All Resistive Pressure-Temperature Bimodal Sensing E-Skin for Object Classification

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.

Laser-Induced Graphene-Based Sensors in Health Monitoring: Progress, Sensing Mechanisms, and Applications

The rising global population and improved living standards have led to an alarming increase in non-communicable diseases, notably cardiovascular and chronic respiratory diseases, posing a severe threat to human health. Wearable sensing devices, utilizing micro-sensing technology for real-time monitoring, have emerged as promising tools for disease prevention. Among various sensing platforms, graphene-based sensors have shown exceptional performance in the field of micro-sensing. Laser-induced graphene (LIG) technology, a cost-effective and facile method for graphene preparation, has gained particular attention. By converting polymer films directly into patterned graphene materials at ambient temperature and pressure, LIG offers a convenient and environmentally friendly alternative to traditional methods, opening up innovative possibilities for electronic device fabrication. Integrating LIG-based sensors into health monitoring systems holds the potential to revolutionize health management. To commemorate the tenth anniversary of the discovery of LIG, this work provides a comprehensive overview of LIG's evolution and the progress of LIG-based sensors. Delving into the diverse sensing mechanisms of LIG-based sensors, recent research advances in the domain of health monitoring are explored. Furthermore, the opportunities and challenges associated with LIG-based sensors in health monitoring are briefly discussed.

Ultra-Thin Highly Sensitive Electronic Skin for Temperature Monitoring

Electronic skin capable of reliable monitoring of human skin temperature is crucial for the advancement of non-invasive clinical biomonitoring, disease diagnosis, and health surveillance. Ultra-thin temperature sensors, with excellent mechanical flexibility and robustness, can conformably adhere to uneven skin surfaces, making them ideal candidates. However, achieving high sensitivity often demands sacrificing flexibility, rendering the development of temperature sensors combining both qualities a challenging task. In this study, we utilized a low-cost drop-casting technique to print ultra-thin and lightweight (thickness: approximately 3 µm, weight: 0.61 mg) temperature sensors based on a combination of vanadium dioxide and PEDOT:PSS at room temperature and atmospheric conditions. These sensors exhibit high sensitivity (temperature coefficient of resistance: -5.11%/°C), rapid response and recovery times (0.36 s), and high-temperature accuracy (0.031 °C). Furthermore, they showcased remarkable durability in extreme bending conditions (bending radius = 400 µm), along with stable electrical performance over approximately 2400 bending cycles. This work offers a low-cost, simple, and scalable method for manufacturing ultra-thin and lightweight electronic skins for temperature monitoring, which seamlessly integrate exceptional temperature-measuring capabilities with optimal flexibility.

Structure-Foldable and Performance-Tailorable PI Paper-Based Triboelectric Nanogenerators Processed and Controlled by Laser-Induced Graphene

Laser-induced graphene (LIG) technology has provided a new manufacturing strategy for the rapid and scalable assembling of triboelectric nanogenerators (TENG). However, current LIG-based TENG commonly rely on polymer films, e.g., polyimide (PI) as both friction material and carbon precursor of electrodes, which limit the structural diversity and performance escalation due to its incapability of folding and creasing. Using specialized PI paper composed of randomly distributed PI fibers to substantially enhance its foldability, this work creates a new type of TENG, which are structurally foldable and stackable, and performance tailorable. First, by systematically investigating the laser power-regulated performance of single-unit TENG, the open-circuit voltage can be effectively improved. By further exploiting the folding process, multiple TENG units can be assembled together to form multi-layered structures to continuously expand the open-circuit voltage from 5.3 to 34.4 V cm-2, as the increase of friction units from 1 to 16. Last, by fully utilizing the unique structure and performance, representative energy-harvesting and smart-sensing applications are demonstrated, including a smart shoe to recognize running motions and power LEDs, a smart leaf to power a thermometer by wind, a matrix sensor to recognize writing trajectories, as well as a smart glove to recognize different objects.

Lithium-Ion-Doped Eutectogel for Surface-Capacitive Sensing Touch Panel

Touch panels are deemed as a critical platform for the future of human--computer interaction. Recently, flexible touch panels have attracted much attention due to their superior adhesivity and integratability to the human body. However, hydrogel- or organogel-based devices suffer from instability due to liquid evaporation or low-conductivity substrates. It demands an alternative functional touch panel featuring temperature tolerance, high conductivity, and stretchability. Here, we introduce an eutectogel by immobilizing a novel deep eutectic solvent (DES) within 2-hydroxyethyl acrylate (HEA) covalently cross-linked polymer scaffolds. In this DES (ethylene carbonate(EC)-LiTFSI), the C═O group of EC is unique as an electron donor exhibiting strong coordination interactions with Li+, promoting the dissociation of Li+ from LiTFSI to achieve excellent conductivity. Benefiting from their traits, eutectogel presents high conductivity, transmittance, antifreezing, and mechanical strength. In addition, using the surface-capacitive sensing mechanism, the eutectogel can be designed as a 1D strip and 2D rectangular touch panel which can achieve high-resolution touching tracks, even in a low-temperature environment and pressure-then-recovered state. This eutectogel strategy is envisioned to facilitate the development of next-generation intelligent devices, especially in extreme stretching and low-temperature application scenarios.

Recent advances in wearable flexible electronic skin: types, power supply methods, and development prospects

In recent years, wearable e-skin has emerged as a prominent technology with a wide range of applications in healthcare, health surveillance, human-machine interface, and virtual reality. Inspired by the properties of human skin, arrayed wearable e-skin is a novel technology that offers multifunctional sensing capabilities. It can detect and quantify various stimuli, mimicking the human somatosensory system, and record a wide range of physical and physiological parameters in real time. By combining flexible electronic device units with a data acquisition system, specific functional sensors can be distributed in targeted areas to achieve high sensitivity, resolution, adjustable sensing range, and large-area expandability. This review provides a comprehensive overview of recent advances in wearable e-skin technology, including its development status, types of applications, power supply methods, and prospects for future development. The emphasis of current research is on enhancing the sensitivity and stability of sensors, improving the comfort and reliability of wearable devices, and developing intelligent data processing and application algorithms. This review aims to serve as a scientific reference for the intelligent development of wearable e-skin technology.

Intelligence Sparse Sensor Network for Automatic Early Evaluation of General Movements in Infants

General movements (GMs) have been widely used for the early clinical evaluation of infant brain development, allowing immediate evaluation of potential development disorders and timely rehabilitation. The infants' general movements can be captured digitally, but the lack of quantitative assessment and well-trained clinical pediatricians presents an obstacle for many years to achieve wider deployment, especially in low-resource settings. There is a high potential to explore wearable sensors for movement analysis due to outstanding privacy, low cost, and easy-to-use features. This work presents a sparse sensor network with soft wireless IMU devices (SWDs) for automatic early evaluation of general movements in infants. The sparse network consisting of only five sensor nodes (SWDs) with robust mechanical properties and excellent biocompatibility continuously and stably captures full-body motion data. The proof-of-the-concept clinical testing with 23 infants showcases outstanding performance in recognizing neonatal activities, confirming the reliability of the system. Taken together with a tiny machine learning algorithm, the system can automatically identify risky infants based on the GMs, with an accuracy of up to 100% (99.9%). The wearable sparse sensor network with an artificial intelligence-based algorithm facilitates intelligent evaluation of infant brain development and early diagnosis of development disorders.

Thermogalvanic hydrogel-based e-skin for self-powered on-body dual-modal temperature and strain sensing

Sensing of both temperature and strain is crucial for various diagnostic and therapeutic purposes. Here, we present a novel hydrogel-based electronic skin (e-skin) capable of dual-mode sensing of temperature and strain. The thermocouple ion selected for this study is the iodine/triiodide (I-/I3-) redox couple, which is a common component in everyday disinfectants. By leveraging the thermoelectric conversion in conjunction with the inherent piezoresistive effect of a gel electrolyte, self-powered sensing is achieved by utilizing the temperature difference between the human body and the external environment. The composite hydrogels synthesized from polyvinyl alcohol (PVA) monomers using a simple freeze‒thaw method exhibit remarkable flexibility, extensibility, and adaptability to human tissue. The incorporation of zwitterions further augments the resistance of the hydrogel to dehydration and low temperatures, allowing maintenance of more than 90% of its weight after 48 h in the air. Given its robust thermal current response, the hydrogel was encapsulated and then integrated onto various areas of the human body, including the cheeks, fingers, and elbows. Furthermore, the detection of the head-down state and the monitoring of foot movements demonstrate the promising application of the hydrogel in supervising the neck posture of sedentary office workers and the activity status. The successful demonstration of self-powered on-body temperature and strain sensing opens up new possibilities for wearable intelligent electronics and robotics.

Bioinspired electrically stable, optically tunable thermal management electronic skin via interfacial self-assembly

The skin is the largest organ in the human body and serves vital functions such as sensation, thermal management, and protection. While electronic skin (E-skin) has made significant progress in sensory functions, achieving adaptive thermal management akin to human skin has remained a challenge. Drawing inspiration from squid skin, we have developed a hybrid electronic-photonic skin (hEP-skin) using an elastomer semi-embedded with aligned silver nanowires through interfacial self-assembly. With mechanically adjustable optical properties, the hEP-skin demonstrates adaptive thermal management abilities, warming in the range of +3.5°C for heat preservation and cooling in the range of -4.2°C for passive cooling. Furthermore, it exhibits an ultra-stable high electrical conductivity of ∼4.5×104 S/cm, even under stretching, bending or torsional deformations over 10,000 cycles. As a proof of demonstration, the hEP-skin successfully integrates stretchable light-emitting electronic skin with adaptive thermal management photonic skin.

Proximity Sensing Electronic Skin: Principles, Characteristics, and Applications

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

Flexible temperature-pressure dual sensor based on 3D spiral thermoelectric Bi2Te3 films

Dual-parameter pressure-temperature sensors are widely employed in personal health monitoring and robots to detect external signals. Herein, we develop a flexible composite dual-parameter pressure-temperature sensor based on three-dimensional (3D) spiral thermoelectric Bi2Te3 films. The film has a (000l) texture and good flexibility, exhibiting a maximum Seebeck coefficient of -181 μV K-1 and piezoresistance gauge factor of approximately -9.2. The device demonstrates a record-high temperature-sensing performance with a high sensing sensitivity (-426.4 μV K-1) and rapid response time (~0.95 s), which are better than those observed in most previous studies. In addition, owing to the piezoresistive effect in the Bi2Te3 film, the 3D-spiral deviceexhibits significant pressure-response properties with a pressure-sensing sensitivity of 120 Pa-1. This innovative approach achieves high-performance dual-parameter sensing using one kind of material with high flexibility, providing insight into the design and fabrication of many applications, such as e-skin.

Integrating In-Plane Thermoelectricity and Out-Plane Piezoresistivity for Fully Decoupled Temperature-Pressure Sensing

A flexible sensor that simultaneously senses temperature and pressure is crucial in various fields, such as human-machine interaction, artificial intelligence, and biomedical applications. Previous research has mainly focused on single-function flexible sensors for e-skins or smart devices, and integrated bimodal sensing of temperature and pressure without complex crosstalk decoupling algorithms remains challenging. In this work, a flexible bimodal sensor is proposed that utilizes spatial orthogonality between in-plane thermoelectricity and out-plane piezoresistivity, which enables fully decoupled temperature-pressure sensing. The proposed bimodal sensor exhibits a high sensitivity of 281.46 µV K-1 for temperature sensing and 2.181 kPa-1 for pressure sensing. In the bimodal sensing mode, the sensor exhibits negligible mutual interference, providing a measurement error of ± 7% and ± 8% for temperature and pressure, respectively, within a 120 kPa pressure range and a 40 K temperature variation. Additionally, simultaneous spatial mapping of temperature and pressure with a bimodal sensor array enables contact shape identification with enhanced accuracy beyond the limit imposed by the number of sensing units. The proposed integrated bimodal sensing strategy does not require complex crosstalk decoupling algorithms, which represents a significant advancement in flexible sensors for applications that necessitate simultaneous sensing of temperature and pressure.

Templated Laser-Induced-Graphene-Based Tactile Sensors Enable Wearable Health Monitoring and Texture Recognition via Deep Neural Network

Flexible tactile sensors show great potential for portable healthcare and environmental monitoring applications. However, challenges persist in scaling up the manufacturing of stable tactile sensors with real-time feedback. This work demonstrates a robust approach to fabricating templated laser-induced graphene (TLIG)-based tactile sensors via laser scribing, elastomer hot-pressing transfer, and 3D printing of the Ag electrode. With different mesh sandpapers as templates, TLIG sensors with adjustable sensing properties were achieved. The tactile sensor obtains excellent sensitivity (52260.2 kPa-1 at a range of 0-7 kPa), a broad detection range (up to 1000 kPa), a low limit of detection (65 Pa), a rapid response (response/recovery time of 12/46 ms), and excellent working stability (10000 cycles). Benefiting from TLIG's high performance and waterproofness, TLIG sensors can be used as health monitors and even in underwater scenarios. TLIG sensors can also be integrated into arrays acting as receptors of the soft robotic gripper. Furthermore, a deep neural network based on the convolutional neural network was employed for texture recognition via a soft TLIG tactile sensing array, achieving an overall classification rate of 94.51% on objects with varying surface roughness, thus offering high accuracy in real-time practical scenarios.