Imperceptible, designable, and scalable braided electronic cord

Smart Textiles for Personalized Sports and Healthcare

Advances in wearable electronics and information technology drive sports data collection and analysis toward real-time visualization and precision. The growing pursuit of athleticism and healthy life makes it appealing for individuals to track their real-time health and exercise data seamlessly. While numerous devices enable sports and health monitoring, maintaining comfort over long periods remains a considerable challenge, especially in high-intensity and sweaty sports scenarios. Textiles, with their breathability, deformability, and moisture-wicking abilities, ensure exceptional comfort during prolonged wear, making them ideal for wearable platforms. This review summarized the progress of research on textile-based sports monitoring devices. First, the design principles and fabrication methods of smart textiles were introduced systematically. Textiles undergo a distinctive fiber-yarn-fabric or fiber-fabric manufacturing process that allows for the regulation of performance and the integration of functional elements at every step. Then, the performance requirements for precise sports data collection of smart textiles, including main vital signs, joint movement, and data transmission, were discussed. Lastly, the applications of smart textiles in various sports scenarios are demonstrated. Additionally, the review provides an in-depth analysis of the emerging challenges, strategies, and opportunities for the research and development of sports-oriented smart textiles. Smart textiles not only maintain comfort and accuracy in sports, but also serve as inexpensive and efficient information-gathering terminals. Therefore, developing multifunctional, cost-effective textile-based systems for personalized sports and healthcare is a pressing need for the future of intelligent sports.

Imperceptible and Disposable Humidity and Temperature Sensors with Low Environmental Footprint Enabled by Aerosol Jet Printing and Cellulose-Based Substrates

The continuous growth of the electronics industry requires a reevaluation of traditional materials and manufacturing techniques to address the rising issue of electronic waste (e-waste). Environmental monitoring devices, which provide valuable insights into factors such as humidity and temperature, currently rely on non-degradable substrates and toxic metals, significantly contributing to plastic and electronic waste. Furthermore, conventional manufacturing techniques like screen printing, while effective, are limited in their ability to produce miniaturized, high-resolution features. Here, aerosol jet printing is used to fabricate devices for humidity and temperature monitoring, enabling minimal footprint (99.75% material reduction vs other printing methods), and precise patterning of features as small as 13 µm, even on biodegradable substrates. The resistive sensor is made of biocompatible conducting polymer poly(3,4 ethylenedioxythiophene) doped with polystyrene sulfonate (PEDOT:PSS) on a biodegradable cellulose substrate. It operates efficiently within a 10-80% RH range while maintaining a high optical transmittance of 91% in the visible spectrum. Additionally, by crosslinking PEDOT:PSS with (3 Glycidyloxypropyl)Trimethoxysilane (GOPS), the sensors effectively detects changes within a temperature range of 20-50 °C. This fully printed sensor on biodegradable substrates represents a step toward next-generation, eco-friendly, and metal-free solutions for environmental monitoring while minimizing ecological impact.

Deep-Learning-Based Analysis of Electronic Skin Sensing Data

E-skin is an integrated electronic system that can mimic the perceptual ability of human skin. Traditional analysis methods struggle to handle complex e-skin data, which include time series and multiple patterns, especially when dealing with intricate signals and real-time responses. Recently, deep learning techniques, such as the convolutional neural network, recurrent neural network, and transformer methods, provide effective solutions that can automatically extract data features and recognize patterns, significantly improving the analysis of e-skin data. Deep learning is not only capable of handling multimodal data but can also provide real-time response and personalized predictions in dynamic environments. Nevertheless, problems such as insufficient data annotation and high demand for computational resources still limit the application of e-skin. Optimizing deep learning algorithms, improving computational efficiency, and exploring hardware-algorithm co-designing will be the key to future development. This review aims to present the deep learning techniques applied in e-skin and provide inspiration for subsequent researchers. We first summarize the sources and characteristics of e-skin data and review the deep learning models applicable to e-skin data and their applications in data analysis. Additionally, we discuss the use of deep learning in e-skin, particularly in health monitoring and human-machine interactions, and we explore the current challenges and future development directions.

Ultrathin and capacity-tunable lithium metal wires for lithium-based fiber batteries

Ultrathin lithium (Li) metal wires with tunable capacities have great promise for precise prelithiation of fiber anodes and high-energy-density Li-based fiber batteries. However, the application of Li metal in fiber batteries faces great challenges due to its mechanical fragility and the resulting limited micro-dimension manufacturing capability. These challenges impede the production of ultrathin Li wires with adjustable Li contents to match the capacities of Li-based fiber batteries. Herein, silver-plated aramid yarns (Ag/AYs) are employed to load Li metal for producing ultrathin Li wires. The bundled structure of Ag/AYs leads to the adjustable volume of oriented voids within the fibers, thus resulting in accurately tunable capacities (0.0048-2.4 mAh cm-1) and diameters (20-534 μm) of Li wires. Such thin Li wires are used to precisely compensate for Li loss during the formation cycle of the fiber graphite anodes, thereby improving the initial Coulombic efficiency from ∼88% to ∼100%. Additionally, when employed as anodes, these Li wires enabled the fiber batteries to exhibit exceptional cycling stability for 150 cycles under a relatively low negative/positive ratio of 2.06, while achieving a high energy density of 139.822 Wh kg-1 based on the total mass of the battery.

Biomaterials for reliable wearable health monitoring: Applications in skin and eye integration

Recent advancements in biomaterials have significantly impacted wearable health monitoring, creating opportunities for personalized and non-invasive health assessments. These developments address the growing demand for customized healthcare solutions. Durability is a critical factor for biomaterials in wearable applications, as they must withstand diverse wearing conditions effectively. Therefore, there is a heightened focus on developing biomaterials that maintain robust and stable functionalities, essential for advancing wearable sensing technologies. This review examines the biomaterials used in wearable sensors, specifically those interfaced with human skin and eyes, highlighting essential strategies for achieving long-lasting and stable performance. We specifically discuss three main categories of biomaterials-hydrogels, fibers, and hybrid materials-each offering distinct properties ideal for use in durable wearable health monitoring systems. Moreover, we delve into the latest advancements in biomaterial-based sensors, which hold the potential to facilitate early disease detection, preventative interventions, and tailored healthcare approaches. We also address ongoing challenges and suggest future directions for research on material-based wearable sensors to encourage continuous innovation in this dynamic field.

Full-fiber triboelectric nanogenerators with knitted origami structures for high impact resistance intelligent protection fabric

Next-generation fabrics with excellent protection and intelligent sensing abilities will be beneficial to protect the elderly from accidents, as the ageing population will be a global challenge in the next decade. However, for widely used techniques such as fabric coating and multi-layer compositing, maintaining a balance between comfortability, stable anti-impact protection, and multi-function such as intelligent monitoring remains elusive. Herein, a full-fiber composite yarn with triboelectric ability was developed, which was then woven into an origami-structured knitted fabric (OSKF). Due to the coaxial torsional structure, the composite yarn exhibited outstanding fracture strength (219.18 MPa). The full-fiber multi-scale structure design endowed the OSKF with significantly improved energy absorption capacity (absorbing > 85% of the applied force) and the desired self-powered sensing performance without affecting the comfortability. The OSKF also had a unique ability to respond to various hazardous situations, such as external mechanical force stimuli, cutting by a sharp object, and accidental falls. This work sheds light on a new path toward the design of next-generation smart protection wearables based on knitted fabric structure design-based full-fiber materials.

A high stretchability fiber based on a synergistic three-dimensional conductive network for wide-range strain sensing

Fiber strain sensors are promising for constructing high-performance wearable electronic devices due to their light weight, high flexibility and excellent integration. However, the conductivity of most reported fiber strain sensors is severely degraded, following deformation upon stretching, and it is still a considerable challenge to achieve both high conductivity and stretchability. Herein, we have fabricated a fiber strain sensor with high conductivity and stretchability by integrating the AgNPs into the multi-walled carbon nanotube/graphene/thermoplastic polyurethane (MWCNT/GE/TPU) fiber. The tunneling-effect dominated MWCNT/GE layer bridges separated AgNP islands, endowing conductive fibers with the integrity of conductive pathways under large strain. By means of the synergistic effect of a three-dimensional conductive network, the fiber strain sensor of AgNPs/MWCNT/GE/TPU presents not only a high conductivity of 116 S m-1, but also a wide working range of up to 600% and excellent durability (8000 stretching-releasing cycles). Remarkably, benefiting from the crack propagation on the brittle AgNP layer, the fiber strain sensor exhibits a large resistance change in the strain range of 500-600%, and thus high sensitivity with a gauge factor of 545. This fiber strain sensor can monitor human physiological signals and body movement in real-time, including pulse and joint bending, which will contribute to the development of smart textiles and next-generation wearable devices.

Stretchable and High-Performance Fibrous Sensors Based on Ionic Capacitive Sensing for Wearable Healthcare Monitoring

Electronic textiles with remarkable breathability, lightweight, and comfort hold great potential in wearable technologies and smart human-machine interfaces. Ionic capacitive sensors, leveraging the advantages of the electric double layer, offer higher sensitivity compared to traditional capacitive sensors. Current research on wearable ion-capacitive sensors has focused mainly on two-dimensional (2D) or three-dimensional (3D) device architectures, which show substantial challenges for direct integration with textiles and compromise their wearing experience on conformability and permeability. One-dimensional (1D) stretchable fiber materials serve as vital components in constructing electronic textiles, allowing for rich structural design, patterning, and device integration through mature textile techniques. Here, a stretchable functional fiber with robust mechanical and electrical performances is fabricated based on semi-solid metal and ionic polymer, which provided a high stretchability and good electrical conductivity, enabling seamless integration with textiles. Consequently, high-performance stretchable fiber sensors are developed through different device architecture designs, including pressure sensors with high sensitivity (7.21 kPa-1), fast response (60 ms/30 ms), and excellent stability, as well as strain sensors with high sensitivity (GF = 1.05), wide detection range (0-300% strain), and excellent sensing stability under dynamic deformations.

Cationic chitosan enables eutectogels with high ionic conductivity for multifunctional applications in energy harvesting and storage

Eutectogels are popular as an emerging material in the field of flexible electronics. However, limited mechanical properties and ionic conductivity restrict their multifunctional application expansion. Herein, cationic chitosan quaternary ammonium salt (CQS) was evenly embedded into the three-dimensional porous framework of eutectogel to build ion migration channels. And a simple solvent replacement process enhanced the crystallization of polyvinyl alcohol matrix and hydrogen bonding, preparing composite eutectogels with high toughness, environmental tolerance and conductivity. The prepared gel exhibites excellent mechanical properties (1.72 MPa, 413 %) and conductivity (0.40 S·m-1). Under external force, three-dimensional porous network with cationic polysaccharide distribution can achieve effective piezoionic effect. Moderate CQS significantly enhances the piezoionic voltage output to 270 mV, which is 4.5 times that of the pure eutectogel. Further, the prepared composite eutectogels was used for capacitor energy storage and wearable sensing devices, and has good charge/discharge stability (94 % capacitance retention) and fast response time (292 ms). This design is typically suitable for preparing advanced multifunctional ion conductors using various natural polysaccharides with sustainable application potential.

Evaluating a Smart Textile Loneliness Monitoring System for Older People: Co-Design and Qualitative Focus Group Study

BACKGROUND

Previous studies have explored how sensor technologies can assist in in the detection, recognition, and prevention of subjective loneliness. These studies have shown a correlation between physiological and behavioral sensor data and the experience of loneliness. However, little research has been conducted on the design requirements from the perspective of older people and stakeholders in technology development. The use of these technologies and infrastructural questions have been insufficiently addressed. Systems generally consist of sensors or software installed in smartphones or homes. However, no studies have attempted to use smart textiles, which are fabrics with integrated electronics.

OBJECTIVE

This study aims to understand the design requirements for a smart textile loneliness monitoring system from the perspectives of older people and stakeholders.

METHODS

We conducted co-design workshops with 5 users and 6 stakeholders to determine the design requirements for smart textile loneliness monitoring systems. We derived a preliminary product concept of the smart wearable and furniture system. Digital and physical models and a use case were evaluated in a focus group study with older people and stakeholders (n=7).

RESULTS

The results provided insights for designing systems that use smart textiles to monitor loneliness in older people and widen their use. The findings informed the general system, wearables and furniture, materials, sensor positioning, washing, sensor synchronization devices, charging, intervention, and installation and maintenance requirements. This study provided the first insight from a human-centered perspective into smart textile loneliness monitoring systems for older people.

CONCLUSIONS

We recommend more research on the intervention that links to the monitored loneliness in a way that addresses different needs to ensure its usefulness and value to people. Future systems must also reflect on questions of identification of system users and the available infrastructure and life circumstances of people. We further found requirements that included user cooperation, compatibility with other worn medical devices, and long-term durability.

Scale Production of a Stretchable Fiber Triboelectric Nanogenerator in Customizable Textile for Human Motion Recognition

Although the fiber-based triboelectric nanogenerator (F-TENG) has been recognized as one of the most promising flexible sensor systems, it is facing a challenge of balancing the performance and the processing scalability. Herein, we develop a hierarchical coaxial F-TENG possessing PU layer, Ag layer, and PA layer from the core to the outer part by an efficient and straightforward two-step braiding method. Owning a small diameter of 1 mm, the F-TENG presents a high linear sensing response, a wide working range of 5 to 150 kPa, and a quick reaction speed of around 200 ms. In addition, it shows high flexibility, cyclic washability, and superior mechanical stability. Furthermore, customizable textiles (e.g., wrist support and socks) that conform perfectly to the human body have been knitted from the F-TENGs as warps or wefts, which are able to monitor human motion signals. Together with an optimized machine learning algorithm, five human motions (stand, slow walk, normal walk, run, and jump) can be analyzed with a precision of up to 99%. In short, this work presents a scalable approach to develop customizable self-powered sensing textiles, offering an excellent wearable digital platform/system for potential motion capture/monitoring, identification, and smart-sports-related applications.

Bioinspired Artificial Intelligent Nociceptive Alarm System Based on Fibrous Biomemristors

With the advancement of modern medical and brain-computer interface devices, flexible artificial nociceptors with tactile perception hold significant scientific importance and exhibit great potential in the fields of wearable electronic devices and biomimetic robots. Here, a bioinspired artificial intelligent nociceptive alarm system integrating sensing monitoring and transmission functions is constructed using a silk fibroin (SF) fibrous memristor. This memristor demonstrates high stability, low operating power, and the capability to simulate synaptic plasticity. As a result, an artificial pressure nociceptor based on the SF fibrous memristor can detect both fast and chronic pain and provide a timely alarm in the event of a fall or prolonged immobility of the carrier. Further, an array of artificial pressure nociceptors not only monitors the pressure distribution across various parts of the carrier but also provides direct feedback on the extent of long-term pressure to the carrier. This work holds significant implications for medical support in biological carriers or targeted maintenance of electronic carriers.

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.

Toward an AI Era: Advances in Electronic Skins

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

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

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

In-Sensor Tactile Fusion and Logic for Accurate Intention Recognition

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

Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities

Continuous monitoring of lower extremity muscles is necessary, as the muscles support many human daily activities, such as maintaining balance, standing, walking, running, and jumping. However, conventional electromyography and physiological cross-sectional area methods inherently encounter obstacles when acquiring precise and real-time data pertaining to human bodies, with a notable lack of consideration for user comfort. Benefitting from the fast development of various fabric-based sensors, this paper addresses these current issues by designing an integrated smart compression stocking system, which includes compression garments, fabric-embedded capacitive pressure sensors, an edge control unit, a user mobile application, and cloud backend. The pipeline architecture design and component selection are discussed in detail to illustrate a comprehensive user-centered STIMES design. Twelve healthy young individuals were recruited for clinical experiments to perform maximum voluntary isometric ankle plantarflexion contractions. All data were simultaneously collected through the integrated smart compression stocking system and a muscle force measurement system (Humac NORM, software version HUMAC2015). The obtained correlation coefficients above 0.92 indicated high linear relationships between the muscle torque and the proposed system readout. Two-way ANOVA analysis further stressed that different ankle angles (p = 0.055) had more important effects on the results than different subjects (p = 0.290). Hence, the integrated smart compression stocking system can be used to monitor the muscle force of the lower extremities in isometric mode.

Highly Sensitive Fiber Crossbar Sensors Enabled by Second-Order Synergistic Effect of Air Capacitance and Equipotential Body

Fiber crossbars, an emerging electronic device, have become the most promising basic unit for advanced smart textiles. The demand for highly sensitive fiber crossbar sensors (FCSs) in wearable electronics is increased. However, the unique structure of FCSs presents challenges in replicating existing sensitivity enhancement strategies. Aiming at the sensitivity of fiber crossbar sensors, a second-order synergistic strategy is proposed that combines air capacitance and equipotential bodies, resulting in a remarkable sensitivity enhancement of over 20 times for FCSs. This strategy offers a promising avenue for the design and fabrication of FCSs that do not depend on intricate microstructures. Furthermore, the integrative structure of core-sheath fibers ensures a robust interface, leading to a low hysteresis of only 2.33% and exceptional stability. The outstanding capacitive response performance of FCSs allows them to effectively capture weak signals such as pulses and sounds. This capability opens up possibilities for the application of FCSs in personalized health management, as demonstrated by wireless monitoring systems based on pulse signals.

In-situ forming ultra-mechanically sensitive materials for high-sensitivity stretchable fiber strain sensors

Fiber electronics with flexible and weavable features can be easily integrated into textiles for wearable applications. However, due to small sizes and curved surfaces of fiber materials, it remains challenging to load robust active layers, thus hindering production of high-sensitivity fiber strain sensors. Herein, functional sensing materials are firmly anchored on the fiber surface in-situ through a hydrolytic condensation process. The anchoring sensing layer with robust interfacial adhesion is ultra-mechanically sensitive, which significantly improves the sensitivity of strain sensors due to the easy generation of microcracks during stretching. The resulting stretchable fiber sensors simultaneously possess an ultra-low strain detection limit of 0.05%, a high stretchability of 100%, and a high gauge factor of 433.6, giving 254-folds enhancement in sensitivity. Additionally, these fiber sensors are soft and lightweight, enabling them to be attached onto skin or woven into clothes for recording physiological signals, e.g. pulse wave velocity has been effectively obtained by them. As a demonstration, a fiber sensor-based wearable smart healthcare system is designed to monitor and transmit health status for timely intervention. This work presents an effective strategy for developing high-performance fiber strain sensors as well as other stretchable electronic devices.

Electrostatic Smart Textiles for Braille-To-Speech Translation

A wearable Braille-to-speech translation system is of great importance for providing auditory feedback in assisting blind people and people with speech impairment. However, previous reported Braille-to-speech translation systems still need to be improved in terms of comfortability or integration. Here, a Braille-to-speech translation system that uses dual-functional electrostatic transducers which are made of fabric-based materials and can be integrated into textiles is reported. Based on electrostatic induction, the electrostatic transducer can either serve as a tactile sensor or a loudspeaker with the same design. The proposed electrostatic transducers have excellent output performances, mechanical robustness, and working stability. By combining the devices with machine learning algorithms, it is possible to translate the Braille alphabet and 40 commonly used words (extensible) into speech with an accuracy of 99.09% and 97.08%, respectively. This work demonstrates a new approach for further developments of advanced assistive technology toward improving the lives of disabled people.

Triboelectric micro-flexure-sensitive fiber electronics

Developing fiber electronics presents a practical approach for establishing multi-node distributed networks within the human body, particularly concerning triboelectric fibers. However, realizing fiber electronics for monitoring micro-physiological activities remains challenging due to the intrinsic variability and subtle amplitude of physiological signals, which differ among individuals and scenarios. Here, we propose a technical approach based on a dynamic stability model of sheath-core fibers, integrating a micro-flexure-sensitive fiber enabled by nanofiber buckling and an ion conduction mechanism. This scheme enhances the accuracy of the signal transmission process, resulting in improved sensitivity (detectable signal at ultra-low curvature of 0.1 mm-1; flexure factor >21.8% within a bending range of 10°.) and robustness of fiber under micro flexure. In addition, we also developed a scalable manufacturing process and ensured compatibility with modern weaving techniques. By combining precise micro-curvature detection, micro-flexure-sensitive fibers unlock their full potential for various subtle physiological diagnoses, particularly in monitoring fiber upper limb muscle strength for rehabilitation and training.

Wearable and interactive multicolored photochromic fiber display

Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent, wearable interactive devices. However, significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight hardware. Here, we introduce a mass-produced, wearable, and interactive photochromic fiber that provides uniform multicolored light control. We designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the fiber. The impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission direction. In addition, we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single fiber. We prepared fibers on mass-produced kilometer-long using the thermal drawing method. The fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as needed. This work provides a new perspective and inspiration to the existing field of fiber display interaction, paving the way for future human-machine integration.

Materials-Driven Soft Wearable Bioelectronics for Connected Healthcare

In the era of Internet-of-things, many things can stay connected; however, biological systems, including those necessary for human health, remain unable to stay connected to the global Internet due to the lack of soft conformal biosensors. The fundamental challenge lies in the fact that electronics and biology are distinct and incompatible, as they are based on different materials via different functioning principles. In particular, the human body is soft and curvilinear, yet electronics are typically rigid and planar. Recent advances in materials and materials design have generated tremendous opportunities to design soft wearable bioelectronics, which may bridge the gap, enabling the ultimate dream of connected healthcare for anyone, anytime, and anywhere. We begin with a review of the historical development of healthcare, indicating the significant trend of connected healthcare. This is followed by the focal point of discussion about new materials and materials design, particularly low-dimensional nanomaterials. We summarize material types and their attributes for designing soft bioelectronic sensors; we also cover their synthesis and fabrication methods, including top-down, bottom-up, and their combined approaches. Next, we discuss the wearable energy challenges and progress made to date. In addition to front-end wearable devices, we also describe back-end machine learning algorithms, artificial intelligence, telecommunication, and software. Afterward, we describe the integration of soft wearable bioelectronic systems which have been applied in various testbeds in real-world settings, including laboratories that are preclinical and clinical environments. Finally, we narrate the remaining challenges and opportunities in conjunction with our perspectives.

Biomimetic, knittable aerogel fiber for thermal insulation textile

Aerogels have been considered as an ideal material for thermal insulation. Unfortunately, their application in textiles is greatly limited by their fragility and poor processability. We overcame these issues by encapsulating the aerogel fiber with a stretchable layer, mimicking the core-shell structure of polar bear hair. Despite its high internal porosity over 90%, our fiber is stretchable up to 1000% strain, which is greatly improved compared with that of traditional aerogel fibers (~2% strain). In addition to its washability and dyeability, our fiber is mechanically robust, retaining its stable thermal insulation property after 10,000 stretching cycles (100% strain). A sweater knitted with our fiber was only one-fifth as thick as down, with similar performance. Our strategy for this fiber provides rich possibilities for developing multifunctional aerogel fibers and textiles.

Highly Sensitive Capacitive Fiber Pressure Sensors Enabled by Electrode and Dielectric Layer Regulation

Capacitive pressure sensors play an important role in the field of flexible electronics. Despite significant advances in two-dimensional (2D) soft pressure sensors, one-dimensional (1D) fiber electronics are still struggling. Due to differences in structure, the theoretical research of 2D sensors has difficulty guiding the design of 1D sensors. The multiple response factors of 1D sensors and the capacitive response mechanism have not been explored. Fiber sensors urgently need a tailor-made theoretical research and development path. In this regard, we established a fiber pressure-sensing platform using a coaxial wet spinning process. Aiming at the two problems of the soft electrode modulus and dielectric layer thickness, the conclusions are drawn from three aspects: model analysis, experimental verification, and formula derivation. It makes up some theoretical blanks of capacitive fiber pressure sensors. Through the self-regulation of these two factors without a complex structural design, the sensitivity can be significantly improved. This provides a great reference for the design and development of fiber pressure sensors. Besides, taking advantage of the scalability and easy integration of 1D electronics, multipoint sensors prepared by fibers have verified their application potential in health monitoring, human-machine interface, and motion behavior analysis.

High-Sensitivity Self-Powered Photodetector Fibers Using Hierarchical Heterojunction Photoelectrodes Enable Wearable Amphibious Optoelectronic Textiles

Fiber-shaped photodetectors (FPDs) with multidirectional light absorption properties offer exciting opportunities for intelligent optoelectronic textiles. However, achieving FPDs capable of working in ampule environments, especially with high sensitivity, remains a fundamental challenge. Here, quasi-solid-state twisted-fiber photoelectrochemical photodetectors (FPPDs) consisting of photoanode, gel electrolyte, and counter electrode are successfully assembled. In situ decorated n-type one-dimensional (1D) TiO2 nanowire arrays with 2D Ni-Fe metal-organic framework (NiFeMOF) nanosheets serve as hierarchical heterojunction photoanodes, thereby optimizing carrier transfer dynamics at the photoanode/electrolyte interface. As expected, the resulting self-powered FPPD exhibits 88.6 mA W-1 high responsiveness and a < 30 ms fast response time. Significantly, our FPPD can operate in both terrestrial and aquatic environments thanks to its intrinsic ionic properties, making it a versatile tool for detecting ultraviolet light on land and facilitating optical communication underwater. These high-sensitivity self-powered FPPDs with hierarchical heterojunction photoelectrodes hold promise for the development of wearable amphibious optoelectronic textiles.

Fluorescent Fiber-Shaped Aqueous Zinc-Ion Batteries for Bifunctional Multicolor-Emission/Energy-Storage Textiles

Wearable smart textiles are natural carriers to enable imperceptible and highly permeable sensing and response to environmental conditions via the system integration of multiple functional fibers. However, the existing massive interfaces between different functional fibers significantly increase the complexity and reduce the wearability of the textile system. Thus, it is significant yet challenging to achieve all-in-one multifunctional fibers for realizing miniaturized and lightweight smart textiles with high reliability. Herein, as bifunctional electrolyte additives, fluorescent carbon dots with abundant zincophilic functional groups are introduced into electrolytes to develop fluorescent fiber-shaped aqueous zinc-ion batteries (FFAZIBs). Originating from effective dendrite suppression of Zn anodes and multiple active sites of freestanding Prussian blue cathodes, high energy density (0.17 Wh·cm-3) and long-term cyclability (78.9% capacity retention after 1500 cycles) are achieved for FFAZIBs. More importantly, the one-dimensional structure ensures the same luminance in all directions of FFAZIBs, enabling the form of multicolor display-in-battery textiles.

Highly Sensitive Fiber Pressure Sensors over a Wide Pressure Range Enabled by Resistive-Capacitive Hybrid Response

Soft capacitive pressure sensors with high performance are becoming increasingly in demand in the emerging flexible wearable field. While capacitive fiber pressure sensors have achieved high sensitivity, their sensitivity range is limited to low-pressure levels. As fiber sensors typically require preloading and fixation, this narrow range of high sensitivity poses a challenge for practical applications. To overcome this limitation, the study proposes resistive-capacitive hybrid response fiber pressure sensors (HFPSs) with three-layer core-sheath structures. The trigger and sensitivity enhancement mechanisms of the hybrid response are determined through model analysis and experimental verification. By adjustment of the sensitivity enhancement range of the hybrid response, the sensitivity attenuation of HFPSs is alleviated significantly. The obtained results demonstrate that HFPSs have excellent characteristics such as fast response, low hysteresis, wide response frequency, small signal drift, and good durability. The hybrid response enhances the practical sensitivity of HFPSs for various applications. With enhanced sensitivity, HFPSs can effectively monitor pulse signals at preloads ranging from 0 to 22.7 kPa. This wide range of preloads improves the fault tolerance of pulse monitoring and expands the potential application scenarios of fiber pressure sensors.