Dynamic tactility by position-encoded spike spectrum

Three-Dimensionally Architected Tactile Electronic Skins

Tactile electronic skins (e-skins) are flexible electronic devices that aim to replicate tactile sensing capabilities of the human skin, while possessing skin-like geometric features and materials properties. Since the human skin is composed of complex 3D constructions, where the various types of mechanoreceptors are distributed in a spatial layout, an important trend of tactile e-skin development involves introduction of 3D device architectures that can replicate certain structural features of human skins. The resulting 3D architected e-skins have demonstrated advantages in the detection of shear forces and the decoupled perception of multiple mechanical stimuli, which are of pivotal importance in many application scenarios. In this perspective, we summarize the main biological prototypes of existing 3D architected e-skins, and focus on the key 3D architectures related to tactile sensing capabilities. Then we highlight the enhanced tactile perception of 3D architected e-skins in terms of the super-resolution tactile sensing and predictions of diverse physical properties and surface features of an object, which allow for a broad spectrum of practical applications, such as object recognition, human-machine interactions, dexterous manipulation, and health monitoring. Finally, we discuss scientific challenges and opportunities for future developments of 3D architected tactile e-skins.

A flexible pressure sensor array for self-powered identity authentication during typing

The keyboard, a staple tool for information entry and human-machine interaction, faces demands for enhanced information security due to evolving internet technologies. This study introduces a self-powered flexible intelligent keyboard (SFIK) that harnesses the giant magnetoelastic effect to convert the mechanical pressure from key presses into electrical signals. The sensor boasts a wide sensing range (35 to 600 kPa) and a rapid response time (∼300 ms), allowing it to record and recognize individual keystroke dynamics. Integrated with machine learning, this keyboard enables identity authentication through both fixed- and dynamic-text inputs. It accurately authenticates fixed passwords of eight characters with a 95.3% success rate and dynamic text from 14 sets of double keys with 100% accuracy. Given its capabilities, the SFIK offers promising applications in artificial intelligence, network security, and access control for computers and networks.

Self-rerouting sensor network for electronic skin resilient to severe damage

We propose a network architecture for electronic skin with an extensive sensor array-crucial for enabling robots to perceive their environment and interact effectively with humans. Fault tolerance is essential for electronic skins on robot exteriors. Although self-healing electronic skins targeting minor damages are studied using material-based approaches, substantial damages such as severe cuts necessitate re-establishing communication pathways, traditionally performed with high-functionality microprocessor sensor nodes. However, this method is costly, increases latency, and boosts power usage, limiting scalability for large, nuanced sensation-mimicking sensor arrays. Our proposed system features sensor nodes consisting of only a few dozen logic circuits, enabling them to autonomously reconstruct reading pathways. These nodes can adapt to topological changes within the sensor network caused by disconnections and reconnections. Testing confirms rapid reading times of only a few microseconds and power consumption of 1.88 μW/node at a 1 kHz sampling rate. This advancement significantly boosts robots' collaborative potential with humans.

Bioinspired Magnetized String with Tension-Dependent Eigenfrequencies for Wearable Human-Machine Interactions

Flexible and wearable devices have exhibited potential for applications in the fields of human-machine interactions (HMIs) and Internet of Things. However, challenges remain in the improvement of the communication storage capacity with a simplified architecture. Inspired by tension regulation in natural tendons, a single-channel wearable HMI strategy is proposed using the eigenfrequency of magnetized strings as a sensing solution. Based on electromagnetic induction, mechanical vibration of the magnetized string can electrically induce periodical damping signals in the coil that are associated with the intrinsic eigenfrequency property of the string. Using a theoretical vibration model, nonoverlapping eigenfrequencies are precisely customized by designing the dimension/modulus or tension status of the string to broaden the eigenfrequency library. By integrating strings with different eigenfrequencies, multiple commands can be realized with a single communication channel. Moreover, identifiable commands can be flexibly tuned with only one magnetized string by customizing the tensile length (string tension) for eigenfrequency regulation. Demonstrations such as tactile addressing, authentication systems, and robotic control indicate the potential of the interface for multifunctional HMI applications. We expect that this strategy will provide a valuable reference for the future design of wearable HMI interfaces with high storage capacity and controllability in an accessible architecture.

Toward an AI Era: Advances in Electronic Skins

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

Three-dimensional micro strain gauges as flexible, modular tactile sensors for versatile integration with micro- and macroelectronics

Flexible tactile sensors play important roles in many areas, like human-machine interface, robotic manipulation, and biomedicine. However, their flexible form factor poses challenges in their integration with wafer-based devices, commercial chips, or circuit boards. Here, we introduce manufacturing approaches, device designs, integration strategies, and biomedical applications of a set of flexible, modular tactile sensors, which overcome the above challenges and achieve cooperation with commercial electronics. The sensors exploit lithographically defined thin wires of metal or alloy as the sensing elements. Arranging these elements across three-dimensional space enables accurate, hysteresis-free, and decoupled measurements of temperature, normal force, and shear force. Assembly of such sensors on flexible printed circuit boards together with commercial electronics forms various flexible electronic systems with capabilities in wireless measurements at the skin interface, continuous monitoring of biomechanical signals, and spatial mapping of tactile information. The flexible, modular tactile sensors expand the portfolio of functional components in both microelectronics and macroelectronics.

Artificial organic afferent nerves enable closed-loop tactile feedback for intelligent robot

The emulation of tactile sensory nerves to achieve advanced sensory functions in robotics with artificial intelligence is of great interest. However, such devices remain bulky and lack reliable competence to functionalize further synaptic devices with proprioceptive feedback. Here, we report an artificial organic afferent nerve with low operating bias (-0.6 V) achieved by integrating a pressure-activated organic electrochemical synaptic transistor and artificial mechanoreceptors. The dendritic integration function for neurorobotics is achieved to perceive directional movement of object, further reducing the control complexity by exploiting the distributed and parallel networks. An intelligent robot assembled with artificial afferent nerve, coupled with a closed-loop feedback program is demonstrated to rapidly implement slip recognition and prevention actions upon occurrence of object slippage. The spatiotemporal features of tactile patterns are well differentiated with a high recognition accuracy after processing spike-encoded signals with deep learning model. This work represents a breakthrough in mimicking synaptic behaviors, which is essential for next-generation intelligent neurorobotics and low-power biomimetic electronics.

In-Sensor Tactile Fusion and Logic for Accurate Intention Recognition

Touch control intention recognition is an important direction for the future development of human-machine interactions (HMIs). However, the implementation of parallel-sensing functional modules generally requires a combination of different logical blocks and control circuits, which results in regional redundancy, redundant data, and low efficiency. Here, a location-and-pressure intelligent tactile sensor (LPI tactile sensor) unprecedentedly combined with sensing, computing, and logic is proposed, enabling efficient and ultrahigh-resolution action-intention interaction. The LPI tactile sensor eliminates the need for data transfer among the functional units through the core integration design of the layered structure. It actuates in-sensor perception through feature transmission, fusion, and differentiation, thereby revolutionizing the traditional von Neumann architecture. While greatly simplifying the data dimensionality, the LPI tactile sensor achieves outstanding resolution sensing in both location (<400 µm) and pressure (75 Pa). Synchronous feature fusion and decoding support the high-fidelity recognition of action and combinatorial logic intentions. Benefiting from location and pressure synergy, the LPI tactile sensor demonstrates robust privacy as an encrypted password device and interaction intelligence through pressure enhancement. It can recognize continuous touch actions in real time, map real intentions to target events, and promote accurate and efficient intention-driven HMIs.

A multimodal magnetoelastic artificial skin for underwater haptic sensing

Future exploitation of marine resources in a sustainable and eco-friendly way requires autonomous underwater robotics with human-like perception. However, the development of such intelligent robots is now impeded by the lack of adequate underwater haptic sensing technology. Inspired by the populational coding strategy of the human tactile system, we harness the giant magnetoelasticity in soft polymer systems as an innovative platform technology to construct a multimodal underwater robotic skin for marine object recognition with intrinsic waterproofness and a simple configuration. The bioinspired magnetoelastic artificial skin enables multiplexed tactile modality in each single taxel and obtains an impressive classification rate of 95% in identifying seven types of marine creatures and marine litter. By introducing another degree of freedom in underwater haptic sensing, this work represents a milestone toward sustainable marine resource exploitation.

Purposive Design of Stretchable Composite Electrodes for Strain-Negative, Strain-Neutral, and Strain-Positive Ionic Sensors

Soft ionic sensors have emerged as a promising device form to accommodate various future electronic applications. One of the hurdles in ionic sensors is that the sensing signals by mechanical deformation and other stimuli are mixed up. Although the performance of the ionic sensors is highly dependent on the structure of electrodes, systematic investigation of purposive electrode design has been rarely explored. This study proposes a simple strategy for designing stretchable composite electrodes which make the ionic sensor strain-negative, strain-neutral, and strain-positive. This study reveals that such strain-responses can be obtained by adjusting the surface coverage of the electrically-effective conductive fillers. On the basis of the concept, deposition of a Au film on an elastomer composite and crack formation of the Au film are presented for the practical fabrication of a highly reproducible strain-neutral ionic sensor. A completely strain-independent temperature sensor is demonstrated by using the Au crack-based ionic sensor. In addition, this study demonstrates a two-terminal shear sensor capable of recognizing shear directions by combining the strain-positive and strain-negative electrodes.

Modulus difference-induced embedding strategy to construct iontronic pressure sensor with high sensitivity and wide linear response range

Sensitivity and linearity are two crucial indices to assess the sensing capability of pressure sensors; unfortunately, the two mutually exclusive parameters usually result in limited applications. Although a series of microengineering strategies including micropatterned, multilayered, and porous approach have been provided in detail, the conflict between the two parameters still continues. Here, we present an efficient strategy to resolve this contradiction via modulus difference-induced embedding deformation. Both the microscopic observation and finite element simulation results confirm the embedding deformation behavior ascribed to the elastic modulus difference between soft electrode and rigid microstructures. The iontronic pressure sensor with high sensitivity (35 kPa-1) and wide linear response range (0-250 kPa) is further fabricated and demonstrates the potential applications in monitoring of high-fidelity pulse waveforms and human motion. This work provides an alternative strategy to guide targeted design of all-around and comprehensive pressure sensor.

Dynamic Metal-Ligand Coordination-Assisted Ionogels for Deformable Alternating Current Electroluminescent Devices

Overcoming the trade-off between the mechanical robustness and conductivity of ionic conductors is a crucial challenge for deformable ionotronics. In this work, we propose a simple but effective gelation strategy for selectively improving the mechanical robustness of ionogels without compromising their ionic conductivity. To achieve this, we introduce dynamic metal-ligand coordination chemistry into the ionic liquid (IL)-insoluble domains of a physically crosslinked ionogel network structure. As a result, the overall mechanical property is remarkably improved with the aid of additional chemical crosslinking. This strategy does not require any additional heat/light (UV) treatments to induce chemical crosslinking. The homogeneous physically/chemically dual crosslinked ionogel films can be readily obtained by simply casting a solution containing Ni²⁺ sources, copolymer gelators, and ILs. The effects of adjusting fundamental parameters on the ionogel properties are investigated systematically. The optimized mechanically robust and highly conductive ionogels are successfully employed as deformable ionic electrodes in alternating-current electroluminescent displays, indicating their high practicality. Overall, these results validate that exploiting metal-ligand coordination dynamic bonding is an extremely straightforward strategy for selectively improving the mechanical characteristics of conductive ionogels, which are promising platforms for deformable ionotronics.

Technology Roadmap for Flexible Sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Water-Modulated Biomimetic Hyper-Attribute-Gel Electronic Skin for Robotics and Skin-Attachable Wearables

Electronic skin (e-skin), mimicking the physical-chemical and sensory properties of human skin, is promising to be applied as robotic skins and skin-attachable wearables with multisensory functionalities. To date, most e-skins are dedicated to sensory function development to mimic human skins in one or several aspects, yet advanced e-skin covering all the hyper-attributes (including both the sensory and physical-chemical properties) of human skins is seldom reported. Herein, a water-modulated biomimetic hyper-attribute-gel (Hygel) e-skin with reversible gel-solid transition is proposed, which exhibits all the desired skin-like physical-chemical properties (stretchability, self-healing, biocompatibility, biodegradability, weak acidity, antibacterial activities, flame retardance, and temperature adaptivity), sensory properties (pressure, temperature, humidity, strain, and contact), function reconfigurability, and evolvability. Then the Hygel e-skin is applied as an on-robot e-skin and skin-attached wearable to demonstrate its highly skin-like attributes in capturing multiple sensory information, reconfiguring desired functions, and excellent skin compatibility for real-time gesture recognition via deep learning. This Hygel e-skin may find more applications in advanced robotics and even skin-replaceable artificial skin.

BaroTac: Barometric Three-Axis Tactile Sensor with Slip Detection Capability

Tactile sensors for robotic applications enhance the performance of robotic end-effectors as they ca n provide tactile information to operate various tasks. In particular, tactile sensors can measure multi-axial force and detect slip can aid the end-effectors in grasping diverse objects in an unstructured environment. We propose BaroTac, which measures three-axial forces and detects slip with a barometric pressure sensor chip (BPSC) for robotic applications. A BPSC is an off-the-shelf commercial sensor that is inexpensive, easy to customize, robust, and simple to use. While a single BPSC-based tactile sensor can measure pressure, an array of BPSC-based tactile sensors can measure multi-axial force through the reactivity of each sensor and detect slip by observing high frequency due to slip vibration. We first experiment with defining the fundamental characteristics of a single-cell BPSC-based sensor to set the design parameters of our proposed sensor. Thereafter, we suggest the sensing method of BaroTac: calibration matrix for three-axis force measurement and discrete wavelet transform (DWT) for slip detection. Subsequently, we validate the three-axis force measuring ability and slip detectability of the fabricated multi-cell BPSC-based tactile sensor. The sensor measures three-axis force with low error (0.14, 0.18, and 0.3% in the X-, Y- and Z-axis, respectively) and discriminates slip in the high-frequency range (75-150 Hz). We finally show the practical applicability of BaroTac by installing them on the commercial robotic gripper and controlling the gripper to grasp common objects based on our sensor feedback.

Multimodal Sensors with Decoupled Sensing Mechanisms

Highly sensitive and multimodal sensors have recently emerged for a wide range of applications, including epidermal electronics, robotics, health-monitoring devices and human-machine interfaces. However, cross-sensitivity prevents accurate measurements of the target input signals when a multiple of them are simultaneously present. Therefore, the selection of the multifunctional materials and the design of the sensor structures play a significant role in multimodal sensors with decoupled sensing mechanisms. Hence, this review article introduces varying methods to decouple different input signals for realizing truly multimodal sensors. Early efforts explore different outputs to distinguish the corresponding input signals applied to the sensor in sequence. Next, this study discusses the methods for the suppression of the interference, signal correction, and various decoupling strategies based on different outputs to simultaneously detect multiple inputs. The recent insights into the materials' properties, structure effects, and sensing mechanisms in recognition of different input signals are highlighted. The presence of the various decoupling methods also helps avoid the use of complicated signal processing steps and allows multimodal sensors with high accuracy for applications in bioelectronics, robotics, and human-machine interfaces. Finally, current challenges and potential opportunities are discussed in order to motivate future technological breakthroughs.

Binary Co-Gelator Strategy: Toward Highly Deformable Ionic Conductors for Wearable Ionoskins

Stretchable ionic conductors have been actively developed due to the increasing demand for wearable electrochemical platforms. Herein, we propose a convenient and effective strategy for tailoring the mechanical deformability of ionic conductors. The mixing of poly(methyl methacrylate) (PMMA, polymer gelator) and 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([BMI][TFSI], ionic liquid) produces mechanically stiff ionic conductors. To reduce the chain entanglement of polymer gelators and induce effective dissipation of applied stresses, flexible poly(butyl acrylate) (PBA) with a low glass-transition temperature is additionally doped into the ionic conductor. An extremely stretchable (∼1500%) homogeneous ternary ionic conductor is obtained without a notable change in electrochemical characteristics, unless the content of PBA exceeds the macrophase separation limit of 3 wt %. In addition, the mechanical elasticity (1.8 × 10⁵ Pa) and durability (e.g., recovery ratio of ∼86.3% after 1000 stretching/releasing cycles) of the conductor further support its suitability as a strain sensory platform. In contrast to conventional ionoskins that have to fit the area of target body parts, even a small piece of the ternary ionic conductor successfully monitors human motion over large areas by taking advantage of its superior deformability.