Multimodal Sensors with Decoupled Sensing Mechanisms

Shape-morphing bioelectronic devices

Shape-morphing bioelectronic devices, which can actively transform their geometric configurations in response to external stimuli (e.g., light, heat, electricity, and magnetic fields), have enabled many unique applications in different areas, ranging from human-machine interfaces to biomedical applications. These devices can not only realize in vivo deformations to execute specific tasks, form conformal contacts with target organs for real-time monitoring, and dynamically reshape their structures to adjust functional properties, but also assist users in daily activities through physical interactions. In this review, we provide a comprehensive overview of recent advances in shape-morphing bioelectronic devices, covering their fundamental working principles, representative deformation modes, and advanced manufacturing methodologies. Then, a broad range of practical applications of shape-morphing bioelectronics are summarized, including electromagnetic devices, optoelectronic devices, biological devices, biomedical devices, and haptic interfaces. Finally, we discuss key challenges and emerging opportunities in this rapidly evolving field, providing insights into future research directions and potential breakthroughs.

Deep Learning-Assisted 3D Pressure Sensors for Control of Unmanned Aerial Vehicles

Accurately and reliably detecting and recognizing human body movements in real time, relaying appropriate commands to the machine, have substantial implications for virtual reality, remote control, and robotics applications. Nonetheless, most contemporary wearable analysis and control systems attain action recognition by setting sensor thresholds. In routine usage, the stringent trigger conditions facilitate inadvertent contact, resulting in a poorer user experience. Here, we have created a wearable intelligent gesture recognition control system utilizing a multilayer microstructure composite thin film piezoresistive sensing array and deep learning techniques. The system exhibits ultrahigh sensitivity (ranging from 0-6 kPa to 412.2 kPa-1) and rapid response times (loading at 40 ms, recovery at 30 ms). The detected gestures are classified and recognized via a convolutional neural network, achieving a recognition accuracy of 97.5%. Ultimately, the altitude control of an unmanned aerial vehicle is accomplished through wireless signal transmission and reception. To achieve the visualization of the complete gesture-controlled flight process, we developed an intuitive user interface for the real-time display of flight altitude and video surveillance. The implementation of this recognition system introduces a novel control mechanism for human-machine interaction, expands the applications of robotic technology, and offers innovative concepts and practical pathways for virtual reality.

Smart Dust for Chemical Mapping

This review article explores the transformative potential of smart dust systems by examining how existing chemical sensing technologies can be adapted and advanced to realize their full capabilities. Smart dust, characterized by submillimeter-scale autonomous sensing platforms, offers unparalleled opportunities for real-time, spatiotemporal chemical mapping across diverse environments. This article introduces the technological advancements underpinning these systems, critically evaluates current limitations, and outlines new avenues for development. Key challenges, including multi-compound detection, system control, environmental impact, and cost, are discussed alongside potential solutions. By leveraging innovations in miniaturization, wireless communication, AI-driven data analysis, and sustainable materials, this review highlights the promise of smart dust to address critical challenges in environmental monitoring, healthcare, agriculture, and defense sectors. Through this lens, the article provides a strategic roadmap for advancing smart dust from concept to practical application, emphasizing its role in transforming the understanding and management of complex chemical systems.

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.

Recent Advancements in Rubber Composites for Physical Activity Monitoring Sensors: A Critical Review

This review provides the latest insight (2020 to 2025) for composite-based physical activity monitoring sensors. These composite materials are based on carbon-reinforced silicone rubber. These composites feature the use of composite materials, thereby allowing the creation of new generation non-invasive sensors for monitoring of sports activity. These physical sports activities include running, cycling, or swimming. The review describes a brief overview of carbon nanomaterials and silicone rubber-based composites. Then, the prospects of such sensors in terms of mechanical and electrical properties are described. Here, a special focus on electrical properties like resistance change, response time, and gauge factor are reported. Finally, the review reports a brief overview of the industrial uses of these sensors. Some aspects are sports activities like boxing or physical activities like walking, squatting, or running. Lastly, the main aspect of fracture toughness for obtaining high sensor durability is reviewed. Finally, the key challenges in material stability, scalability, and integration of multifunctional aspects of these composite sensors are addressed. Moreover, the future research prospects are described for these composite-based sensors, along with their advantages and limitations.

A lamb freshness detection model using a flexible optoelectronic in-situ sensing system and multi-input multi-label causal ensemble learning

Efficient, non-destructive and real-time meat freshness assessment has always been a hot research topic. This paper presents a novel approach for detecting lamb meat freshness using a flexible optoelectronic sensing system combined with an integrated learning model. We developed a flexible impedance sensing system and a flexible optical sensing system through laser direct writing and transfer technology. Freshness of lamb samples was evaluated under various storage conditions (0 °C, 4 °C, and 8 °C). Our results demonstrated that the system offers notable portability, stability, and accuracy compared to traditional methods. Statistical analysis revealed a moderately strong correlation (r > 0.86) among physicochemical properties, impedance measurements, and spectral data of lamb meat. The Granger causality test indicated a causal relationship between impedance and spectral data (p < 0.05). Data were analyzed using our 1DCNN-BiLSTM-ATT model for freshness grading, achieving an accuracy of 94.57 %, significantly outperforming traditional algorithms. This paper provides an innovative solution for the efficient and accurate prediction of lamb freshness.

A crosslinked eutectogel for ultrasensitive pressure and temperature monitoring from nostril airflow

Accurate detection of nostril airflow is vital for real-time respiratory monitoring. However, the developed methods only rely on single stimulus sensing for nostril airflow, which is extremely susceptible to interference in the complex environment, and severely affects the accuracy of detection results. Here, a multimodal integrated eutectogel sensor is explored to simultaneously sense the pressure and temperature stimuli of nostril airflow, by independently outputting capacitance and resistance, respectively, without cross-coupling. The completely physical crosslinking and the synergistic interaction of hydroxyapatite and tannic acid within the network endow this eutectogel with extremely low modulus, remarkable self-healing efficiency, robust adhesion, good environmental stability, and bio-compatibility. A multimodal sensor is developed by integrating this synthetic eutectogel with circuit design, which exhibits superior pressure sensitivity compared to other reported gel-based sensors. As a proof of concept, this sensor is further explored to diagnose the traditional respiratory disease of obstructive sleep apnea syndrome by simultaneously detecting five kinds of stimuli in the sleeping process, greatly improving the accuracy and reliability of the detection results. This work provides a highly effective strategy for achieving ultrasensitive respiratory monitoring and forecasting respiratory diseases.

Natural polysaccharides-based smart sensors for health monitoring, diagnosis and rehabilitation: A review

With the rapid growth of multi-level health needs, precise and real-time health sensing systems have become increasingly pivotal in personal health management and disease prevention. Natural polysaccharides demonstrate immense potential in healthcare sensors by leveraging their superior biocompatibility, biodegradability, environmental sustainability, as well as diverse structural designs and surface functionalities. This review begins by introducing a variety of natural polysaccharides, including cellulose, alginates, chitosan, hyaluronic acid, and starch, and analyzing their structural and functional distinctions, which offer extensive possibilities for sensor design and construction. Further, we summarize several principal sensing mechanisms, such as piezoresistivity, piezoelectricity, capacitance, triboelectricity, and hygroelectricity, which provide a theoretical and technological foundation for developing high-performance healthcare sensing devices. Additionally, the review discusses the most recent applications of natural polysaccharide-based sensors in diverse healthcare contexts, including human body motion tracking, respiratory and heartbeat monitoring, electrophysiological signal recording, body temperature variation detection, and biomarker analysis. Finally, prospective development directions are proposed, such as the integration of artificial intelligence for real-time data analysis, the design of multifunctional devices that combine sensing with therapeutic functionalities, and advancements in remote monitoring and smart wearable technologies. This review aims to provide valuable insights into the development of next-generation healthcare sensors and propose novel research directions for personalized medicine and remote health management.

Facile Design of Highly Stretchable and Conductive Crumpled Graphene/NiS2 Films for Multifunctional Applications

The cost-effective and scalable synthesis and patterning of soft nanomaterial composites with improved electrical conductivity and mechanical stretchability remains challenging in wearable devices. This work reports a scalable, low-cost fabrication approach to directly create and pattern crumpled porous graphene/NiS2 nanocomposites with high mechanical stretchability and electrical conductivity through laser irradiation combined with electrodeposition and a pre-strain strategy. With modulated mechanical stretchability and electrical conductivity, the crumpled graphene/NiS2 nanocomposite can be readily patterned into target geometries for application in a standalone stretchable sensing platform. By leveraging the electrical energy harvested from the kinetic motion from wearable triboelectric nanogenerator (TENG) and stored in micro-supercapacitor arrays (MSCAs) to drive biophysical sensors, the system is demonstrated to monitor human motions, body temperature, and toxic gas in the exposed environment. The material selections, design strategies, and fabrication approaches from this study provide functional nanomaterial composites with tunable properties for future high-performance bio-integrated electronics.

Layer-by-Layer Self-Assembled Honeycomb Structure Flexible Pressure Sensor Array for Gait Analysis and Motion Posture Recognition with the Assistance of the ResNet-50 Neural Network

With the rapid emergence of flexible electronics, flexible pressure sensors are of importance in various fields. In this study, a dopamine-modified melamine sponge (MS) was used to prepare a honeycomb structure of carbon black (CB)/MXene-silicone rubber (SR)@MS flexible pressure sensor (CMSM) through layer-by-layer self-assembly technology. Using SR as a binder to construct the honeycomb structure not only improves the mechanical properties of the sensor but also provides more attachment sites for CB/MXene, enhancing the stability of the conductive network. The honeycomb structure CMSM flexible pressure sensor exhibits high sensitivity (7.44 kPa-1), a wide detection range (0-240 kPa), short response/recovery times (150 ms/180 ms), and exhibits excellent stability. In addition, a flexible smart insole has been developed based on a 6-unit CMSM sensor array, achieving plantar pressure detection. By combination of the ResNet-50 neural network algorithm with plantar pressure data under different postures, the recognition of 16 types of human motion postures has been achieved, with an accuracy rate of 90.63%. This study proposes a flexible sponge pressure sensor with excellent mechanical performance and sensing capabilities, providing new ideas and references for the design of flexible wearable sensor devices.

Smart Vascular Grafts with Integrated Flow Biosensors for Hemodynamic Real-Time Monitoring and Vascular Healthcare

Real-time monitoring of hemodynamics is crucial for diagnosing disorders within implanted vascular grafts and facilitating timely treatment. Integrating vascular grafts with advanced flexible electronics offers a promising approach to developing smart vascular grafts (SVGs) capable of continuous hemodynamic monitoring. However, most existing SVG devices encounter significant challenges in practical applications, particularly regarding biomechanical compatibility and the effective evaluation of vascular status. Here, we present a state-of-the-art SVG device seamlessly integrated with flow biosensors constructed by encapsulating patterned porous graphene within biocompatible polymers. The innovative use of porous graphene imparts the SVG with exceptional mechanical sensing performance, featuring a low strain detection limit of 0.0034% and dynamic stability exceeding 32,400 cycles, thus enabling precise hemodynamic perception. This high sensitivity allows the SVG to accurately diagnose vascular disorders, such as blockage degree and position, by collecting hemodynamic data from an artificial artery model. In vitro thrombi (blood clot) diagnostics, treatment simulation experiments, and in vivo tests using a rabbit model strongly validate the SVG's outstanding and reliable performance in vascular healthcare. We have also developed a stand-alone and wireless system, demonstrating its capability for remote monitoring and managing vascular health. Our pioneering SVG system showcases great potential in vascular healthcare for precise hemodynamic monitoring of disorders, timely diagnostics, and even drug screening.

Toward Stretchable Flexible Integrated Sensor Systems

Skin-like flexible sensors hold great potential as the next generation of intelligent electronic devices owing to their broad applications in environmental monitoring, human-machine interfaces, the Internet of Things, and artificial intelligence. Flexible electronics inspired by human skin play a vital role in continuous and real-time health monitoring. This review summarizes recent progress in skin-mountable electronics developed by designing flexible electrodes and substrates into different structures, including serpentine, microcrack, wrinkle, and kirigami. Furthermore, this review briefly discusses advances in wearable integrated sensor systems that mimic the flexibility of human skin, as well as multisensing functions. In the future, innovations in stretchable integrated sensor systems will be crucial to develop next-generation intelligent skin-based sensors for practical applications such as medical diagnosis, treatment, and environment monitoring.

Anisotropic hydrogel sensors with muscle-like structures based on high-absorbent alginate fibers

Hydrogel sensors have attracted much attention as they play a critical role in health monitoring, multifunctional electronic skin, and human-machine interfaces. However, the isotropic structure makes existing hydrogel sensors exhibit isotropic sensing performance. Therefore, it is a challenge to fabricate hydrogels with human tissue-like structures to achieve anisotropic sensing performance. Herein, we proposed a novel method to prepare anisotropic hydrogel sensors using high-absorbent alginate fibers. The anisotropic hydrogel, HAFG@CNTs, was prepared by adsorbing carbon nanotubes on high-absorbent alginate fibers and immobilized using polyacrylamide bonds. The hydrogel had anisotropic mechanical properties and anisotropic ionic conductivity. The modulus and toughness in the parallel fiber direction were 2.31 and 3.75 times higher than those in the perpendicular fiber direction, respectively, and the sensitivity of the parallel fiber direction was higher than that of the vertical direction when strain occurred. In addition, machine learning algorithms were used to predict and classify different action signals obtained from HAFG@CNTs with an accuracy of up to 98.18 %. These advantages offer great potential for applying HAFG@CNTs to wearable devices and medical monitoring.

Electrospun multifunctional nanofibers for advanced wearable sensors

The multifunctional extension of fiber-based wearable sensors determines their integration and sustainable development, with electrospinning technology providing reliable, efficient, and scalable support for fabricating these sensors. Despite numerous studies on electrospun fiber-based wearable sensors, further attention is needed to leverage composite structural engineering for functionalizing electrospun fibers. This paper systematically reviews the research progress on fiber-based multifunctional wearable sensors in terms of design concept, device fabrication, mechanism exploration, and application potential. Firstly, the basics of electrospinning are briefly introduced, including its development, principles, parameters, and material selection. Tactile sensors, as crucial components of wearable sensors, are discussed in detail, encompassing their performance parameters, transduction mechanisms, and preparation strategies for pressure, strain, temperature, humidity, and bioelectrical signal sensors. The main focus of the article is on the latest research progress in multifunctional sensing design concepts, multimodal decoupling mechanisms, sensing mechanisms, and functional extensions. These extensions include multimodal sensing, self-healing, energy harvesting, personal thermal management, EMI shielding, antimicrobial properties, and other capabilities. Furthermore, the review assesses existing challenges and outlines future developments for multifunctional wearable sensors, highlighting the need for continued research and innovation.

3D active-matrix multimodal sensor arrays for independent detection of pressure and temperature

Pressure and temperature sensing simultaneously and independently is crucial for creating electronic skin that replicates complex sensory functions of human skin. Thin-film transistor (TFT) arrays with sensors have enabled cross-talk-free spatial sensing. However, the thermal dependence of charge transport in semiconductors has resulted in interference between thermal and pressure stimuli. We develop multimodal sensor arrays based on three-dimensional integration of an active matrix to detect temperature and pressure independently. Our approach includes a calibrated compensation to decouple temperature and pressure signals. An individual pixel device consists of a TFT-based pressure sensor layered above a TFT-based temperature sensor. The detected temperature is used to compensate for the thermal effect on TFT-based pressure sensors. We develop large-area sensor arrays to enable accurate detection of two-dimensional pressure and temperature, leveraging these technologies to demonstrate advanced robotic grippers. The grippers stably grasp and lift a cup regardless of temperature, proving their possibility in skin-like electronic applications.

Thermoelectric porous laser-induced graphene-based strain-temperature decoupling and self-powered sensing

Despite rapid developments of wearable self-powered sensors, it is still elusive to decouple the simultaneously applied multiple input signals. Herein, we report the design and demonstration of stretchable thermoelectric porous graphene foam-based materials via facile laser scribing for self-powered decoupled strain and temperature sensing. The resulting sensor can accurately detect temperature with a resolution of 0.5°C and strain with a gauge factor of 1401.5. The design of the nanocomposites also explores the synergistic effect between the porous graphene and thermoelectric components to greatly enhance the Seebeck coefficient by almost four times (from 9.703 to 37.33 μV/°C). Combined with the stretchability of 45%, the self-powered sensor platform allows for early fire detection in remote settings and accurate and decoupled monitoring of temperature and strain during the wound healing process in situ. The design concepts from this study could also be leveraged to prepare multimodal sensors with decoupled sensing capability for accurate multi-parameter detection towards health monitoring.

A Decoupling Method for Multimode Flexible Capacitive Sensors to Decouple Spatial Forces and Dynamic Humidity

This paper focuses on a four-capacitor flexible sensor composed of two electrode materials; also, the decoupling method and sensing performance for multimodal sensing of spatial forces and dynamic humidity are described. In previous work, decoupling of multimode sensors is mostly done by monitoring the types of signals, numerical differences of the same signal, and stacking multiple parameter-sensitive materials. This paper mainly uses the different characteristics of the two electrode materials; in the simulation and experiment of humidity, the moisture-sensitive electrode quickly wets from the outside to the inside and expands, and the contact angle quickly decreases from 58.5 to 3.7° within 12.04 s, while the copper electrode has no obvious change; in the simulation and experiment of force, the capacitance value of the capacitor composed of the two electrodes changes steadily with the magnitude of the force. That is, the moisture-sensitive electrode can respond to both force and humidity, while the copper electrode responds only to force. So, we use the copper electrode to decouple the spatial force information and calculate the capacitance value of the moisture-sensitive electrode under the influence of only spatial force. The capacitance value of the moisture-sensitive electrode only affected by humidity can be obtained by the difference between the measured capacitance value and the capacitance value under the influence of only spatial force, and then, the humidity value can be obtained according to the material properties. When a single physical quantity changes, the built-in test platform of the experiment verifies that the decoupling accuracy of the force in the dual-mode sensor is as high as 0.95, and the decoupling accuracy of humidity is as high as 0.97. When the two physical quantities change synchronously, the decoupling accuracy of the force is relatively uniformly distributed within the range, and the decoupling accuracy of humidity can reach as high as 0.99 within the range of 31%RH-56%RH. As a humidity sensor, the sensitivity gradually decreases as the humidity increases. During the repeated changes from low humidity to high humidity, the dynamic characteristics, stability, and repeatability have very good performance. The repetition rate is 97.64%, the response time is 11.3 s, the recovery time is 6.8 s, and the capacitance value for 24 days remains basically unchanged. All of these provide some insight into the application of multimode sensors.

Flexible Passive Wireless Sensing Platform with Frequency Mapping and Multimodal Fusion

As one of the core parts of the Internet-of-things (IOTs), multimodal sensors have exhibited great advantages in fields such as human-machine interaction, electronic skin, and environmental monitoring. However, current multimodal sensors substantially introduce a bloated equipment architecture and a complicated decoupling mechanism. In this work we propose a multimodal fusion sensing platform based on a power-dependent piecewise linear decoupling mechanism, allowing four parameters to be perceived and decoded from the passive wireless single component, which greatly broadens the configurable freedom of a sensor in the IOT. A systematic model is employed to analyze the linear sensing properties and ensure the feasibility of the scheme. The excitation power dependence provides an efficient and quantitative linear decoupling strategy of unidentified combinations for multiple stimuli. As a validation for a wearable device such as electronic skin (e-skin), the functionalized sensing film polyaniline/graphene oxide (PANI/GO) is served to synchronously monitor humidity, temperature, ultraviolet, and proximity through the mapping in resonant frequency (fs). Compared with the output errors of ∼18.00%, ∼17.50%, ∼15.00%, and ∼20.00%, the maximum experimental errors of temperature, humidity, ultraviolet, and proximity are 5.70%, 4.00%, 5.00%, and 8.30% after decoupling, respectively. In general, the developed single-component multimodal fusion sensing platform offers a strategic advantage for a miniaturization, passive wireless, and inexpensive (less than $1) signal identification system with a facile circuit layout.

Multimodal Flexible Sensor for the Detection of Pressing-Bending-Twisting Mechanical Deformations

Flexible sensors are increasingly significant in applications such as smart wearables and human-computer interactions. However, typical flexible sensors are spatially limited and can generally detect only one deformation mode. This study presents a novel multimodal flexible sensor that combines three sensing units: optoelectronics, ionic liquids, and conductive fabrics. It employs a sophisticated superposition and combination of the three sensing methods to achieve up to eight mechanical deformations, including pressing, bending, twisting, and combinations thereof, all within a very small sensor space. This sensor has excellent detection performance, high sensitivity (optoelectronics 4.312, ionic liquid 8.186, conductive fabric 2.438), a wide measurement range (pressing 0-75 kPa, bending 0-90°, and twisting 0-180°), and good consistency and repeatability. To address the signal coupling problem in multimode sensors, a deep learning method based on the Transformer is combined to provide precise decoupling of multimode signals and high-precision characterization of each mechanical deformation. Finally, the wrist joint experiments demonstrate the sensor's versatile uses in human-computer interaction.

New horizons in smart plant sensors: key technologies, applications, and prospects

As the source of data acquisition, sensors provide basic data support for crop planting decision management and play a foundational role in developing smart planting. Accurate, stable, and deployable on-site sensors make intelligent monitoring of various planting scenarios possible. Recent breakthroughs in plant advanced sensors and the rapid development of intelligent manufacturing and artificial intelligence (AI) have driven sensors towards miniaturization, intelligence, and multi-modality. This review outlines the key technologies in developing new advanced sensors, such as micro-nano technology, flexible electronics technology, and micro-electromechanical system technology. The latest technological frontiers and development trends in sensor principles, fabrication processes, and performance parameters in soil and different segmented crop scenarios are systematically expounded. Finally, future opportunities, challenges, and prospects are discussed. We anticipate that introducing advanced technologies like nanotechnology and AI will rapidly and radically revolutionize the accuracy and intelligence of agricultural sensors, leading to new levels of innovation.

New Carbon Materials for Multifunctional Soft Electronics

Soft electronics are garnering significant attention due to their wide-ranging applications in artificial skin, health monitoring, human-machine interaction, artificial intelligence, and the Internet of Things. Various soft physical sensors such as mechanical sensors, temperature sensors, and humidity sensors are the fundamental building blocks for soft electronics. While the fast growth and widespread utilization of electronic devices have elevated life quality, the consequential electromagnetic interference (EMI) and radiation pose potential threats to device precision and human health. Another substantial concern pertains to overheating issues that occur during prolonged operation. Therefore, the design of multifunctional soft electronics exhibiting excellent capabilities in sensing, EMI shielding, and thermal management is of paramount importance. Because of the prominent advantages in chemical stability, electrical and thermal conductivity, and easy functionalization, new carbon materials including carbon nanotubes, graphene and its derivatives, graphdiyne, and sustainable natural-biomass-derived carbon are particularly promising candidates for multifunctional soft electronics. This review summarizes the latest advancements in multifunctional soft electronics based on new carbon materials across a range of performance aspects, mainly focusing on the structure or composite design, and fabrication method on the physical signals monitoring, EMI shielding, and thermal management. Furthermore, the device integration strategies and corresponding intriguing applications are highlighted. Finally, this review presents prospects aimed at overcoming current barriers and advancing the development of state-of-the-art multifunctional soft electronics.

A High-Repeatability Three-Dimensional Force Tactile Sensing System for Robotic Dexterous Grasping and Object Recognition

Robotic devices with integrated tactile sensors can accurately perceive the contact force, pressure, sliding, and other tactile information, and they have been widely used in various fields, including human-robot interaction, dexterous manipulation, and object recognition. To address the challenges associated with the initial value drift, and to improve the durability and accuracy of the tactile detection for a robotic dexterous hand, in this study, a flexible tactile sensor is designed with high repeatability by introducing a supporting layer for pre-separation. The proposed tactile sensor has a detection range of 0-5 N with a resolution of 0.2 N, and the repeatability error is as relatively small as 1.5%. In addition, the response time of the proposed tactile sensor under loading and unloading conditions are 80 ms and 160 ms, respectively. Moreover, a three-dimensional force decoupling detection method is developed by distributing tactile sensor units on a non-coplanar robotic fingertip. Finally, using a backpropagation neural network, the classification and recognition processes of nine types of objects with different shapes and categories are realized, achieving an accuracy higher than 95%. The results show that the proposed three-dimensional force tactile sensing system could be beneficial for the delicate manipulation and recognition for robotic dexterous hands.

Van der Waals Heterojunction Based Self-Powered Biomimetic Dual-Mode Sensor for Precise Object Identification

The design and fabrication of materials that can concurrently respond to light and gas within the dual-modal recognition domain present a significant challenge due to contradictory structural requirements. This innovative strategy introduces a type-I heterojunction, combining the properties of Sb2Te3 and WSe2 nanosheets, to overcome these obstacles. The heterojunction is prepared through a precise stacking approach to create a single-side barrier on the valence band and a near-zero offset on the conduction band. The resulting Sb2Te3/WSe2 heterojunction demonstrates unparalleled performance, showcasing the best integrated photoelectric and gas sensing performance in a single device to date. Based on the above features, the heterojunction successfully integrates visual and olfactory sensing performance, achieving the first biomimetic visual-olfactory dual-mode recognition in a single device. This simulation increased the accuracy of distinguishing electric and fuel-powered cars from ≈50% to ≈96%. This work introduces a novel approach to creating efficient, self-powered sensing materials, paving the way for next-generation biomimetic dual-model devices with broad applications in environmental protection, medical care, and other fields.

Flexible Pressure, Humidity, and Temperature Sensors for Human Health Monitoring

The rapid advancements in artificial intelligence, micro-nano manufacturing, and flexible electronics technology have unleashed unprecedented innovation and opportunities for applying flexible sensors in healthcare, wearable devices, and human-computer interaction. The human body's tactile perception involves physical parameters such as pressure, temperature, and humidity, all of which play an essential role in maintaining human health. Inspired by the sensory function of human skin, many bionic sensors have been developed to simulate human skin's perception to various stimuli and are widely applied in health monitoring. Given the urgent requirements for sensing performance and integration of flexible sensors in the field of wearable devices and health monitoring, here is a timely overview of recent advances in pressure, humidity, temperature, and multi-functional sensors for human health monitoring. It covers the fundamental components of flexible sensors and categorizes them based on different response mechanisms, including resistive, capacitive, voltage, and other types. Specifically, the application of these flexible tactile sensors in the area of human health monitoring is highlighted. Based on this, an extended overview of recent advances in dual/triple-mode flexible sensors integrating pressure, humidity, and temperature tactile sensing is presented. Finally, the challenges and opportunities of flexible sensors are discussed.

Progress in Protein-Based Hydrogels for Flexible Sensors: Insights from Casein

In recent years, the rapid advancement of flexible sensors as the cornerstone of flexible electronics has propelled a flourishing evolution within the realm of flexible electronics. Unlike traditional flexible devices, hydrogel flexible sensors have characteristic advantages such as biocompatibility, adhesion, and adjustable mechanical properties and have similar properties to human skin. Especially, biobased hydrogels have become the preferred substrate material for flexible sensors due to increased environmental pressures caused by the scarcity of petrochemical resources. In this regard, proteins possess advantages such as diverse amino acid compositions, adjustable advanced structures, chemical modifiability, the application of protein engineering techniques, and the ability to respond to various external stimuli. These enable the hydrogels constructed from them to have greater designability, flexibility, and adaptability. As a result, their applications in manufacturing various types of sensors have experienced rapid growth. This work systematically reviews the sensing mechanism of protein-based hydrogels, focusing on the preparation of protein-based hydrogels and the optimization of flexible sensors mainly from the perspective of a typical type of animal-derived protein casein. In addition, while the potential of casein is recognized, the limitations of casein-based hydrogels in flexible sensor applications are explored, and insights are provided into the development trends of next-generation sensors based on casein-based hydrogel materials.

Directional Characteristic Enhancement of an Omnidirectional Detection Sensor Enabled by Strain Partitioning Effects in a Periodic Composite Hole Substrate

An omnidirectional stretchable strain sensor with high resolution is a critical component for motion detection and human-machine interaction. It is the current dominant solution to integrate several consistent units into the omnidirectional sensor based on a certain geometric structure. However, the excessive similarity in orientation characteristics among sensing units restricts orientation recognition due to their closely matched strain sensitivity. In this study, based on strain partition modulation (SPM), a sensitivity anisotropic amplification strategy is proposed for resistive strain sensors. The stress distribution of a sensitive conductive network is modulated by structural parameters of the customized periodic hole array introduced underneath the elastomer substrate. Meanwhile, the strain isolation structures are designed on both sides of the sensing unit for stress interference immune. The optimized sensors exhibit excellent sensitivity (19 for 0-80%; 109 for 80%-140%; 368 for 140%-200%), with nearly a 7-fold improvement in the 140%-200% interval compared to bare elastomer sensors. More importantly, a sensing array composed of multiple units with different hole configurations can highlight orientation characteristics with amplitude difference between channels reaching up to 29 times. For the 48-class strain-orientation decoupling task, the recognition rate of the sensitivity-differentiated layout sensor with the lightweight deep learning network is as high as 96.01%, superior to that of 85.7% for the sensitivity-consistent layout. Furthermore, the application of the sensor to the fitness field demonstrates an accurate recognition of the wrist flexion direction (98.4%) and spinal bending angle (83.4%). Looking forward, this methodology provides unique prospects for broader applications such as tactile sensors, soft robotics, and health monitoring technologies.

High Performance H2S Sensor Based on Ordered Fe2O3/Ti3C2 Nanostructure at Room Temperature

The utilization of a heterogeneous nanojunction design has shown significant enhancements in the gas sensing capabilities of traditional metal oxide gas sensors. In this study, a novel room temperature H2S gas sensor employing Fe2O3 functionalized Ti3C2 MXene as the sensing material has been developed. This sensor exhibits a broad detection range (0.01-500 ppm), low detection limit (10 ppb), and rapid response/recovery times (10 s/15 s), making it ideal for ppb-level H2S detection. The exceptional gas sensitivity of Fe2O3/Ti3C2 composite to H2S can be attributed to several key factors. First, the unique layered frame structure of Fe2O3/Ti3C2 significantly amplifies the surface area of the hybrid material, enhancing the absorption and diffusion capabilities of H2S molecules. Second, the abundance of functional groups (-O, -OH, and -F) on the surface of Ti3C2 MXene nanosheets provides additional active sites for H2S adsorption, The density functional theory calculation confirms that the adsorption energy of the Fe2O3/Ti3C2 composite for H2S (-2.93 eV) is significantly lower than that of pure Fe2O3 (-2.37 eV) and Ti3C2 (-0.2 eV). Lastly, the remarkable metal conductivity of Ti3C2 MXene ensures efficient electron transfer, thereby enhancing overall sensing performance.

Overview of 3D Printing Multimodal Flexible Sensors

With the growing demand for flexible sensing systems and precision engineering, there is an increasing need for sensors that can accurately measure and analyze multimode signals. 3D printing technology has emerged as a crucial tool in the development of multimodal flexible sensors due to its advantages in design flexibility and manufacturing complex structures. This paper provides a review of recent advancements in 3D printing technology within the field of multimode flexible sensors, with particular emphasis on the relevant working mechanisms involved in decoupling complex signals. First, the research status of 3D printed multimodal flexible sensors is discussed, including their responsiveness to different modal stimuli such as mechanics, temperature, and gas. Furthermore, it explores methods for decoupling multimodal signals through structural and material design, artificial intelligence, and other technologies. Finally, this paper summarizes current challenges such as limited material selection, difficulties in miniaturization integration, and crosstalk between multisignal outputs. It also looks forward to future research directions in this area.

Recent Advances in Artificial Sensory Neurons: Biological Fundamentals, Devices, Applications, and Challenges

Spike-based neural networks, which use spikes or action potentials to represent information, have gained a lot of attention because of their high energy efficiency and low power consumption. To fully leverage its advantages, converting the external analog signals to spikes is an essential prerequisite. Conventional approaches including analog-to-digital converters or ring oscillators, and sensors suffer from high power and area costs. Recent efforts are devoted to constructing artificial sensory neurons based on emerging devices inspired by the biological sensory system. They can simultaneously perform sensing and spike conversion, overcoming the deficiencies of traditional sensory systems. This review summarizes and benchmarks the recent progress of artificial sensory neurons. It starts with the presentation of various mechanisms of biological signal transduction, followed by the systematic introduction of the emerging devices employed for artificial sensory neurons. Furthermore, the implementations with different perceptual capabilities are briefly outlined and the key metrics and potential applications are also provided. Finally, we highlight the challenges and perspectives for the future development of artificial sensory neurons.

An Invisible Dermal Nanotattoo-Based Smart Wearable Sensor for eDiagnostics of Jaundice

Despite substantial progress in the diagnosis of jaundice/hyperbilirubinemia as the most common disease and cause of hospitalization of newborns, on the eve of Industry/Healthcare 5.0, the development of accurate and reliable wearable diagnostic sensors for noninvasive smart monitoring of bilirubin (BIL) is still in high demand. Aiming to fabricate a smart wearable sensor for early diagnosis of neonatal jaundice and its therapeutic monitoring, we here report a fluorescent dermal nanotattoo that further coupled with an IoT-integrated wearable optoelectronic reader for minimally invasive, continuous, and real-time monitoring of BIL in interstitial fluid. Selective recovery of quenched fluorescence of the dermal tattoo sensor, composed of biocompatible dissolving/hydrogel microneedles loaded with fluorescent carbon quantum dots, upon blue light exposure used for jaundice phototherapy was utilized for highly selective BIL sensing. The fascinating features of our developed smart wearable tattoo sensor and its successful results with high correlation with blood BIL results make it a highly promising sensor for easy, minimally invasive, reliable, and smart eDiagnostics and continuous therapeutic eMonitoring of jaundice and other BIL-induced diseases at the point of care. We envision that the developed nanotattoo sensing bioplatform will inspire the development of future smart tattoo sensors in various diagnostic and monitoring scenarios.

Multifunctional Human-Computer Interaction System Based on Deep Learning-Assisted Strain Sensing Array

Continuous and reliable monitoring of gait is crucial for health monitoring, such as postoperative recovery of bone joint surgery and early diagnosis of disease. However, existing gait analysis systems often suffer from large volumes and the requirement of special space for setting motion capture systems, limiting their application in daily life. Here, we develop an intelligent gait monitoring and analysis prediction system based on flexible piezoelectric sensors and deep learning neural networks with high sensitivity (241.29 mV/N), quick response (66 ms loading, 87 ms recovery), and excellent stability (R2 = 0.9946). The theoretical simulations and experiments confirm that the sensor provides exceptional signal feedback, which can easily acquire accurate gait data when fitted to shoe soles. By integrating high-quality gait data with a custom-built deep learning model, the system can detect and infer human motion states in real time (the recognition accuracy reaches 94.7%). To further validate the sensor's application in real life, we constructed a flexible wearable recognition system with human-computer interaction interface and a simple operation process for long-term and continuous tracking of athletes' gait, potentially aiding personalized health management, early detection of disease, and remote medical care.

Advancements in Flexible Electronics Fabrication: Film Formation, Patterning, and Interface Optimization for Cutting-Edge Healthcare Monitoring Devices

Flexible electronics can seamlessly adhere to human skin or internal tissues, enabling the collection of physiological data and real-time vital sign monitoring in home settings, which give it the potential to revolutionize chronic disease management and mitigate mortality rates associated with sudden illnesses, thereby transforming current medical practices. However, the development of flexible electronic devices still faces several challenges, including issues pertaining to material selection, limited functionality, and performance instability. Among these challenges, the choice of appropriate materials, as well as their methods for film formation and patterning, lays the groundwork for versatile device development. Establishing stable interfaces, both internally within the device and in human-machine interactions, is essential for ensuring efficient, accurate, and long-term monitoring in health electronics. This review aims to provide an overview of critical fabrication steps and interface optimization strategies in the realm of flexible health electronics. Specifically, we discuss common thin film processing methods, patterning techniques for functional layers, interface challenges, and potential adjustment strategies. The objective is to synthesize recent advancements and serve as a reference for the development of innovative flexible health monitoring devices.

Mechanically Active Materials and Devices for Bio-Interfaced Pressure Sensors-A Review

Pressures generated by external forces or by internal body processes represent parameters of critical importance in diagnosing physiological health and in anticipating injuries. Examples span intracranial hypertension from traumatic brain injuries, high blood pressure from poor diet, pressure-induced skin ulcers from immobility, and edema from congestive heart failure. Pressures measured on the soft surfaces of vital organs or within internal cavities of the body can provide essential insights into patient status and progression. Challenges lie in the development of high-performance pressure sensors that can softly interface with biological tissues to enable safe monitoring for extended periods of time. This review focuses on recent advances in mechanically active materials and structural designs for classes of soft pressure sensors that have proven uses in these contexts. The discussions include applications of such sensors as implantable and wearable systems, with various unique capabilities in wireless continuous monitoring, minimally invasive deployment, natural degradation in biofluids, and/or multiplexed spatiotemporal mapping. A concluding section summarizes challenges and future opportunities for this growing field of materials and biomedical research.

Robust Treble-Weaving Wearable Textiles for Pressure and Temperature Monitoring in Harsh Environments

Wearable sensing textiles with continuous temperature monitoring, tactile feedback, and motion perception are highly desirable for personal safeguarding in extreme environments, such as fire scenes and extreme sports. However, it remains challenging for current wearable sensors to maintain reliable performance and provide point-of-care monitoring in harsh environments, such as high- and low-temperature or high-humidity conditions. Herein, a robust temperature and pressure sensing textile (TPST) with a hierarchical triple-weaving structure is developed using industrial weaving technology. The well-engineered interlacing configuration of the polyimide binding yarns in the triple-weaving structure tightly solidifies the carbon-based sensing yarns between two weaving layers, forming an integrated textile sensing array. The TPST not only exhibits excellent sensing sensitivity, reliability, and rapid response to pressure and temperature stimuli but also shows robust mechanical properties, flame resistance, and wearing comfort. Moreover, we demonstrate the application of the TPST for continuous temperature monitoring, human motion mapping, and vital sign monitoring. This technology offers significant potential for enhancing autonomous rescue operations and defense wearables.

Pushing Pressure Detection Sensitivity to New Limits by Modulus-Tunable Mechanism

Only microstructures are used to improve the sensitivity of iontronic pressure sensors. By modulating the compressive modulus, a breakthrough in the sensitivity of the iontronic pressure sensor is achieved. Furthermore, it allows for programmatic tailoring of sensor performance according to the requirements of different applications. Such a new strategy pushes the sensitivity up to a record-high of 25 548.24 kPa-1 and expands the linear pressure range from 15 to 127 kPa. Additionally, the sensor demonstrates excellent mechanical stability over 10 000 compression-release cycles. Based on this, a well-controlled robotic hand that precisely tracks the pressure behavior inside a balloon to autonomously regulate the gripping angle is developed. This paves the way for the application of iontronic pressure sensors in precise sensing scenarios.

Multifunctional laser-induced graphene circuits and laser-printed nanomaterials toward non-invasive human kidney function monitoring

Faced with the increasing prevalence of chronic kidney disease (CKD), portable monitoring of CKD-related biomarkers such as potassium ion (K+), creatinine (Cre), and lactic acid (Lac) levels in sweat has shown tremendous potential for early diagnosis. However, a rapidly manufacturable portable device integrating multiple CKD-related biomarker sensors for ease of sweat testing use has yet to be reported. Here, a portable electrochemical sensor integrated with multifunctional laser-induced graphene (LIG) circuits and laser-printed nanomaterials based working electrodes fabricated by fully automatic laser manufacturing is proposed for non-invasive human kidney function monitoring. The sensor comprises a two-electrode LIG circuit for K+ sensing, a three-electrode LIG circuit with a Kelvin compensating connection for Cre and Lac sensing, and a printed circuit board based portable electrochemical workstation. The working electrodes containing Cu and Cu2O nanoparticles fabricated by two-step laser printing show good sensitivity and selectivity toward Cre and Lac sensing. The sensor circuits are fabricated by generating a hydrophilic-hydrophobic interface on a patterned LIG through laser. This sensor recruited rapid laser manufacturing and integrated with multifunctional LIG circuits and laser-printed nanomaterials based working electrodes, which is a potential kidney function monitoring solution for healthy people and kidney disease patients.

Designs and Applications for the Multimodal Flexible Hybrid Epidermal Electronic Systems

Research on the flexible hybrid epidermal electronic system (FHEES) has attracted considerable attention due to its potential applications in human-machine interaction and healthcare. Through material and structural innovations, FHEES combines the advantages of traditional stiff electronic devices and flexible electronic technology, enabling it to be worn conformally on the skin while retaining complex system functionality. FHEESs use multimodal sensing to enhance the identification accuracy of the wearer's motion modes, intentions, or health status, thus realizing more comprehensive physiological signal acquisition. However, the heterogeneous integration of soft and stiff components makes balancing comfort and performance in designing and implementing multimodal FHEESs challenging. Herein, multimodal FHEESs are first introduced in 2 types based on their different system structure: all-in-one and assembled, reflecting totally different heterogeneous integration strategies. Characteristics and the key design issues (such as interconnect design, interface strategy, substrate selection, etc.) of the 2 multimodal FHEESs are emphasized. Besides, the applications and advantages of the 2 multimodal FHEESs in recent research have been presented, with a focus on the control and medical fields. Finally, the prospects and challenges of the multimodal FHEES are discussed.

High-Fidelity Bioelectrodes with Bidirectional Ion-Electron Transduction Capability by Integrating Multiple Charge-Transfer Processes

Bioelectronics is an exciting field that bridges the gap between physiological activities and external electronic devices, striving for high resolution, high conformability, scalability, and ease of integration. One crucial component in bioelectronics is bioelectrodes, designed to convert neural activity into electronic signals or vice versa. Previously reported bioelectrodes have struggled to meet several essential requirements simultaneously: high-fidelity signal transduction, high charge injection capability, strain resistance, and multifunctionality. This work introduces a novel strategy for fabricating superior bioelectrodes by merging multiple charge-transfer processes. The resulting bioelectrodes offer accurate ion-to-electron transduction for capturing electrophysiological signals, dependable charge injection capability for neuromodulation, consistent electrode potential for artifact rejection and biomolecule sensing, and high transparency for seamless integration with optoelectronics. Furthermore, the bioelectrode can be designed to be strain-insensitive by isolating signal transduction from electron transportation. The innovative concept presented in this work holds great promise for extending to other electrode materials and paves the way for the advancement of multimodal bioelectronics.

Quantitative softness and texture bimodal haptic sensors for robotic clinical feature identification and intelligent picking

Replicating human somatosensory networks in robots is crucial for dexterous manipulation, ensuring the appropriate grasping force for objects of varying softness and textures. Despite advances in artificial haptic sensing for object recognition, accurately quantifying haptic perceptions to discern softness and texture remains challenging. Here, we report a methodology that uses a bimodal haptic sensor to capture multidimensional static and dynamic stimuli, allowing for the simultaneous quantification of softness and texture features. This method demonstrates synergistic measurements of elastic and frictional coefficients, thereby providing a universal strategy for acquiring the adaptive gripping force necessary for scarless, antislippage interaction with delicate objects. Equipped with this sensor, a robotic manipulator identifies porcine mucosal features with 98.44% accuracy and stably grasps visually indistinguishable mature white strawberries, enabling reliable tissue palpation and intelligent picking. The design concept and comprehensive guidelines presented would provide insights into haptic sensor development, promising benefits for robotics.

Recent advances of biocompatible optical nanobiosensors in liquid biopsy: towards early non-invasive diagnosis

Liquid biopsy is a non-invasive diagnostic method that can reduce the risk of complications and offers exceptional benefits in the dynamic monitoring and acquisition of heterogeneous cell population information. Optical nanomaterials with excellent light absorption, luminescence, and photoelectrochemical properties have accelerated the development of liquid biopsy technologies. Owing to the unique size effect of optical nanomaterials, their improved optical properties enable them to exhibit good sensitivity and specificity for mitigating signal interference from various molecules in body fluids. Nanomaterials with biocompatible and optical sensing properties play a crucial role in advancing the maturity and diversification of liquid biopsy technologies. This article offers a comprehensive review of recent advanced liquid biopsy technologies that utilize novel biocompatible optical nanomaterials, including fluorescence, colorimetric, photoelectrochemical, and Raman broad-spectrum-based biosensors. We focused on liquid biopsy for the most significant early biomarkers in clinical medicine, and specifically reviewed reports on the effectiveness of optical nanosensing technology in the detection of real patient samples, which may provide basic evidence for the transition of optical nanosensing technology from engineering design to clinical practice. Furthermore, we introduced the integration of optical nanosensing-based liquid biopsy with modern devices, such as smartphones, to demonstrate the potential of the technology in portable clinical diagnosis.

Marangoni-driven deterministic formation of softer, hollow microstructures for sensitivity-enhanced tactile system

Microengineering the dielectric layers with three-dimensional microstructures has proven effective in enhancing the sensitivity of flexible pressure sensors. However, the widely employed geometrical designs of solid microstructures exhibit limited sensitivity over a wide range of pressures due to their inherent but undesired structural compressibility. Here, a Marangoni-driven deterministic formation approach is proposed for fabricating hollow microstructures, allowing for greater deformation while retarding structural stiffening during compression. Fluid convective deposition enables solute particles to reassemble in template microstructures, controlling the interior cavity with a void ratio exceeding 90%. The hollow micro-pyramid sensor exhibits a 10-fold sensitivity improvement across wider pressure ranges over the pressure sensor utilizing solid micro-pyramids, and an ultra-low detect limit of 0.21 Pa. With the advantages of facilitation, scalability, and large-area compatibility, such an approach for hollow microstructures can be expanded to other sensor types for superior performance and has considerable potential in robotic tactile and epidermal devices.

Self-Powered and Self-Recoverable Multimodal Force Sensors Based on Trap State and Interfacial Electron Transfer

Multi-dimensional force sensing that combines intensity, location, area and the like could gather a wealth of information from mechanical stimuli. Developing materials with force-induced optical and electrical dual responses would provide unique opportunities to multi-dimensional force sensing, with electrical signals quantifying the force amplitude and the luminescence output providing spatial distribution of force. However, the reliance on external power supply and high-energy excitation source brings significant challenges to the applicability of multi-dimensional force sensors. Here we reported the mechanical energy-driven and sunlight-activated materials with force-induced dual responses, and investigated the underlying mechanisms of self-sustainable force sensing. Theoretical analysis and experimental data unraveled that trap-controlled luminescence and interfacial electron transfer play a major role in force-induced optical and electrical output. These materials were manufactured into pressure sensor with renewable dual-mode output for quantifying and visualization of pressures by electrical and optical output, respectively, without power supply and high-energy irradiation. The quantification of tactile sensation and stimuli localization of mice highlighted the multi-dimensional sensing ability of the sensor. Overall, this self-powered pressure sensor with multimodal output provides more modalities of force sensing, poised to change the way that intelligent devices sense with the world.

Highly Sensitive Iontronic Pressure Sensor with Side-by-Side Package Based on Alveoli and Arch Structure

Flexible pressure sensors play a significant role in wearable devices and electronic skin. Iontronic pressure sensors with high sensitivity, wide measurement range, and high resolution can meet requirements. Based on the significant deformation characteristics of alveoli to improve compressibility, and the ability of the arch to disperse vertical pressure into horizontal thrust to increase contact area, a graded hollow ball arch (GHBA) microstructure is proposed, greatly improving sensitivity. The fabrication of GHBA ingeniously employs a double-sided structure. One side uses mold casting to create convex structures, while the other utilizes the evaporation of moisture during the curing process to form concave structures. At the same time, a novel side-by-side package structure is proposed, ensuring pressure on flexible substrate is maximally transferred to the GHBA microstructure. Within the range of 0.2 Pa-300 kPa, the iontronic pressure sensor achieves a maximum sensitivity of 10 420.8 kPa-1, pressure resolution of 0.1% under the pressure of 100 kPa, and rapid response/recovery time of 40/35 ms. In wearable devices, it is capable of monitoring dumbbell curl exercises and wirelessly correcting sitting positions. In electronic skin, it can non-contactly detect the location of the wind source and achieve object classification prediction when combined with the CNN model.

Hierarchical Piezoelectric Composites for Noninvasive Continuous Cardiovascular Monitoring

Continuous monitoring of blood pressure (BP) and multiparametric analysis of cardiac functions are crucial for the early diagnosis and therapy of cardiovascular diseases. However, existing monitoring approaches often suffer from bulky and intrusive apparatus, cumbersome testing procedures, and challenging data processing, hampering their applications in continuous monitoring. Here, a heterogeneously hierarchical piezoelectric composite is introduced for wearable continuous BP and cardiac function monitoring, overcoming the rigidity of ceramic and the insensitivity of polymer. By optimizing the hierarchical structure and components of the composite, the developed piezoelectric sensor delivers impressive performances, ensuring continuous and accurate monitoring of BP at Grade A level. Furthermore, the hemodynamic parameters are extracted from the detected signals, such as local pulse wave velocity, cardiac output, and stroke volume, all of which are in alignment with clinical results. Finally, the all-day tracking of cardiac function parameters validates the reliability and stability of the developed sensor, highlighting its potential for personalized healthcare systems, particularly in early diagnosis and timely intervention of cardiovascular disease.

Electrophilicity Modulation for Sub-ppm Visualization and Discrimination of EDA

Precise and timely recognition of hazardous chemical substances is of great significance for safeguarding human health, ecological environment, public security, etc., especially crucial for adopting appropriate disposition measures. Up to now, there remains a practical challenge to sensitively detect and differentiate organic amines with similar chemical structures with intuitive analysis outcomes. Here, a unique optical probe with two electrophilic recognition sites for rapid and ultra-sensitive ratiometric fluorescence detection of ethylenediamine (EDA) is presented, while producing distinct fluorescence signals to its structural analog. The probe exhibits ppb/nmol level sensitivity to liquidous and gaseous EDA, specific recognition toward EDA without disturbance to up to 28 potential interferents, as well as rapid fluorescence response within 0.2 s. By further combining the portable sensing chip with the convolutional algorithm endowed with image processing, this work cracked the problem of precisely discriminating the target and non-targets at extremely low concentrations.

Flexible Multimodal Magnetoresistive Sensors Based on Alginate/Poly(vinyl alcohol) Foam with Stimulus Discriminability for Soft Electronics Using Machine Learning

Flexible foam-based sensors have attracted substantial interest due to their high specific surface area, light weight, superior deformability, and ease of manufacture. However, it is still a challenge to integrate multimodal stimuli-responsiveness, high sensitivity, reliable stability, and good biocompatibility into a single foam sensor. To achieve this, a magnetoresistive foam sensor was fabricated by an in situ freezing-polymerization strategy based on the interpenetrating networks of sodium alginate, poly(vinyl alcohol) in conjunction with glycerol, and physical reinforcement of core-shell bidisperse magnetic particles. The assembled sensor exhibited preferable magnetic/strain-sensing capability (GF ≈ 0.41 T-1 for magnetic field, 4.305 for tension, -0.735 for bending, and -1.345 for pressing), quick response time, and reliable durability up to 6000 cycles under external stimuli. Importantly, a machine learning algorithm was developed to identify the encryption information, enabling high recognition accuracies of 99.22% and 99.34%. Moreover, they could be employed as health systems to detect human physiological motion and integrated as smart sensor arrays to perceive external pressure/magnetic field distributions. This work provides a simple and ecofriendly strategy to fabricate biocompatible foam-based multimodal sensors with potential applications in next-generation soft electronics.

Biomimetic Electronic Skin Based on a Stretchable Ionogel Mechanoreceptor Composed of Crumpled Conductive Rubber Electrodes for Synchronous Strain, Pressure, and Temperature Detection

Electronic skin (e-skin) is showing a huge potential in human-computer interaction, intelligent robots, human health, motion monitoring, etc. However, it is still challenging for e-skin to realize distinguishable detection of stretching strain, vertical pressure, and temperature through a simple noncoupling structure design. Here, a stretchable multimodal biomimetic e-skin was fabricated by integrating layer-by-layer self-assembled crumpled reduced graphene oxide/multiwalled carbon nanotubes film on natural rubber (RGO/MWCNTs@NR) as stretchable conductive electrodes and polyacrylamide/NaCl ionogel as a dielectric layer into an ionotropic capacitive mechanoreceptor. Unlike natural skin receptors, the sandwich-like stretchable ionogel mechanoreceptor possessed a distinct ionotropic capacitive behavior for strain and pressure detection. The results showed that the biomimetic e-skin displayed a negative capacitance change with superior stretchability (0-300%) and a high gauge factor of 0.27 in 180-300% strain, while exhibiting a normal positive piezo-capacitance behavior in vertical pressure range of 0-15 kPa with a maximal sensitivity of 1.759 kPa-1. Based on this feature, the biomimetic e-skin showed an excellent synchronous detection capability of planar strain and vertical pressure in practical wearable applications such as gesture recognition and grasping movement detection without a complicated mathematical or signal decoupling process. In addition, the biomimetic e-skin exhibited a quantifiable linear responsiveness to temperature from 20-90 °C with a temperature coefficient of 0.55%/°C. These intriguing properties gave the biomimetic e-skin the ability to perform a complete function similar to natural skin but beyond its performance for future wearable devices and artificial intelligence devices.

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.

Multifunctional cross-sensitive magnetic alginate-chitosan-polyethylene oxide nanofiber sensor for human-machine interaction

Flexible nanofiber membranes are compelling materials for the development of functional multi-mode sensors; however, their essential features such as high cross-sensitivity, reliable stability and signal discrimination capability have rarely been realized simultaneously in one sensor. Here, a novel multi-mode sensor with a nanofiber membrane structure based on multiple interpenetrating networks of bidisperse magnetic particles, sodium alginate (SA), chitosan (CHI) in conjunction with polyethylene oxide hydrogels was prepared in a controllable electrospinning technology. Specifically, the morphology distributions of nanofibers could be regulated by the crosslinking degree of the interpenetrating networks and the spinning process parameters. The incorporation of SA and CHI endowed the sensor with desirable flexibility, ideal biocompatibility and skin-friendly property. Besides, the assembled sensors not only displayed preferable magnetic sensitivity of 0.34 T-1 and reliable stability, but also exhibited favorable cross-sensitivity, quick response time, and long-term durability for over 5000 cycles under various mechanical stimuli. Importantly, the multi-mode stimuli could be discriminated via producing opposite electrical signals. Furthermore, based on the signal distinguishability of the sensor, a wearable Morse code translation system assisted by the machine learning algorithm was demonstrated, enabling a high recognizing accuracy (>99.1 %) for input letters and numbers information. Due to the excellent multifunctional sensing characteristics, we believe that the sensor will have a high potential in wearable soft electronics and human-machine interactions.

Age of Flexible Electronics: Emerging Trends in Soft Multifunctional Sensors

With the commercialization of first-generation flexible mobiles and displays in the late 2010s, humanity has stepped into the age of flexible electronics. Inevitably, soft multifunctional sensors, as essential components of next-generation flexible electronics, have attracted tremendous research interest like never before. This review is dedicated to offering an overview of the latest emerging trends in soft multifunctional sensors and their accordant future research and development (R&D) directions for the coming decade. First, key characteristics and the predominant target stimuli for soft multifunctional sensors are highlighted. Second, important selection criteria for soft multifunctional sensors are introduced. Next, emerging materials/structures and trends for soft multifunctional sensors are identified. Specifically, the future R&D directions of these sensors are envisaged based on their emerging trends, namely i) decoupling of multiple stimuli, ii) data processing, iii) skin conformability, and iv) energy sources. Finally, the challenges and potential opportunities for these sensors in future are discussed, offering new insights into prospects in the fast-emerging technology.