ABSTRACT FROM AUTHOR]

Nanotubes, being one of the most sought after materials in nanotechnology, are finding new areas of application, such as filters for harmful gases. However, in practical applications of nanotubes, it often turns out that, after capturing the analyzed substance, there is no change in their electronic state. This makes it difficult to detect the fact of adsorption of a substance by electronic devices, such as touch sensors. One way to solve this problem could be to modify the surface of carbon nanotubes with various atoms, which leads to the creation of nanotubular heterostructures. One of the most effective substances for carrying out the substitution reaction is boron. It allows the creation of a redistribution of the electron density on the surface of nanotubes without introducing significant changes to the topology of the nanotube surface. This, in turn, leads to a change in the electron-energy structure of the resulting systems and can lead to a more pronounced change in this structure during the sorption of atoms and molecules on the surface of such modified nanotubes. This paper analyzes the effect of boron impurities of different concentrations on the sensory activity of such boron-modified carbon nanotubes towards carbon dioxide to study the possibility of using boron-carbon systems such as a material for high-performance sensors. [ABSTRACT FROM AUTHOR]

Soft generators hold great promise both in powering flexible electronics and in signaling specific parameter variations. In particular, mechanical motions for electricity harvest have attracted great interests due to their ubiquity and relevance to human activities. Instead of the widely reported piezoelectric and triboelectric generators, in this study an efficient electric‐double‐layer (EDL) generator is designed by embedding liquid metal (LM) into biologic porous ionogels. When pulsating LM into or out of the ionogel pores, an alternating current would be produced from the variation of EDL area between LM and ionogels. The porous ionogels are produced unprecedentedly by partially fusing biologic nanofibrils and ionic liquid, whose porosities and adhesion to LM surfaces are tuned elaborately to ensure their reversible compressibility, freely moving of LM within the internal channels and hereby maximal variation of EDL area for optimal energy harvest, e.g., showing an alternating current with amplitude up to 25 µA cm−2 and energy power of 4 mW cm−2 higher than many piezoelectric and triboelectric generators. Besides electricity harvest from motions, this soft generator can also serve as a self‐powered and highly sensitive tactile sensor. [ABSTRACT FROM AUTHOR]

The sustainable tactile electronics demonstrates huge potential in mimicking the functionality of human skin and satisfies with an eco‐friendly concept. However, on the premise of successfully introducing natural materials, such electronics are still not sufficient for improving the fatigue threshold in high‐frequency sensing scenarios. Here an eco‐ and user‐friendly cellulose integrated tactile array (CITA) is introduced that relies on laminated hierarchical architecture (LAHA) for alleviating the notorious structural vulnerability toward long‐term haptic evaluation. By cross‐validation with conventional bulky configuration, finite element simulation unveils that the LAHA leverages compact laminated adjacent layer for dramatically facilitating in‐plane stress distribution for diminishing the interfacial stress concentration, thus affords prolonged and reliable sensory augmentation. The CITA wireless monitoring system offers impeccable real‐time spatiotemporal haptic patterns on multi‐user interfaces and can substantially promote a record‐high durability (150000 cycles), showcasing low interfacial contact impedance (1.78 ± 0.4 ohm, 1 kHz), remarkably channel uniformity (97.2%), unparalleled sensitivity (12944 kPa−1), and sensing‐robustness against perturbations (e.g., humidity, temperature, and bending). It is envisioned that the proposed CITA system will open up new avenues for sustainable tactile electronics in continuous health surveillance. [ABSTRACT FROM AUTHOR]

In biomedical sciences, there is a demand for electronic skins with highly sensitive tactile sensors that have applications in patient monitoring, human–machine interfaces, and on‐body sensors. Sensor fabrication requires high‐performance conductive surfaces that are transparent, breathable, flexible, and easy to fabricate. It is also preferable if the electrodes are easily processable as wastes, for example, are degradable. In this work, the design and fabrication of hydrophilic silanol/amine‐terminated poly(caprolactone‐urethane) (SA‐PCLU) elastomer‐based breathable, stretchable, and biodegradable electrodes are reported. Ag nanowires dispersed in water are sprayed onto the intrinsically hydrophilic electrospun SA‐PCLU that became embedded into the scaffold and formed conformal hydrophilic polyurethane‐based conductive networks (HPCN). The electrodes are used to fabricate capacitive, curvature, and strain sensors, all having monomaterial composition. In addition to displaying particularly good transparencies at low sheet resistances, stretchability, hydrophilicity, and tight and conformal bonding with the target surface, the electrodes also allow the evaporation of perspiration, making them suitable for epidermal sensors for long‐time use. The application of the HPCN electrodes in flexible electronics and bionic skin applications is demonstrated through gesture monitoring experiments and swelling sensors. [ABSTRACT FROM AUTHOR]

Thin‐film transistors (TFTs) have been studied for their high mobility and stability to facilitate the development of TFT‐based touch sensors and electronic devices. A metal capping (MC) layer on the back channel of Si–Zn–Sn–O(SZTO) TFTs has been proposed to improve the electrical properties. MC, when adopted on the channel layer, has low resistance, leading to an improvement in the mobility of the TFT. The mobility of Ti/Al MC TFT has improved from 20.7 to 37.9 cm2 V−1 s compared to the pristine TFTs. Applying a potential voltage to the MC layer sensitively modulates the I–V characteristics of the TFT. The present study applies a voltage of 60 mV, similar to that of the human body, to MC‐TFTs to explore their possibilities as human touch sensors. The sensitivity and the energy bandgap modulation are also discussed. [ABSTRACT FROM AUTHOR]

Herein, the development and characterization of three distinct artificial mechanoreceptor sensors meticulously engineered is reported to emulate human skin. By mimicking the morphology, structure, and response characteristics (including preferential sensitivity, adaptation profile, and frequency response) of biological mechanoreceptors, artificial Meissner, Merkel, and Ruffini sensors capable of detecting pressure, shear, and tensile deformations with high fidelity are successfully fabricated. In situ experiments, designed to mimic physiological conditions, demonstrate that the integrated sensor array, mimicking human fingertips, can accurately discriminate seven Braille characters, five distinct surface textures, a grating with ridges, and four‐step delivery stages of an object. Furthermore, a woolen glove incorporating 15 multimodal sensors are developed, which exhibits enhanced classification capabilities for eight objects of varying sizes and surface roughness. Notably, the trimodal sensor integration demonstrates superior recognition speed and precision compared to uni‐ or bimodal configurations, while also improving tactile identification intuition. This biomimetic mechanoreceptor sensor system demonstrates comprehensive and synergistic recognition of diverse stimuli and objects, potentially overcoming technological limitations in applications requiring human‐like tactile perception, such as advanced prosthetics, robotics, and immersive augmented and virtual reality interfaces. [ABSTRACT FROM AUTHOR]

Single‐mode sensors suffer from poor robustness and insufficient data features in facial expression recognition, so fusing multi‐sensor signals is the key to improving the accuracy of expression recognition systems. Here, a biocompatible capacitive‐electromyographic dual‐mode sensor (CEDS) is presented, consisting of a capacitive pressure sensing unit and dry electrodes for electrophysiological signal monitoring, assembled in a 3D stacking fashion. A double‐coupled microstructure is prepared and the electrical double‐layer effect is realized by doping ionic liquid, which significantly improves the capacitive performance of the sensor. The application of dry electrodes effectively solves the problems of hydrogel electrodes that are prone to water loss and skin irritation. Besides, the good biocompatibility and antimicrobial properties of CEDS are verified through cytotoxicity and bacteriostatic tests. Based on the sensing of a single signal, a fatigue driving monitoring system and a manipulator control system are constructed respectively. By further integrating the capacitive and electrophysiological signal monitoring functions of CEDS, a 1D convolutional neural network‐assisted facial expression recognition system is constructed, which effectively improves the accuracy of expression recognition and demonstrates the great potential of facial expression monitoring systems based on flexible sensor technology in practical applications. [ABSTRACT FROM AUTHOR]