Touchless interactive teaching of soft robots through flexible bimodal sensory interfaces

Flexible Pressure Sensors Enhanced by 3D-Printed Microstructures

3D printing has revolutionized the development of flexible pressure sensors by enabling the precise fabrication of diverse microstructures that significantly enhance sensor performance. These advancements have substantially improved key attributes such as sensitivity, response time, and durability, facilitating applications in wearable electronics, robotics, and human-machine interfaces. This review provides a comprehensive analysis of the sensing mechanisms of these sensors, emphasizing the role of microstructures, such as micro-patterned, microporous, and hierarchical designs, in optimizing performance. The advantages of 3D printing techniques, including direct and indirect fabrication methods, in the creation of complex microstructures with high precision and adaptability are highlighted. Specific applications, including human physiological signal monitoring, motion detection, soft robotics, and emerging applications, are explored to demonstrate the versatility of these sensors. Additionally, this review briefly discusses key challenges, such as material compatibility, optimization difficulties, and environmental stability, as well as emerging trends, such as the integration of advanced technologies, innovative designs, and multidimensional sensing as promising avenues for future advancements. By summarizing recent progress and identifying opportunities for innovation, this review provides critical insights into bridging the gap between research and real-world applications, helping to accelerate the evolution of flexible pressure sensors with sophisticated 3D-printed microstructures.

Bat-Inspired Bionic Bimodal Active Cognitive Electronic Skin with Multisensory Integration Ability

Empowering intelligent robots with cognitive abilities that rival or even surpass those of humans is the key to enabling more complex and sophisticated interactions. Currently, most electronic skins (e-skins) perform excellently in distinguishing shallow object properties, but they still face significant challenges in perceiving deeper object properties. Here, inspired by the multisensory integrated cognition of echolocation and tactility in bats, a bionic bimodal active cognition (BBAC) e-skin is designed. This e-skin utilizes feature fusion machine learning methods to evolve from passive perception to advanced active cognition and, further, constructs a bimodal enhanced intelligent material cognition system based on multilayer perceptron. This system enables intelligent robotic hands integrated with BBAC e-skin to achieve synergistic cognition of dielectric constant, softness, and material types of 8 smooth surface objects through a simple proximity and contact action without strictly controlling the test conditions, significantly surpassing the ability of humans.

Optimized Magnetization Distribution in Body-Centered Cubic Lattice-Structured Magnetoelastomer for High-Performance 3D Force-Tactile Sensors

Flexible magnetic tactile sensors hold transformative potential in robotics and human-computer interactions by enabling precise force detection. However, existing sensors face challenges in balancing sensitivity, detection range, and structural adaptability for sensing force. This study proposed a pre-compressed magnetization method to address these limitations by amplifying the magnetoelastic effect through optimized magnetization direction distribution of the elastomer. A body-centered cubic lattice-structured magnetoelastomer featuring regular deformation under compression was fabricated via digital light processing (DLP) to validate this method. Finite element simulations and experimental analyses revealed that magnetizing the material under 60% compression strain optimized magnetization direction distribution, enhancing force-magnetic coupling. Integrating the magnetic elastomer with a hall sensor, the prepared tactile sensor demonstrated a low detection limit (1 mN), wide detection range (0.001-10 N), rapid response/recovery times (40 ms/50 ms), and durability (>1500 cycles). By using machine learning, the sensor enabled accurate 3D force prediction.

Wearable Self-Powered Pressure Sensors Based on alk-Ti3C2Tx Regulating Contact Barrier Difference for Noncontact Motion Object Recognition

Wearable self-powered pressure sensors present tremendous potential for object recognition. However, the fluctuated approach speed and distance may compromise the device output, thus affecting the recognition accuracy. Herein, a wearable self-powered pressure sensor with high sensitivity (1.48 V kPa-1), high output (130.5V), and high permeability (259.98 mm s-1) are developed where the contact barrier difference and triboelectric charge density of the triboelectric layer surface are dynamically regulated by modulating the surface groups resulting in a lower dielectric loss and higher output. The sensor leverages the polarity difference between the target object and the sensitive material to generate electrical signals at different speeds and distances through an electrostatic induction mechanism. With the assistance of the Transformer model with a self-attention mechanism, an average recognition accuracy of 94.3% is achieved by acquiring sensing signals at different speeds and distances. Simulating the ability of human vision, enables visually impaired people to acclimate to their surroundings more easily and independently and provides a critical advancement in the assistance of the blind with daily life.

Soft Materials and Devices Enabling Sensorimotor Functions in Soft Robots

Sensorimotor functions, the seamless integration of sensing, decision-making, and actuation, are fundamental for robots to interact with their environments. Inspired by biological systems, the incorporation of soft materials and devices into robotics holds significant promise for enhancing these functions. However, current robotics systems often lack the autonomy and intelligence observed in nature due to limited sensorimotor integration, particularly in flexible sensing and actuation. As the field progresses toward soft, flexible, and stretchable materials, developing such materials and devices becomes increasingly critical for advanced robotics. Despite rapid advancements individually in soft materials and flexible devices, their combined applications to enable sensorimotor capabilities in robots are emerging. This review addresses this emerging field by providing a comprehensive overview of soft materials and devices that enable sensorimotor functions in robots. We delve into the latest development in soft sensing technologies, actuation mechanism, structural designs, and fabrication techniques. Additionally, we explore strategies for sensorimotor control, the integration of artificial intelligence (AI), and practical application across various domains such as healthcare, augmented and virtual reality, and exploration. By drawing parallels with biological systems, this review aims to guide future research and development in soft robots, ultimately enhancing the autonomy and adaptability of robots in unstructured environments.

Wearable Mechanoluminescent Triboelectric Sensors for Real-Time Monitoring of Nighttime Sports Activities

Smart clothing that integrates active luminescence and motion monitoring holds significant importance for enhancing safety during nighttime activities. In this study, by combining mechanoluminescent materials (ZnS/Cu) with triboelectric nanogenerators, an intelligent yoga pant that actively emits light and senses joint movements during physical activities has been fabricated. The incorporation of silver fiber electrodes ensures breathability throughout the mechanoluminescent triboelectric sensor (MTS), contributing to the high comfort of wearable smart clothing. The doping of ZnS/Cu with organic silicone rubber enhances the dielectric constant of the triboelectric layer, thereby effectively enhancing the output signal of the MTS. Moreover, the mechanoluminescent materials convert the tension applied during joint flexion into dynamically varying light, alerting passing vehicles and safeguarding users during nighttime activities. An in-depth investigation was conducted on the relationship between the content of luminescent materials and the device's light intensity and output voltage under the same stretching conditions. The integration of a wearable signal acquisition system ensures real-time output of the electrical signals from the MTS during running, enabling online real-time monitoring of motion indicators such as joint bending angles and step counts. These findings provide feasible insights for the development of breathable, active luminescent smart clothing.

Bio-inspired organic electrosense transistor for impalpable perception

Artificial sense technologies predominantly rely on visual and tactile input, which often prove inadequate in obscured or opaque environments. Inspired by the natural electrosensory capabilities of electrogenic fishes, we introduce an organic electrosense transistor designed to detect electric fields generated by nearby objects, facilitating the creation of impalpable perception systems. Unlike traditional sensors, our electrosense transistor perceives bipolar electric fields with high sensitivity and stability. We use compact models and device simulations to elucidate the mechanisms of charge induction and transport within organic electrosense transistors when exposed to spatial electric fields. Demonstrating its practical utility, we show that robots equipped with our electrosense transistor can successfully navigate and detect concealed objects without requiring direct contact. This work not only advances the understanding of charge dynamics in electrosensory systems but also establishes a platform for developing highly sensitive, noninvasive artificial sensing technologies applicable in surveillance, search and rescue, and other challenging environments.

A natural biomimetic prosthetic hand with neuromorphic tactile sensing for precise and compliant grasping

The human hand's hybrid structure combines soft and rigid anatomy to provide strength and compliance for versatile object grasping. Tactile sensing by skin mechanoreceptors enables precise and dynamic manipulation. Attempts to replicate the human hand have fallen short of a true biomimetic hybrid robotic hand with tactile sensing. We introduce a natural prosthetic hand composed of soft robotic joints and a rigid endoskeleton with three independent neuromorphic tactile sensing layers inspired by human physiology. Our innovative design capitalizes on the strengths of both soft and rigid robots, enabling the hybrid robotic hand to compliantly grasp numerous everyday objects of varying surface textures, weight, and compliance while differentiating them with 99.69% average classification accuracy. The hybrid robotic hand with multilayered tactile sensing achieved 98.38% average classification accuracy in a texture discrimination task, surpassing soft robotic and rigid prosthetic fingers. Controlled via electromyography, our transformative prosthetic hand allows individuals with upper-limb loss to grasp compliant objects with precise surface texture detection.

Hollow fiber-based strain sensors with desirable modulus and sensitivity at effective deformation for dexterous electroelastomer cylindrical actuator

The electroelastomer cylindrical actuators, a typical representation of soft actuators, have recently aroused increasing interest owing to their advantages in flexibility, deformability, and spatial utilization rate. Proprioception is crucial for controlling and monitoring the shape and position of these actuators. However, most existing flexible sensors have a modulus mismatch with the actuation unit, hindering the free movement of these actuators. Herein, a low-modulus strain sensor based on laser-induced cellular graphitic flakes (CGF) onto the surface of hollow TPU fibers (HTF) is present. Through the electrostatic self-assembly technology, the flexible sensor features a unique hybrid sensing unit including soft HTF as substrate and rigid CGF as conductive path. As a result, the sensor simultaneously possesses desirable modulus (~0.155 MPa), a gauge factor of 220.3 (25% < ε < 50%), fast response/recovery behaviors (31/62 ms), and a low detection limit (0.1% strain). Integrating the sensor onto the electroelastomer cylindrical actuators enables precise measurement of deformation modes, directions, and quantity. As proof-of-concept demonstrations, a prototype soft robot with high-precision perception is successfully designed, achieving real-time detection of its deformations during the crawling process. Thus, the proposed scheme sheds new light on the development of intelligent soft robots.

Biodegradable origami enables closed-loop sustainable robotic systems

Robots are increasingly integral across various sectors due to their efficiency and superior capabilities, which enable performance beyond human potential. However, the development of robotic systems often conflicts with the sustainable development goals set by the United Nations, as they generate considerable nondegradable waste and organic/inorganic pollutants throughout their life cycle. In this paper, we introduce a dual closed-loop robotic system that integrates biodegradable, sustainable materials such as plasticized cellulose films and NaCl-infused ionic conductive gelatin organogels. These materials undergo a closed-loop ecological cycle from processing to biodegradation, contributing to new growth, while the self-sensing, origami-based robot supports a seamless human-in-the-loop teleoperation system. This innovative approach represents a paradigm shift in the application of soft robotic systems, offering a path toward a more sustainable future by aligning advanced robotic functionalities with environmental stewardship.

Soft Crawling Microrobot Based on Flexible Optoelectronics Enabling Autonomous Phototaxis in Terrestrial and Aquatic Environments

Many organisms move directly toward light for prey hunting or navigation, which is called phototaxis. Mimicking this behavior in robots is crucially important in the energy industry and environmental exploration. However, the phototaxis robots with rigid bodies and sensors still face challenges in adapting to unstructured environments, and the soft phototaxis robots often have high requirements for light sources with limited locomotion performance. Here, we report a 3.5 g soft microrobot that can perceive the azimuth angle of light sources and exhibit rapid phototaxis locomotion autonomously enabled by three-dimensional flexible optoelectronics and compliant shape memory alloy (SMA) actuators. The optoelectronics is assembled from a planar patterned flexible circuit with miniature photodetectors, introducing the self-occlusion to light, resulting in high sensing ability (error < 3.5°) compared with the planar counterpart. The actuator produces a straightening motion driven by an SMA wire and is then returned to a curled shape by a prestretched elastomer layer. The actuator exhibits rapid actuation within 0.1 s, a significant degree of deformation (curvature change of ∼87 m-1) and a blocking force of ∼0.4 N, which is 68 times its own weight. Finally, we demonstrated the robot is capable of autonomously crawling toward a moving light source in a hybrid aquatic-terrestrial environment without human intervention. We envision that our microrobot could be widely used in autonomous light tracking applications.

Mechano-Graded Contact-Electrification Interfaces Based Artificial Mechanoreceptors for Robotic Adaptive Reception

Triboelectrification-based artificial mechanoreceptors (TBAMs) is able to convert mechanical stimuli directly into electrical signals, realizing self-adaptive protection and human-machine interactions of robots. However, traditional contact-electrification interfaces are prone to reaching their deformation limits under large pressures, resulting in a relatively narrow linear range. In this work, we fabricated mechano-graded microstructures to modulate the strain behavior of contact-electrification interfaces, simultaneously endowing the TBAMs with a high sensitivity and a wide linear detection range. The presence of step regions within the mechanically graded microstructures helps contact-electrification interfaces resist fast compressive deformation and provides a large effective area. The highly sensitive linear region of TBAM with 1.18 V/kPa can be effectively extended to four times of that for the devices with traditional interfaces. In addition, the device is able to maintain a high sensitivity of 0.44 V/kPa even under a large pressure from 40 to 600 kPa. TBAM has been successfully used as an electronic skin to realize self-adaptive protection and grip strength perception for a commercial robot arm. Finally, a high angle resolution of 2° and an excellent linearity of 99.78% for joint bending detection were also achieved. With the aid of a convolutional neural network algorithm, a data glove based on TBAMs realizes a high accuracy rate of 95.5% for gesture recognition in a dark environment.

A Force-Thermal-Magnetic Trimodal Flexible Sensor for Ultrafine Recognition of Metallic Materials

Humans possess the remarkable ability to perceive the intricate world by integrating multiple senses. However, the challenge of enabling humanoid robots to achieve multimodal sensing and fine recognition of metallic materials persists. In this study, we propose a flexible tactile sensor that mimics the sensory patterns of human skin, which is assembled by a flexible electromagnetic coil that is engraved on the surface of a polyimide substrate and porous MXene/CNT aerogel. This sensor is capable of detecting pressure, temperature, and inductive signals with minimal interference via three disparate response mechanisms of the piezoresistive sensing, the thermoelectric principle, and the electromagnetic induction effect, allowing the device with the abilities of sensing grasp forces and selectively identifying ferromagnetic and nonferromagnetic metals, which has a high accuracy rate of 99.2% in distinguishing mixed metals with varying ratios based on the fusion algorithm of multimodal sensory data. Further, the sensor was integrated on a humanoid robotic hand to demonstrate its recognition capacity of objects used in a kitchen setting and a simulated scenario of mineral exploration, achieving a remarkable ultrafine accuracy of 100% in distinguishing 16 common metal products. These findings will pave the way for humanoid robots to attain heightened levels of perception and recognition.

Programmable Robotic Shape Shifting and Color Morphing Dynamics Through Magneto-Mechano-Chromic Coupling

Recreating natural organisms' dynamic shape-morphing and adaptive color-changing capabilities in a compact structure poses significant challenges but unlocks unprecedented hybridized robotic-visual applications. Overcoming programmability and predictability obstacles is key to achieving real-time, responsive changes in appearance and functionality, enhancing robot-environment-user interactions in ways previously unattainable. Herein, a Soft Magneto-Mechano-Chromic (SoMMeC) structure comprising a magnetic actuating and a synthetic photonic film, mirroring the intricate color-tuning mechanism of chameleons is devised. A model combining numerical simulation and a strain-dependent color evolution map enables precise predictions and controllable shape-color alterations across various geometrical and magnetization profiles. The SoMMeC exhibits rapid (0.1s), broad (full-visible spectrum), tether-free (remote magnetic manipulation), and programmable (model-guided control) color transformations, surpassing traditional limitations with its real-time response, broad and omnidirectional coloration for enhanced visibility, and robustness against external disturbances. The SoMMeC translates into dynamic advertising iridescence, adaptive camouflage, self-sensing, and multi-level encryption, and transcends traditional robotics by seamlessly blending dynamic movement with nuanced visual changes. It opens up a spectrum of applications that redefine robotic functionality through dynamic appearance modulation, making robotic systems more versatile, adaptive, and suitable for unexplored integrative functions.

Silk Flocked Flexible Sensor Capable of Wide-Range and Sensitive Pressure Perception

In recent years, there have been advancements in high-performance soft sensors with simultaneous moderate sensitivity and wide linearity. However, it remains challenging to combine high-efficiency production and high performance for soft sensors. The skin and hair structure provide an elegantly simple sensing model, where hair acts as signal receptors and basal skin acts as signal processors. Herein, we used efficient electrostatic flocking and extrusion printing to engineer comb-shaped electrodes with conductive polydimethylsiloxane (PDMS) flocked with conductive silk fibers as a biomimetic flexible sensor. The mechanical and electrical properties of modified PDMS and silk fibers were characterized to optimize the functionalization process. The sensor unit exhibited a high linear range up to 2,000 kPa and a competitively good sensitivity of 0.0285 kPa-1 in the contact mode with conductive materials, as well as good resolution in the noncontact mode. Such sensors and a sensor array demonstrated potential applications for detecting pressure disturbances from acoustic activity and for human-robot interactions. We anticipate that the straightforward design and facile fabrication of soft sensors with vertical fibrous morphology for perception will open new avenues for the next generation of high-performance soft sensors integrated with artificial intelligence.

Sensing expectation enables simultaneous proprioception and contact detection in an intelligent soft continuum robot

A high-level perceptual model found in the human brain is essential to guide robotic control when facing perception-intensive interactive tasks. Soft robots with inherent softness may benefit from such mechanisms when interacting with their surroundings. Here, we propose an expected-actual perception-action loop and demonstrate the model on a sensorized soft continuum robot. By sensing and matching expected and actual shape (1.4% estimation error on average), at each perception loop, our robot system rapidly (detection within 0.4 s) and robustly detects contact and distinguishes deformation sources, whether external and internal actions are applied separately or simultaneously. We also show that our soft arm can accurately perceive contact direction in both static and dynamic configurations (error below 10°), even in interactive environments without vision. The potential of our method are demonstrated in two experimental scenarios: learning to autonomously navigate by touching the walls, and teaching and repeating desired configurations of position and force through interaction with human operators.

Mormyroidea-inspired electronic skin for active non-contact three-dimensional tracking and sensing

The capacity to discern and locate positions in three-dimensional space is crucial for human-machine interfaces and robotic perception. However, current soft electronics can only obtain two-dimensional spatial locations through physical contact. In this study, we report a non-contact position targeting concept enabled by transparent and thin soft electronic skin (E-skin) with three-dimensional sensing capabilities. Inspired by the active electrosensation of mormyroidea fish, this E-skin actively ascertains the 3D positions of targeted objects in a contactless manner and can wirelessly convey the corresponding positions to other devices in real-time. Consequently, this E-skin readily enables interaction with machines, i.e., manipulating virtual objects, controlling robotic arms, and drones in either virtual or actual 3D space. Additionally, it can be integrated with robots to provide them with 3D situational awareness for perceiving their surroundings, avoiding obstacles, or tracking targets.

Tactile Sensing and Rendering Patch with Dynamic and Static Sensing and Haptic Feedback for Immersive Communication

Wearable human-machine interface (HMI) with bidirectional and multimodal tactile information exchange is of paramount importance in teleoperation by providing more intuitive data interpretation and delivery of tactilely related signals. However, the current sensing and feedback devices still lack enough integration and modalities. Here, we present a Tactile Sensing and Rendering Patch (TSRP) that is made of a customized expandable array which consists of a piezoelectric sensing and feedback unit fused with an elastomeric triboelectric multidimensional sensor and its inner pneumatic feedback structure. The primary functional unit of TSRP is mainly featured with a soft silicone substrate with compact multilayer structure integrating static and dynamic multidimensional tactile sensing capabilities, which synergistically leverage both triboelectric and piezoelectric effects. Additionally, based on the air chamber created by the triboelectric sensor and the converse piezoelectric effect, it provides pneumatic and vibrational haptic feedback simultaneously for both static and dynamic perception regeneration. With the aid of the other variants of this unit, the array shaped TSRP is capable of simulating different terrains, geometries, sliding, collisions, and other critical interactive events during teleoperation via skin perception. Moreover, immediate manipulation can be done on TSRP through the tactile sensors. The preliminary demonstration of TSRP interface with a completed control module in robotic teleoperation is provided, which shows the feasibility of assisting certain tasks in a complex environment by direct tactile communication. The proposed device offers a potential method of enabling bidirectional tactile communication with enriched key information for improving interaction efficiency in the fields of robot teleoperation and training.

Dual Interactive Mode Human-Machine Interfaces Based on Triboelectric Nanogenerator and IGZO/In2O3 Heterojunction Synaptic Transistor

Imitating human neural networks via bio-inspired electronics advances human-machine interfaces (HMI), overcoming von Neumann limitations and enabling efficient, low-energy data processing in the big data era. However, single-contact mode HMIs have inherent limitations in terms of their capabilities and performances, such as constrained adaptability to dynamic environments, and reduced cognitive processing capabilities. Here, a dual-interactive-mode HMI system based on a triboelectric nanogenerator (TENG) and heterojunction synaptic transistor (HJST) is proposed for both contact and non-contact applications. The TENG incorporates a poly-methyl meth-acrylate (PMMA)-NiCo2S4/S film, in which the NiCo2S4/S composite traps and blocks electrons to optimize charge generation and storage. The heterojunction structure, mitigates the Debye screening effect, thereby improving transistor characteristics and reliability. The integrated TENG-HJST system exhibits synaptic functions, including excitatory/inhibitory postsynaptic current (EPSC/IPSC), paired-pulse facilitation/depression (PPF/PPD), and synaptic plasticity, enabling emulation of neural behavior and advanced information processing. Moreover, neural morphology manipulation is demonstrated in practical tasks, such as controlling international chess games. By integrating the TENG-HJST device with a robotic hand, conscious artificial responses are generated, enhancing event accuracy. This breakthrough in dual-interactive-mode interfacing holds promise for HMI systems and neural prostheses.

Economically viable electromechanical tensile testing equipment for stretchable sensor assessment

The growing interest in soft robotics increases the demand for stretchable sensors. The high performance of stretchable sensors depends much on the linearity, reliability and hysteresis of the stretchable conductive materials. In the applications of conductive materials such as in dielectric elastomer actuators, a stretchable conductive material should maintain the conductivity while sustaining large and multiple cycles of stretch and release tests. To understand the stretchable electrode quality, researchers should perform an electromechanical test. However, researchers require a high investment cost to use a professional type of electromechanical tensile test. In this research, we proposed an economically viable version of the Do-it-yourself (DIY) electromechanical tensile test (EMTT) to resolve the high investment cost problems. The DIY-EMTT is based on the Arduino-nano module. We integrate the load cell, displacement sensor, motor linear stage and DIY resistance meter. We can use the DIY mechanism to suppress the instrumental cost from thousands to hundreds of dollars. Furthermore, we provide a step-by-step guide to build the DIY-EMTT. We expect our DIY-EMTT to boost stretchable sensor development in soft robotics.

Stretchable and Self-Powered Mechanoluminescent Triboelectric Nanogenerator Fibers toward Wearable Amphibious Electro-Optical Sensor Textiles

Flexible electro-optical dual-mode sensor fibers with capability of the perceiving and converting mechanical stimuli into digital-visual signals show good prospects in smart human-machine interaction interfaces. However, heavy mass, low stretchability, and lack of non-contact sensing function seriously impede their practical application in wearable electronics. To address these challenges, a stretchable and self-powered mechanoluminescent triboelectric nanogenerator fiber (MLTENGF) based on lightweight carbon nanotube fiber is successfully constructed. Taking advantage of their mechanoluminescent-triboelectric synergistic effect, the well-designed MLTENGF delivers an excellent enhancement electrical signal of 200% and an evident optical signal whether on land or underwater. More encouragingly, the MLTENGF device possesses outstanding stability with almost unchanged sensitivity after stretching for 200%. Furthermore, an extraordinary non-contact sensing capability with a detection distance of up to 35 cm is achieved for the MLTENGF. As application demonstrations, MLTENGFs can be used for home security monitoring, intelligent zither, traffic vehicle collision avoidance, and underwater communication. Thus, this work accelerates the development of wearable electro-optical textile electronics for smart human-machine interaction interfaces.

Multiple Self-Powered Sensor-Integrated Mobile Manipulator for Intelligent Environment Detection

A multiple self-powered sensor-integrated mobile manipulator (MSIMM) system was proposed to address challenges in existing exploration devices, such as the need for a constant energy supply, limited variety of sensed information, and difficult human-computer interfaces. The MSIMM system integrates triboelectric nanogenerator (TENG)-based self-powered sensors, a bionic manipulator, and wireless gesture control, enhancing sensor data usability through machine learning. Specifically, the system includes a tracked vehicle platform carrying the manipulator and electronics, including a storage battery and a microcontroller unit (MCU). An integrated sensor glove and terminal application (APP) enable intuitive manipulator control, improving human-computer interaction. The system responds to and analyzes various environmental stimuli, including the droplet and fall height, temperature, pressure, material type, angles, angular velocity direction, and acceleration amplitude and direction. The manipulator, fabricated using 3D printing technology, integrates multiple sensors that generate electrical signals through the triboelectric effect of mechanical motion. These signals are classified using convolutional neural networks for accurate environmental monitoring. Our database shows signal recognition and classification accuracy exceeding 94%, with specific accuracies of 100% for pressure sensors, 99.55% for angle sensors, and 98.66, 95.91, 96.27, and 94.13% for material, droplet, temperature, and acceleration sensors, respectively.

Bioinspired Liquid Metal Based Soft Humanoid Robots

The pursuit of constructing humanoid robots to replicate the anatomical structures and capabilities of human beings has been a long-standing significant undertaking and especially garnered tremendous attention in recent years. However, despite the progress made over recent decades, humanoid robots have predominantly been confined to those rigid metallic structures, which however starkly contrast with the inherent flexibility observed in biological systems. To better innovate this area, the present work systematically explores the value and potential of liquid metals and their derivatives in facilitating a crucial transition towards soft humanoid robots. Through a comprehensive interpretation of bionics, an overview of liquid metals' multifaceted roles as essential components in constructing advanced humanoid robots-functioning as soft actuators, sensors, power sources, logical devices, circuit systems, and even transformable skeletal structures-is presented. It is conceived that the integration of these components with flexible structures, facilitated by the unique properties of liquid metals, can create unexpected versatile functionalities and behaviors to better fulfill human needs. Finally, a revolution in humanoid robots is envisioned, transitioning from metallic frameworks to hybrid soft-rigid structures resembling that of biological tissues. This study is expected to provide fundamental guidance for the coming research, thereby advancing the area.

A Sensorized Soft Robotic Hand with Adhesive Fingertips for Multimode Grasping and Manipulation

Soft robotic grippers excel at achieving conformal and reliable contact with objects without the need for complex control algorithms. However, they still lack in grasp and manipulation abilities compared with human hands. In this study, we present a sensorized multi-fingered soft gripper with bioinspired adhesive fingertips that can provide both fingertip-based adhesion grasping and finger-based form closure grasping modes. The gripper incorporates mushroom-like microstructures on its adhesive fingertips, enabling robust adhesion through uniform load shearing. A single fingertip exhibits a maximum load capacity of 4.18 N against a flat substrate. The soft fingers have multiple joints, and each joint can be independently actuated through pneumatic control. This enables diverse bending motions and stable grasping of various objects, with a maximum load capacity of 28.29 N for three fingers. In addition, the soft gripper is equipped with a kirigami-patterned stretchable sensor for motion monitoring and control. We demonstrate the effectiveness of our design by successfully grasping and manipulating a diverse range of objects with varying shapes, sizes, and curvatures. Moreover, we present the practical application of our sensorized soft gripper for remotely controlled cooking.

Biomimetic bimodal haptic perception using triboelectric effect

Multimodal haptic perception is essential for enhancing perceptual experiences in augmented reality applications. To date, several artificial tactile interfaces have been developed to perceive pressure and precontact signals, while simultaneously detecting object type and softness with quantified modulus still remains challenging. Here, inspired by the campaniform sensilla on insect antennae, we proposed a hemispherical bimodal intelligent tactile sensor (BITS) array using the triboelectric effect. The system is capable of softness identification, modulus quantification, and material type recognition. In principle, due to the varied deformability of materials, the BITS generates unique triboelectric output fingerprints when in contact with the tested object. Furthermore, owing to the different electron affinities, the BITS array can accurately recognize material type (99.4% accuracy), facilitating softness recognition (100% accuracy) and modulus quantification. It is promising that the BITS based on the triboelectric effect has the potential to be miniaturized to provide real-time accurate haptic information as an artificial antenna toward applications of human-machine integration.

An intelligent spinal soft robot with self-sensing adaptability

Self-sensing adaptability is a high-level intelligence in living creatures and is highly desired for their biomimetic soft robots for efficient interaction with the surroundings. Self-sensing adaptability can be achieved in soft robots by the integration of sensors and actuators. However, current strategies simply assemble discrete sensors and actuators into one robotic system and, thus, dilute their synergistic and complementary connections, causing low-level adaptability and poor decision-making capability. Here, inspired by vertebrate animals supported by highly evolved backbones, we propose a concept of a bionic spine that integrates sensing and actuation into one shared body based on the reversible piezoelectric effect and a decoupling mechanism to extract the environmental feedback. We demonstrate that the soft robots equipped with the bionic spines feature locomotion speed improvements between 39.5% and 80% for various environmental terrains. More importantly, it can also enable the robots to accurately recognize and actively adapt to changing environments with obstacle avoidance capability by learning-based gait adjustments. We envision that the proposed bionic spine could serve as a building block for locomotive soft robots toward more intelligent machine-environment interactions in the future.

Facile Electret-Based Self-Powered Soft Sensor for Noncontact Positioning and Information Translation

Noncontact sensors have demonstrated significant potential in human-machine interactions (HMIs) in terms of hygiene and less wear and tear. The development of soft, stable, and simply structured noncontact sensors is highly desired for their practical applications in HMIs. This work reports on electret-based self-powered noncontact sensors that are soft, transparent, stable, and easy to manufacture. The sensors contain a three-layer structure with a thickness of 0.34 mm that is fabricated by simply stacking a polymeric electret layer, an electrode layer, and a substrate layer together. The fabricated sensors show high charge-retention capability, keeping over 98% of the initial surface potential even after 90 h, and can accurately and repeatedly sense external approaching objects with impressive durability. The intensity of the detected signal shows a strong dependence on the distance between the object and the sensor, capable of sensing a distance as small as 2 mm. Furthermore, the sensors can report stable signals in response to external objects over 3000 cycles. By virtue of the signal dependence on distance, an intelligent noncontact positioning system is developed that can precisely detect the location of an approaching object. Finally, by integrating with eyeglasses, the transparent sensor successfully captures the movements of blinks for information translation. This work may contribute to the development of stable and easily manufactured noncontact soft sensors for HMI applications, for instance, assisting with communication for locked-in syndrome patients.

A Dual-Modal Hybrid Gripper with Wide Tunable Contact Stiffness Range and High Compliance for Adaptive and Wide-Range Grasping Objects with Diverse Fragilities

The difficulties of traditional rigid/soft grippers in meeting the increasing performance expectations (e.g., high grasping adaptability and wide graspable objects range) of a single robotic gripper have given birth to numerous soft-rigid coupling grippers with promising performance. However, it is still hard for these hybrid grippers to adaptively grasp various objects with diverse fragilities intact, such as incense ash and orange, due to their limited contact stiffness adjustable range and compliance. To solve these challenging issues, herein, we propose a dual-modal hybrid gripper, whose fingers contain a detachable elastomer-coated flexible sheet that is restrained by a moving frame as a teardrop shape. The gripper's two modes switched by controlling the moving frame position can selectively highlight the low contact stiffness and excellent compliance of the teardrop-shaped flexible sheets and the high contact stiffness of the moving frames. Moreover, the contact stiffness of the teardrop-shaped sheets can be wide-range adjusted by online controlling the moving frame position and offline replacing the sheets with different thicknesses. The compliance of the teardrop-shaped sheets also proves to be excellent compared with an Ecoflex 10 fingertip with the same profile. Such a gripper with wide-range tunable contact stiffness and high compliance demonstrates excellent grasping adaptability (e.g., it can safely grasp several fragile strawberries with a maximum size difference of 18 mm, a strawberry with a left/right offset of 3 cm, and a strawberry in two different lying poses) and wide-range graspable objects (from 0.1 g super fragile cigarette ashes to 5.1 kg dumbbell).

A Soft Collaborative Robot for Contact-based Intuitive Human Drag Teaching

Soft material-based robots, known for their safety and compliance, are expected to play an irreplaceable role in human-robot collaboration. However, this expectation is far from real industrial applications due to their complex programmability and poor motion precision, brought by the super elasticity and large hysteresis of soft materials. Here, a soft collaborative robot (Soft Co-bot) with intuitive and easy programming by contact-based drag teaching, and also with exceptional motion repeatability (< 0.30% of body length) and ultra-low hysteresis (< 2.0%) is reported. Such an unprecedented capability is achieved by a biomimetic antagonistic design within a pneumatic soft robot, in which cables are threaded to servo motors through tension sensors to form a self-sensing system, thus providing both precise actuation and dragging-aware collaboration. Hence, the Soft Co-bots can be first taught by human drag and then precisely repeat various tasks on their own, such as electronics assembling, machine tool installation, etc. The proposed Soft Co-bots exhibit a high potential for safe and intuitive human-robot collaboration in unstructured environments, promoting the immediate practical application of soft robots.

Contactless User-Interactive Sensing Display for Human-Human and Human-Machine Interactions

Creating a large-scale contactless user-interactive sensing display (CUISD) with optimal features is challenging but crucial for efficient human-human or human-machine interactions. This study reports a CUISD based on dynamic alternating current electroluminescence (ACEL) that responds to humidity. Subsecond humidity-induced luminescence is achieved by integrating a highly responsive hydrogel into the ACEL layer. The patterned silver nanofiber electrode and luminescence layer, produced through electrospinning and microfabrication, result in a stretchable, large-scale, high-resolution, multicolor, and dynamic CUISD. The CUISD is implemented for the real-time control of a remote-controlled car, wherein the luminescence signals induced by touchless finger movements are distinguished and encoded to deliver specific commands. Moreover, the distinctive recognition of breathing facilitates the CUISD to serve as a visual signal transmitter for information interaction, which is particularly beneficial for individuals with disabilities. The paradigm shift depicts in this work is expected to reshape the way authors interact with each other and devices, discovering niche applications in virtual/augmented reality and the metaverse.

Self-Perceptional Soft Robotics by a Dielectric Elastomer

Soft robotics has been a rapidly growing field in recent decades due to its advantages of softness, deformability, and adaptability to various environments. However, the separation of perception and actuation in soft robot research hinders its progress toward compactness and flexibility. To address this limitation, we propose the use of a dielectric elastomer actuator (DEA), which exhibits both an actuation capability and perception stability. Specifically, we developed a DEA array to localize the 3D spatial position of objects. Subsequently, we integrate the actuation and sensing properties of DEA into soft robots to achieve self-perception. We have developed a system that integrates actuation and sensing and have proposed two modes to achieve this integration. Furthermore, we demonstrated the feasibility of this system for soft robots. When the robots detect an obstacle or an approaching object, they can swiftly respond by avoiding or escaping the obstacle. By eliminating the need for separate perception and motion considerations, self-perceptional soft robots can achieve an enhanced response performance and enable applications in a more compact and flexible field.

Video feedback approach to improve clinical teaching of gastroenterology for nursing students

AIMS

To investigate effect of a video feedback approach in clinical teaching of gastroenterology for nursing students.

METHODS

In this study, we selected 100 eligible student interns who meet the enrollment criteria from The First Affiliated Hospital of Ningbo University from March 2021 to March 2023. According to their personal choices, 50 interns were assigned to a control group (traditional teaching methods), while the other 50 interns were assigned to an observation group (video feedback methods). We compared theoretical knowledge, practical skills, and comprehensive ward-round abilities between the two groups, as well as doing an evaluation of teaching behaviors of the supervising teachers at the end of the clinical internship.

RESULTS

The observation group significantly outperformed the control group in theoretical and practical assessments (P<0.05). The observation group also scored higher in nursing inquiry, examination, diagnosis, interventions, health consultation, humanistic care, organizational effectiveness, and overall evaluation (P<0.05). In addition, the total score of critical thinking (267.24±16.87 points) and scores of the individual dimensions in the observation group were higher than those of the control group (257.64±13.84 points), (P<0.001).

CONCLUSION

The video feedback method can effectively improve the theoretical knowledge, practical skills, and overall ward-round performance of students in clinical nursing interns in the field of gastroenterology. Additionally, this approach can standardize teaching behaviors and enhance student satisfaction.

A multifunctional flexible sensor based on PI-MXene/SrTiO3 hybrid aerogel for tactile perception

The inadequacy of tactile perception systems in humanoid robotic manipulators limits the breadth of available robotic applications. Here, we designed a multifunctional flexible tactile sensor for robotic fingers that provides capabilities similar to those of human skin sensing modalities. This sensor utilizes a novel PI-MXene/SrTiO3 hybrid aerogel developed as a sensing unit with the additional abilities of electromagnetic transmission and thermal insulation to adapt to certain complex environments. Moreover, polyimide (PI) provides a high-strength skeleton, MXene realizes a pressure-sensing function, and MXene/SrTiO3 achieves both thermoelectric and infrared radiation response behaviors. Furthermore, via the pressure response mechanism and unsteady-state heat transfer, these aerogel-derived flexible sensors realize multimodal sensing and recognition capabilities with minimal cross-coupling. They can differentiate among 13 types of hardness and four types of material from objects with accuracies of 94% and 85%, respectively, using a decision tree algorithm. In addition, based on the infrared radiation-sensing function, a sensory array was assembled, and different shapes of objects were successfully recognized. These findings demonstrate that this PI-MXene/SrTiO3 aerogel provides a new concept for expanding the multifunctionality of flexible sensors such that the manipulator can more closely reach the tactile level of the human hand. This advancement reduces the difficulty of integrating humanoid robots and provides a new breadth of application scenarios for their possibility.

Flexible sensors with zero Poisson's ratio

Flexible sensors have been developed for the perception of various stimuli. However, complex deformation, usually resulting from forces or strains from multi-axes, can be challenging to measure due to the lack of independent perception of multiaxial stimuli. Herein, flexible sensors based on the metamaterial membrane with zero Poisson's ratio (ZPR) are proposed to achieve independent detection of biaxial stimuli. By deliberately designing the geometric dimensions and arrangement parameters of elements, the Poisson's ratio of an elastomer membrane can be modulated from negative to positive, and the ZPR membrane can maintain a constant transverse dimension under longitudinal stimuli. Due to the accurate monitoring of grasping force by ZPR sensors that are insensitive to curvatures of contact surfaces, rigid robotic manipulators can be guided to safely grasp deformable objects. Meanwhile, the ZPR sensor can also precisely distinguish different states of manipulators. When ZPR sensors are attached to a thermal-actuation soft robot, they can accurately detect the moving distance and direction. This work presents a new strategy for independent biaxial stimuli perception through the design of mechanical metamaterials, and may inspire the future development of advanced flexible sensors for healthcare, human-machine interfaces and robotic tactile sensing.

Bimodal Intelligent Electronic Skin Based on Proximity and Tactile Interaction for Pressure and Configuration Perception

The flexible bimodal e-skin exhibits significant promise for integration into the next iteration of human-computer interactions, owing to the integration of tactile and proximity perception. However, those challenges, such as low tactile sensitivity, complex fabrication processes, and incompatibility with bimodal interactions, have restricted the widespread adoption of bimodal e-skin. Herein, a bimodal capacitive e-skin capable of simultaneous tactile and proximity sensing has been developed. The entire process eliminates intricate fabrication techniques, employing DLP-3D printing for the electrode layers and sacrificial templating for the dielectric layers, conferring high tactile sensitivity (1.672 kPa-1) and rapid response capability (∼30 ms) to the bimodal e-skin. Moreover, exploiting the "fringing electric field" effect inherent in parallel-plate capacitors has facilitated touchless sensing, thereby enabling static distance recognition and dynamic gesture recognition of varying materials. Interestingly, an e-skin sensing array was created to identify the positions and pressure levels of various objects of different masses. Furthermore, with the aid of machine learning techniques, an artificial neural network has been established to possess intelligent object recognition capabilities, facilitating the identification, classification, and training of various object configurations. The advantages of the bimodal e-skin render it highly promising for extensive applications in the field of next-generation human-machine interaction.

Underwater Gesture Recognition Meta-Gloves for Marine Immersive Communication

Rapid advancements in immersive communications and artificial intelligence have created a pressing demand for high-performance tactile sensing gloves capable of delivering high sensitivity and a wide sensing range. Unfortunately, existing tactile sensing gloves fall short in terms of user comfort and are ill-suited for underwater applications. To address these limitations, we propose a flexible hand gesture recognition glove (GRG) that contains high-performance micropillar tactile sensors (MPTSs) inspired by the flexible tube foot of a starfish. The as-prepared flexible sensors offer a wide working range (5 Pa to 450 kPa), superfast response time (23 ms), reliable repeatability (∼10000 cycles), and a low limit of detection. Furthermore, these MPTSs are waterproof, which makes them well-suited for underwater applications. By integrating the high-performance MPTSs with a machine learning algorithm, the proposed GRG system achieves intelligent recognition of 16 hand gestures under water, which significantly extends real-time and effective communication capabilities for divers. The GRG system holds tremendous potential for a wide range of applications in the field of underwater communications.

Tactile corpuscle-inspired piezoresistive sensors based on (3-aminopropyl) triethoxysilane-enhanced CNPs/carboxylated MWCNTs/cellulosic fiber composites for textile electronics

Recently, wearable electronic products and gadgets have developed quickly with the aim of catching up to or perhaps surpassing the ability of human skin to perceive information from the external world, such as pressure and strain. In this study, by first treating the cellulosic fiber (modal textile) substrate with (3-aminopropyl) triethoxysilane (APTES) and then covering it with conductive nanocomposites, a bionic corpuscle layer is produced. The sandwich structure of tactile corpuscle-inspired bionic (TCB) piezoresistive sensors created with the layer-by-layer (LBL) technology consists of a pressure-sensitive module (a bionic corpuscle), interdigital electrodes (a bionic sensory nerve), and a PU membrane (a bionic epidermis). The synergistic mechanism of hydrogen bond and coupling agent helps to improve the adhesive properties of conductive materials, and thus improve the pressure sensitive properties. The TCB sensor possesses favorable sensitivity (1.0005 kPa-1), a wide linear sensing range (1700 kPa), and a rapid response time (40 ms). The sensor is expected to be applied in a wide range of possible applications including human movement tracking, wearable detection system, and textile electronics.

Multimodal Sensors Enabled Autonomous Soft Robotic System with Self-Adaptive Manipulation

Human hands are amazingly skilled at recognizing and handling objects of different sizes and shapes. To date, soft robots rarely demonstrate autonomy equivalent to that of humans for fine perception and dexterous operation. Here, an intelligent soft robotic system with autonomous operation and multimodal perception ability is developed by integrating capacitive sensors with triboelectric sensor. With distributed multiple sensors, our robot system can not only sense and memorize multimodal information but also enable an adaptive grasping method for robotic positioning and grasp control, during which the multimodal sensory information can be captured sensitively and fused at feature level for crossmodally recognizing objects, leading to a highly enhanced recognition capability. The proposed system, combining the performance and physical intelligence of biological systems (i.e., self-adaptive behavior and multimodal perception), will greatly advance the integration of soft actuators and robotics in many fields.

Anisotropy in magnetic materials for sensors and actuators in soft robotic systems

The field of soft intelligent robots has rapidly developed, revealing extensive potential of these robots for real-world applications. By mimicking the dexterities of organisms, robots can handle delicate objects, access remote areas, and provide valuable feedback on their interactions with different environments. For autonomous manipulation of soft robots, which exhibit nonlinear behaviors and infinite degrees of freedom in transformation, innovative control systems integrating flexible and highly compliant sensors should be developed. Accordingly, sensor-actuator feedback systems are a key strategy for precisely controlling robotic motions. The introduction of material magnetism into soft robotics offers significant advantages in the remote manipulation of robotic operations, including touch or touchless detection of dynamically changing shapes and positions resulting from the actuations of robots. Notably, the anisotropies in the magnetic nanomaterials facilitate the perception and response with highly selective, directional, and efficient ways used for both sensors and actuators. Accordingly, this review provides a comprehensive understanding of the origins of magnetic anisotropy from both intrinsic and extrinsic factors and summarizes diverse magnetic materials with enhanced anisotropy. Recent developments in the design of flexible sensors and soft actuators based on the principle of magnetic anisotropy are outlined, specifically focusing on their applicabilities in soft robotic systems. Finally, this review addresses current challenges in the integration of sensors and actuators into soft robots and offers promising solutions that will enable the advancement of intelligent soft robots capable of efficiently executing complex tasks relevant to our daily lives.

Bioinspired Flexible Capacitive Sensor for Robot Positioning in Unstructured Environments

The evolution of bionic machines into intelligent robots to adapt to real scenarios is inseparable from positioning sensors. However, traditional positioning methods such as camera arrays, ultrasound, or GPS are limited in narrow concealed spaces, harsh temperatures, or dynamic light fields, which hinder the practical application of special robots. Here, we report a flexible sensor inspired by Gnathonemus petersii that enables robots to achieve contactless and high-precision spatial localization independent of the unstructured features of the environment. Sensors are obtained from low-cost materials (carbon nanotubes and polyimides) and simple structures (fibers) and preparation processes (spin-coating). Experiments and simulations confirmed the high resolution (<1 mm) of the sensor over a large distance detection range (>150 mm) and high bandwidth (0-520 MPa) of contact force. Moreover, the sensing capability is still feasible when the sensor is bent to various curvatures and not affected under harsh conditions such as ultralow temperatures (below -78 °C), ultrahigh temperatures (over 250 °C), darkness, or brightness. We demonstrate the practical potential of the proposed sensors for a biomimetic hyper-redundant continuum robot to locate and avoid collisions in unstructured environments.

Proximity Sensing Electronic Skin: Principles, Characteristics, and Applications

The research on proximity sensing electronic skin has garnered significant attention. This electronic skin technology enables detection without physical contact and holds vast application prospects in areas such as human-robot collaboration, human-machine interfaces, and remote monitoring. Especially in the context of the spread of infectious diseases like COVID-19, there is a pressing need for non-contact detection to ensure safe and hygienic operations. This article comprehensively reviews the significant advancements in the field of proximity sensing electronic skin technology in recent years. It covers the principles, as well as single-type proximity sensors with characteristics such as a large area, multifunctionality, strain, and self-healing capabilities. Additionally, it delves into the research progress of dual-type proximity sensors. Furthermore, the article places a special emphasis on the widespread applications of flexible proximity sensors in human-robot collaboration, human-machine interfaces, and remote monitoring, highlighting their importance and potential value across various domains. Finally, the paper provides insights into future advancements in flexible proximity sensor technology.

Closely Packed Stretchable Ultrasound Array Fabricated with Surface Charge Engineering for Contactless Gesture and Materials Detection

Communication with hand gestures plays a significant role in human-computer interaction by providing an intuitive and natural way for humans to communicate with machines. Ultrasound-based devices have shown promising results in contactless hand gesture recognition without requiring physical contact. However, it is challenging to fabricate a densely packed wearable ultrasound array. Here, a stretchable ultrasound array is demonstrated with closely packed transducer elements fabricated using surface charge engineering between pre-charged 1-3 Lead Zirconate Titanate (PZT) composite and thin polyimide film without using a microscope. The array exhibits excellent ultrasound properties with a wide bandwidth (≈57.1%) and high electromechanical coefficient (≈0.75). The ultrasound array can decipher gestures up to 10 cm in distance by using a contactless triboelectric module and identify materials from the time constant of the exponentially decaying impedance based on their triboelectric properties by utilizing the electrostatic induction phase. The newly proposed metric of the areal-time constant is material-specific and decreases monotonically from a highly positive human body (1.13 m2 s) to negatively charged polydimethylsiloxane (PDMS) (0.02 m2 s) in the triboelectric series. The capability of the closely packed ultrasound array to detect material along with hand gesture interpretation provides an additional dimension in the next-generation human-robot interaction.

Mechatronic automatic control system of electropneumatic manipulator

Mechatronic systems of electropneumatic automation are one of the main classes of industrial automation systems. A laboratory stand for the study of the mechatronic system of automatic control of the pneumatic manipulator and a computer model for preliminary experiments on the adjustment of the automatic control system were developed. Manual and software control modes are provided for research of indicators of safety and quality of management in both modes. To implement the software control mode, a microcontroller part of the laboratory stand based on ADuC841 was developed, with the help of which it is possible to simulate a part of a certain technological process, to detect and eliminate faults in the automatic control system. A study of automatic control systems using a traditional relay-contactor control system, based on GrafCet technology and using a virtual controller. The combination of computer modeling of technological processes and physical modeling of executive mechanisms is a kind of digital double that displays its state, parameters and behavior in real time. The use of a laboratory stand in combination with an adequate simulation model reduces the complexity of developing control systems for practical applications, and also contributes to the formation of students' creative component, ability to analyze the results, and make decisions in unusual situations, which will increase their theoretical and practical training. The study of mechatronic systems of pneumatic manipulators will allow to increase their efficiency and productivity, to optimize their speed and accuracy for various applications in production. The interaction of mechatronic systems of pneumatic manipulators with other technologies, such as machine learning, artificial intelligence, IoT is the basis for creating more integrated and intelligent systems.

Bioinspired ion channel receptor based on hygroelectricity for precontact sensing of living organism

Tactile sensors play an important role in human-machine interaction (HMI). Compared to contact tactile sensing, which leaves physical hardware vulnerable to wear and tear, proximity sensing is better at reacting to remote events before physical contact. The apteronotus albifrons possess ion channel receptors for remote surroundings perception. Inspired by the relevant ion channel structure and self-powered operation mode, we designed a new proximity sensor with ion rectification characteristics and self-powered capability. This bio-inspired ion channel receptor exploits the hygroelectric effect to convert the humidity information into a series of current signals when the living organism approaches, and it is insensitive to non-aquatic non-organisms. The sensor offers high sensitivity (2.3 mm-1), a suitable range (0-10 mm) for close object detection, fast response (0.3 s), and fast recovery (2.5 s). The unique combination of bio-sensitivity, non-contact detection characteristics, and humidity-based power generation capabilities enriches the functionality of future HMI electronics. As a proof of concept, the sensor has been successfully applied in different scenarios such as human health management, early warning systems, non-contact switches to prevent virus transmission, object recognition, and finger trajectory detection.

Covalently-Bonded Laminar Assembly of Van der Waals Semiconductors with Polymers: Toward High-Performance Flexible Devices

Van der Waals semiconductors (vdWS) offer superior mechanical and electrical properties and are promising for flexible microelectronics when combined with polymer substrates. However, the self-passivated vdWS surfaces and their weak adhesion to polymers tend to cause interfacial sliding and wrinkling, and thus, are still challenging the reliability of vdWS-based flexible devices. Here, an effective covalent vdWS-polymer lamination method with high stretch tolerance and excellent electronic performance is reported. Using molybdenum disulfide (MoS2 )and polydimethylsiloxane (PDMS) as a case study, gold-chalcogen bonding and mercapto silane bridges are leveraged. The resulting composite structures exhibit more uniform and stronger interfacial adhesion. This enhanced coupling also enables the observation of a theoretically predicted tension-induced band structure transition in MoS2 . Moreover, no obvious degradation in the devices' structural and electrical properties is identified after numerous mechanical cycle tests. This high-quality lamination enhances the reliability of vdWS-based flexible microelectronics, accelerating their practical applications in biomedical research and consumer electronics.

Dielectric-Enhanced, High-Sensitivity, Wide-Bandwidth, and Moisture-Resistant Noncontact Triboelectric Sensor for Vibration Signal Acquisition

Noncontact triboelectric sensors (TESs) have the potential to enhance self-powered sensing performance by eliminating the need for physical contact. This study demonstrates a strategy to construct noncontact TES that enables self-powered sensing and vibration signal acquisition with high sensitivity and wide bandwidth. The incorporation of carbon nanotubes into nitrocellulose (CNTs/NC) endows the tribopositive layer with larger inner micro/nanocapacitances, consequently augmenting the charge storage capacity. As a result, the contactless sensing performance of CNTs/NC-based TES (CNTs/NC-TES) was enhanced by 146%. Correspondingly, the related theory and working mechanism of noncontact sensing were demonstrated. Furthermore, the CNTs/NC-TES exhibits optimal distance response sensitivity of 57.10 V mm-1, a wide-bandwidth response from 0.1 to 4000 Hz, and relative humidity (RH) stability. This contactless CNTs/NC-TES has the potential for high sensitivity and wide frequency vibration monitoring in a high-RH environment.

Two-Stage Micropyramids Enhanced Flexible Piezoresistive Sensor for Health Monitoring and Human-Computer Interaction

High-performance flexible piezoresistive sensors are becoming increasingly essential in various novel applications such as health monitoring, soft robotics, and human-computer interaction. The evolution of the interfacial contact morphology determines the sensing properties of piezoresistive devices. The introduction of microstructures enriches the interfacial contact morphology and effectively boosts the sensitivity; however, the limited compressibility of conventional microstructures leads to rapid saturation of the sensitivity in the low-pressure range, which hinders their application. Herein, we present a flexible piezoresistive sensor featuring a two-stage micropyramid array structure, which effectively enhances the sensitivity while widening the sensing range. Owing to the synergistic enhancement effect resulting from the sequential contact of micropyramids of various heights, the devices demonstrate remarkable performance, including boosting sensitivity (30.8 kPa-1) over a wide sensing range (up to 200 kPa), a fast response/recovery time (75/50 ms), and an ultralong durability of 15,000 loading-unloading cycles. As a proof of concept, the sensor is applied to detect human physiological and motion signals, further demonstrating a real-time spatial pressure distribution sensing system and a game control system, showing great potential for applications in health monitoring and human-computer interaction.

Viscoelastic blood coagulation testing system enabled by a non-contact triboelectric angle sensor

Thromboelastography (TEG) remains a convenient and effective viscoelastic blood coagulation testing device for guiding blood component transfusion and assessing the risk of thrombosis. Here, a TEG enabled by a non-contact triboelectric angle sensor (NTAS) with a small size (∼7 cm3) is developed for assessing the blood coagulation system. With the assistance of a superelastic torsion wire structure, the NTAS-TEG realizes the detection of blood viscoelasticity. Benefiting from a grating and convex design, the NTAS holds a collection of compelling features, including accurate detection of rotation angles from -2.5° to 2.5°, high linearity (R 2 = 0.999), and a resolution of 0.01°. Besides, the NTAS exhibits merits of low cost and simplified fabrication. Based on the NTAS-TEG, a viscoelastic blood coagulation detection and analysis system is successfully constructed, which can provide a graph and parameters associated with clot initiation, formation, and stability for clinicians by using 0.36 mL of whole blood. The system not only validates the feasibility of the triboelectric coagulation testing sensor, but also further expands the application of triboelectric sensors in healthcare.

Bioinspired handheld time-share driven robot with expandable DoFs

Handheld robots offer accessible solutions with a short learning curve to enhance operator capabilities. However, their controllable degree-of-freedoms are limited due to scarce space for actuators. Inspired by muscle movements stimulated by nerves, we report a handheld time-share driven robot. It comprises several motion modules, all powered by a single motor. Shape memory alloy (SMA) wires, acting as "nerves", connect to motion modules, enabling the selection of the activated module. The robot contains a 202-gram motor base and a 0.8 cm diameter manipulator comprised of sequentially linked bending modules (BM). The manipulator can be tailored in length and integrated with various instruments in situ, facilitating non-invasive access and high-dexterous operation at remote surgical sites. The applicability was demonstrated in clinical scenarios, where a surgeon held the robot to conduct transluminal experiments on a human stomach model and an ex vivo porcine stomach. The time-share driven mechanism offers a pragmatic approach to build a multi-degree-of-freedom robot for broader applications.

Perceived Safety Assessment of Interactive Motions in Human-Soft Robot Interaction

Soft robots, especially soft robotic hands, possess prominent potential for applications in close proximity and direct contact interaction with humans due to their softness and compliant nature. The safety perception of users during interactions with soft robots plays a crucial role in influencing trust, adaptability, and overall interaction outcomes in human-robot interaction (HRI). Although soft robots have been claimed to be safe for over a decade, research addressing the perceived safety of soft robots still needs to be undertaken. The current safety guidelines for rigid robots in HRI are unsuitable for soft robots. In this paper, we highlight the distinctive safety issues associated with soft robots and propose a framework for evaluating the perceived safety in human-soft robot interaction (HSRI). User experiments were conducted, employing a combination of quantitative and qualitative methods, to assess the perceived safety of 15 interactive motions executed by a soft humanoid robotic hand. We analyzed the characteristics of safe interactive motions, the primary factors influencing user safety assessments, and the impact of motion semantic clarity, user technical acceptance, and risk tolerance level on safety perception. Based on the analyzed characteristics, we summarize vital insights to provide valuable guidelines for designing safe, interactive motions in HSRI. The current results may pave the way for developing future soft machines that can safely interact with humans and their surroundings.