A Deep-Learning-Assisted On-Mask Sensor Network for Adaptive Respiratory Monitoring

Neuromorphic Computing-Assisted Triboelectric Capacitive-Coupled Tactile Sensor Array for Wireless Mixed Reality Interaction

Flexible tactile sensors show promise for artificial intelligence applications due to their biological adaptability and rapid signal perception. Triboelectric sensors enable active dynamic tactile sensing, while integrating static pressure sensing and real-time multichannel signal transmission is key for further development. Here, we propose an integrated structure combining a capacitive sensor for static spatiotemporal mapping and a triboelectric sensor for dynamic tactile recognition. A liquid metal-based flexible dual-mode triboelectric-capacitive-coupled tactile sensor (TCTS) array of 4 × 4 pixels achieves a spatial resolution of 7 mm, exhibiting a pressure detection limit of 0.8 Pa and a fast response of 6 ms. Furthermore, neuromorphic computing using the MXene-based synaptic transistor achieves 100% recognition accuracy of handwritten numbers/letters within 90 epochs based on dynamic triboelectric signals collected by the TCTS array, and cross-spatial information communication from the perceived multichannel tactile data is realized in the mixed reality space. The results illuminate considerable application possibilities of dual-mode tactile sensing technology in human-machine interfaces and advanced robotics.

Development of Bio-Voltage Operated Humidity-Sensory Neurons Comprising Self-Assembled Peptide Memristors

Biomimetic humidity sensors offer a low-power approach for respiratory monitoring in early lung-disease diagnosis. However, balancing miniaturization and energy efficiency remains challenging. This study addresses this issue by introducing a bioinspired humidity-sensing neuron comprising a self-assembled peptide nanowire (NW) memristor with unique proton-coupled ion transport. The proposed neuron shows a low Ag+ activation energy owing to the NW and redox activity of the tyrosine (Tyr)-rich peptide in the system, facilitating ultralow electric-field-driven threshold switching and a high energy efficiency. Additionally, Ag+ migration in the system can be controlled by a proton source owing to the hydrophilic nature of the phenolic hydroxyl group in Tyr, enabling the humidity-based control of the conductance state of the memristor. Furthermore, a memristor-based neuromorphic perception neuron that can encode humidity signals into spikes is proposed. The spiking characteristics of this neuron can be modulated to emulate the strength-modulated spike-frequency characteristics of biological neurons. A three-layer spiking neural network with input neurons comprising these highly tunable humidity perception neurons shows an accuracy of 92.68% in lung-disease diagnosis. This study paves the way for developing bioinspired self-assembly strategies to construct neuromorphic perception systems, bridging the gap between artificial and biological sensing and processing paradigms.

Advanced Applications of Porous Materials in Triboelectric Nanogenerator Self-Powered Sensors

Porous materials possess advantages such as rich pore structures, a large surface area, low relative density, high specific strength, and good breathability. They have broad prospects in the development of a high-performance Triboelectric Nanogenerator (TENG) and self-powered sensing fields. This paper elaborates on the structural forms and construction methods of porous materials in existing TENG, including aerogels, foam sponges, electrospinning, 3D printing, and fabric structures. The research progress of porous materials in improving TENG performance is systematically summarized, with a focus on discussing design strategies of porous structures to enhance the TENG mechanical performance, frictional electrical performance, and environmental tolerance. The current applications of porous-material-based TENG in self-powered sensing such as pressure sensing, health monitoring, and human-machine interactions are introduced, and future development directions and challenges are discussed.

Displacement-pressure biparametrically regulated softness sensory system for intraocular pressure monitoring

High intraocular pressure (IOP) is one of the high-risk pathogenic factors of glaucoma. Existing methods of IOP measurement are based on the direct interaction with the cornea. Commercial ophthalmic tonometers based on snapshot measurements are expensive, bulky, and their operation requires trained personnel. Theranostic contact lenses are easy to use, but they may block vision and cause infection. Here, we report a sensory system for IOP assessment that uses a soft indentor with two asymmetrically deployed iontronic flexible pressure sensors to interact with the eyelid-eyeball in an eye-closed situation. Inspired by human fingertip assessment of softness, the sensory system extracts displacement-pressure information for soft evaluation, achieving high accuracy IOP monitoring (>96%). We further design and custom-make a portable and wearable ophthalmic tonometer based on the sensory system and demonstrate its high efficacy in IOP screening. This sensory system paves a way towards cost-effective, robust, and reliable IOP monitoring.

Emerging Trends of Nanofibrous Piezoelectric and Triboelectric Applications: Mechanisms, Electroactive Materials, and Designed Architectures

Over the past few decades, significant progress in piezo-/triboelectric nanogenerators (PTEGs) has led to the development of cutting-edge wearable technologies. Nanofibers with good designability, controllable morphologies, large specific areas, and unique physicochemical properties provide a promising platform for PTEGs for various advanced applications. However, the further development of nanofiber-based PTEGs is limited by technical difficulties, ranging from materials design to device integration. Herein, the current developments in PTEGs based on electrospun nanofibers are systematically reviewed. This review begins with the mechanisms of PTEGs and the advantages of nanofibers and nanodevices, including high breathability, waterproofness, scalability, and thermal-moisture comfort. In terms of materials and structural design, novel electroactive nanofibers and structure assemblies based on 1D micro/nanostructures, 2D bionic structures, and 3D multilayered structures are discussed. Subsequently, nanofibrous PTEGs in applications such as energy harvesters, personalized medicine, personal protective equipment, and human-machine interactions are summarized. Nanofiber-based PTEGs still face many challenges such as energy efficiency, material durability, device stability, and device integration. Finally, the research gap between research and practical applications of PTEGs is discussed, and emerging trends are proposed, providing some ideas for the development of intelligent wearables.

Permeable Bioelectronics toward Biointegrated Systems

Bioelectronics integrates electronics with biological organs, sustaining the natural functions of the organs. Organs dynamically interact with the external environment, managing internal equilibrium and responding to external stimuli. These interactions are crucial for maintaining homeostasis. Additionally, biological organs possess a soft and stretchable nature; encountering objects with differing properties can disrupt their function. Therefore, when electronic devices come into contact with biological objects, the permeability of these devices, enabling interactions and substance exchanges with the external environment, and the mechanical compliance are crucial for maintaining the inherent functionality of biological organs. This review discusses recent advancements in soft and permeable bioelectronics, emphasizing materials, structures, and a wide range of applications. The review also addresses current challenges and potential solutions, providing insights into the integration of electronics with biological organs.

Highly efficient microbial inactivation enabled by tunneling charges injected through two-dimensional electronics

Airborne pathogens retain prolonged infectious activity once attached to the indoor environment, posing a pervasive threat to public health. Conventional air filters suffer from ineffective inactivation of the physics-separated microorganisms, and the chemical-based antimicrobial materials face challenges of poor stability/efficiency and inefficient viral inactivation. We, therefore, developed a rapid, reliable antimicrobial method against the attached indoor bacteria/viruses using a large-scale tunneling charge-motivated disinfection device fabricated by directly dispersing monolayer graphene on insulators. Free charges can be stably immobilized under the monolayer graphene through the tunneling effect. The stored charges can motivate continuous electron loss of attached microorganisms for accelerated disinfection, overcoming the diffusion limitation of chemical disinfectants. Complete (>99.99%) and broad-spectrum disinfection was achieved <1 min of attachment to the scaled-up device (25 square centimeters), reliably for 72 hours at high temperature (60°C) and humidity (90%). This method can be readily applied to high-touch surfaces in indoor environments for pathogen control.

All-in-One Self-Powered Microneedle Device for Accelerating Infected Diabetic Wound Repair

Diabetic wound healing remains a significant clinical challenge due to the complex microenvironment and attenuated endogenous electric field. Herein, a novel all-in-one self-powered microneedle device (termed TZ@mMN-TENG) is developed by combining the multifunctional microneedle carried tannin@ZnO microparticles (TZ@mMN) with the self-powered triboelectric nanogenerator (TENG). In addition to the delivery of tannin and Zn2+, TZ@mMN also effectively conducts electrical stimulation (ES) to infected diabetic wounds. As a self-powered device, the TENG can convert biomechanical motion into exogenous ES to accelerate the infected diabetic wound healing. In vitro experiment demonstrated that TZ@mMN shows excellent conductive, high antioxidant ability, and effective antibacterial properties against both Staphylococcus aureus and Escherichia coli (>99% antibacterial rates). Besides, the TZ@mMN-TENG can effectively promote cell proliferation and migration. In the diabetic rat full-thickness skin wound model infected with Staphylococcus aureus, the TZ@mMN-TENG can eliminate bacteria, accelerate epidermal growth (regenerative epidermis: ≈303.3 ± 19.1 µm), enhance collagen deposition, inhibit inflammation (lower TNF-α and IL-6 expression), and promote angiogenesis (higher CD31 and VEGF expression) to accelerate infected wound repair. Overall, the TZ@mMN-TENG provides a promising strategy for clinical application in diabetic wound repair.

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.

Advanced Dielectric Materials for Triboelectric Nanogenerators: Principles, Methods, and Applications

Triboelectric nanogenerator (TENG) manifests distinct advantages such as multiple structural selectivity, diverse selection of materials, environmental adaptability, low cost, and remarkable conversion efficiency, which becomes a promising technology for micro-nano energy harvesting and self-powered sensing. Tribo-dielectric materials are the fundamental and core components for high-performance TENGs. In particular, the charge generation, dissipation, storage, migration of the dielectrics, and dynamic equilibrium behaviors determine the overall performance. Herein, a comprehensive summary is presented to elucidate the dielectric charge transport mechanism and tribo-dielectric material modification principle toward high-performance TENGs. The contact electrification and charge transport mechanism of dielectric materials is started first, followed by introducing the basic principle and dielectric materials of TENGs. Subsequently, modification mechanisms and strategies for high-performance tribo-dielectric materials are highlighted regarding physical/chemical, surface/bulk, dielectric coupling, and structure optimization. Furthermore, representative applications of dielectric materials based TENGs as power sources, self-powered sensors are demonstrated. The existing challenges and promising potential opportunities for advanced tribo-dielectric materials are outlined, guiding the design, fabrication, and applications of tribo-dielectric materials.

Flexible Antibacterial Respiratory Monitoring Sensor Based on Controllable Au-Modified Surface of Highly {001} Preferred Anatase Titanium Dioxide Thin Film

Respiratory signals are critical clinical diagnostic criteria for respiratory diseases and health conditions, and respiratory sensors play a crucial role in achieving the desired respiratory monitoring effect. High sensitivity to a single factor can improve the reliability of respiratory monitoring, and maintaining the hygiene of the sensors is also important for daily health monitoring. Herein, we propose a flexible Au-modified anatase titanium dioxide resistive respiratory sensor, which can be mechanically compliantly attached to curved surfaces for respiratory monitoring in different modalities (i.e., respiratory intensity, frequency, and rate). The uniform and preferentially oriented anatase titanium dioxide films gained by the polymer-assisted deposition technique can be fabricated on flexible substrates through a liquid-assisted transferring process. The Au modification can enhance surface plasmon resonance to facilitate the photocatalytic activity of titanium dioxide, and the optimized distribution of Au on the surface of titanium dioxide film made the sensor have an excellent antibacterial effect. The uniquely designed encapsulation can effectively control the contact between the surface of titanium dioxide films and electrodes, allowing the flexible sensor to exhibit fast response time (0.71 s) and recovery time (1.06 s) to respiratory as well as insensitivity or low sensitivity to other factors (i.e., gas composition, humidity, temperature, stress, and strain). This work provided an effective strategy for flexible wearable respiratory sensors and has great potential in daily respiratory monitoring for health management and pandemic control.

A high altitude respiration and SpO2 dataset for assessing the human response to hypoxia

This report presents the Harespod dataset, an open dataset for high altitude hypoxia research, which includes respiration and SpO2 data. The dataset was collected from 15 college students aged 23-31 in a hypobaric oxygen chamber, during simulated altitude changes and induced hypoxia. Real-time physiological data, such as oxygen saturation waveforms, oxygen saturation, respiratory waveforms, heart rate, and pulse rate, were obtained at 100 Hz. Approximately 12 hours of valid data were collected from all participants. Researchers can easily identify the altitude corresponding to physiological signals based on their inherent patterns. Time markers were also recorded during altitude changes to facilitate realistic annotation of physiological signals and analysis of time-difference-of-arrival between various physiological signals for the same altitude change event. In high altitude scenarios, this dataset can be used to enhance the detection of human hypoxia states, predict respiratory waveforms, and develop related hardware devices. It will serve as a valuable and standardized resource for researchers in the field of high altitude hypoxia research, enabling comprehensive analysis and comparison.

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

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

Flexible Metasurfaces for Multifunctional Interfaces

Optical metasurfaces, capable of manipulating the properties of light with a thickness at the subwavelength scale, have been the subject of extensive investigation in recent decades. This research has been mainly driven by their potential to overcome the limitations of traditional, bulky optical devices. However, most existing optical metasurfaces are confined to planar and rigid designs, functions, and technologies, which greatly impede their evolution toward practical applications that often involve complex surfaces. The disconnect between two-dimensional (2D) planar structures and three-dimensional (3D) curved surfaces is becoming increasingly pronounced. In the past two decades, the emergence of flexible electronics has ushered in an emerging era for metasurfaces. This review delves into this cutting-edge field, with a focus on both flexible and conformal design and fabrication techniques. Initially, we reflect on the milestones and trajectories in modern research of optical metasurfaces, complemented by a brief overview of their theoretical underpinnings and primary classifications. We then showcase four advanced applications of optical metasurfaces, emphasizing their promising prospects and relevance in areas such as imaging, biosensing, cloaking, and multifunctionality. Subsequently, we explore three key trends in optical metasurfaces, including mechanically reconfigurable metasurfaces, digitally controlled metasurfaces, and conformal metasurfaces. Finally, we summarize our insights on the ongoing challenges and opportunities in this field.

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.

Synergizing Machine Learning Algorithm with Triboelectric Nanogenerators for Advanced Self-Powered Sensing Systems

The advancement of the Internet of Things (IoT) has increased the demand for large-scale intelligent sensing systems. The periodic replacement of power sources for ubiquitous sensing systems leads to significant resource waste and environmental pollution. Human staffing costs associated with replacement also increase the economic burden. The triboelectric nanogenerators (TENGs) provide both an energy harvesting scheme and the possibility of self-powered sensing. Based on contact electrification from different materials, TENGs provide a rich material selection to collect complex and diverse data. As the data collected by TENGs become increasingly numerous and complex, different approaches to machine learning (ML) and deep learning (DL) algorithms have been proposed to efficiently process output signals. In this paper, the latest advances in ML algorithms assisting solid-solid TENG and liquid-solid TENG sensors are reviewed based on the sample size and complexity of the data. The pros and cons of various algorithms are analyzed and application scenarios of various TENG sensing systems are presented. The prospects of synergizing hardware (TENG sensors) with software (ML algorithms) in a complex environment and their main challenges for future developments are discussed.

Fully Integrated Patch Based on Lamellar Porous Film Assisted GaN Optopairs for Wireless Intelligent Respiratory Monitoring

Respiratory pattern is one of the most crucial indicators for accessing human health, but there has been limited success in implementing fast-responsive, affordable, and miniaturized platforms with the capability for smart recognition. Herein, a fully integrated and flexible patch for wireless intelligent respiratory monitoring based on a lamellar porous film functionalized GaN optoelectronic chip with a desirable response to relative humidity (RH) variation is reported. The submillimeter-sized GaN device exhibits a high sensitivity of 13.2 nA/%RH at 2-70%RH and 61.5 nA/%RH at 70-90%RH, and a fast response/recovery time of 12.5 s/6 s. With the integration of a wireless data transmission module and the assistance of machine learning based on 1-D convolutional neural networks, seven breathing patterns are identified with an overall classification accuracy of >96%. This integrated and flexible on-mask sensing platform successfully demonstrates real-time and intelligent respiratory monitoring capability, showing great promise for practical healthcare applications.

Tracing the Flu Symptom Progression via a Smart Face Mask

Respiration and body temperature are largely influenced by the highly contagious influenza virus, which poses persistent global public health challenges. Here, we present a wireless all-in-one sensory face mask (WISE mask) made of ultrasensitive fibrous temperature sensors. The WISE mask shows exceptional thermosensitivity, excellent breathability, and wearing comfort. It offers highly sensitive body temperature monitoring and respiratory detection capabilities. Capitalizing on the advances in the Internet of Things and artificial intelligence, the WISE mask is further demonstrated by customized flexible circuitry, deep learning algorithms, and a user-friendly interface to continuously recognize the abnormalities of both the respiration and body temperature. The WISE mask represents a compelling approach to tracing flu symptom progression in a cost-effective and convenient manner, serving as a powerful solution for personalized health monitoring and point-of-care systems in the face of ongoing influenza-related public health concerns.

Advances in Bioresorbable Triboelectric Nanogenerators

With the growing demand for next-generation health care, the integration of electronic components into implantable medical devices (IMDs) has become a vital factor in achieving sophisticated healthcare functionalities such as electrophysiological monitoring and electroceuticals worldwide. However, these devices confront technological challenges concerning a noninvasive power supply and biosafe device removal. Addressing these challenges is crucial to ensure continuous operation and patient comfort and minimize the physical and economic burden on the patient and the healthcare system. This Review highlights the promising capabilities of bioresorbable triboelectric nanogenerators (B-TENGs) as temporary self-clearing power sources and self-powered IMDs. First, we present an overview of and progress in bioresorbable triboelectric energy harvesting devices, focusing on their working principles, materials development, and biodegradation mechanisms. Next, we examine the current state of on-demand transient implants and their biomedical applications. Finally, we address the current challenges and future perspectives of B-TENGs, aimed at expanding their technological scope and developing innovative solutions. This Review discusses advancements in materials science, chemistry, and microfabrication that can advance the scope of energy solutions available for IMDs. These innovations can potentially change the current health paradigm, contribute to enhanced longevity, and reshape the healthcare landscape soon.

Surface Defect Detection of Bearing Rings Based on an Improved YOLOv5 Network

Considering the characteristics of complex texture backgrounds, uneven brightness, varying defect sizes, and multiple defect types of the bearing surface images, a surface defect detection method for bearing rings is proposed based on improved YOLOv5. First, replacing the C3 module in the backbone network with a C2f module can effectively reduce the number of network parameters and computational complexity, thereby improving the speed and accuracy of the backbone network. Second, adding the SPD module into the backbone and neck networks enhances their ability to process low-resolution and small-object images. Next, replacing the nearest-neighbor upsampling with the lightweight and universal CARAFE operator fully utilizes feature semantic information, enriches contextual information, and reduces information loss during transmission, thereby effectively improving the model's diversity and robustness. Finally, we constructed a dataset of bearing ring surface images collected from industrial sites and conducted numerous experiments based on this dataset. Experimental results show that the mean average precision (mAP) of the network is 97.3%, especially for dents and black spot defects, improved by 2.2% and 3.9%, respectively, and that the detection speed can reach 100 frames per second (FPS). Compared with mainstream surface defect detection algorithms, the proposed method shows significant improvements in both accuracy and detection time and can meet the requirements of industrial defect detection.

Technology Roadmap for Flexible Sensors

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

Machine Learning-Enhanced Flexible Mechanical Sensing

To realize a hyperconnected smart society with high productivity, advances in flexible sensing technology are highly needed. Nowadays, flexible sensing technology has witnessed improvements in both the hardware performances of sensor devices and the data processing capabilities of the device's software. Significant research efforts have been devoted to improving materials, sensing mechanism, and configurations of flexible sensing systems in a quest to fulfill the requirements of future technology. Meanwhile, advanced data analysis methods are being developed to extract useful information from increasingly complicated data collected by a single sensor or network of sensors. Machine learning (ML) as an important branch of artificial intelligence can efficiently handle such complex data, which can be multi-dimensional and multi-faceted, thus providing a powerful tool for easy interpretation of sensing data. In this review, the fundamental working mechanisms and common types of flexible mechanical sensors are firstly presented. Then how ML-assisted data interpretation improves the applications of flexible mechanical sensors and other closely-related sensors in various areas is elaborated, which includes health monitoring, human-machine interfaces, object/surface recognition, pressure prediction, and human posture/motion identification. Finally, the advantages, challenges, and future perspectives associated with the fusion of flexible mechanical sensing technology and ML algorithms are discussed. These will give significant insights to enable the advancement of next-generation artificial flexible mechanical sensing.

Miniaturized retractable thin-film sensor for wearable multifunctional respiratory monitoring

As extremely important physiological indicators, respiratory signals can often reflect or predict the depth and urgency of various diseases. However, designing a wearable respiratory monitoring system with convenience, excellent durability, and high precision is still an urgent challenge. Here, we designed an easy-fabricate, lightweight, and badge reel-like retractable self-powered sensor (RSPS) with high precision, sensitivity, and durability for continuous detection of important indicators such as respiratory rate, apnea, and respiratory ventilation. By using three groups of interdigital electrode structures with phase differences, combined with flexible printed circuit boards (FPCBs) processing technology, a miniature rotating thin-film triboelectric nanogenerator (RTF-TENG) was developed. Based on discrete sensing technology, the RSPS has a sensing resolution of 0.13 mm, sensitivity of 7 P·mm-1, and durability more than 1 million stretching cycles, with low hysteresis and excellent anti-environmental interference ability. Additionally, to demonstrate its wearability, real-time, and convenience of respiratory monitoring, a multifunctional wearable respiratory monitoring system (MWRMS) was designed. The MWRMS demonstrated in this study is expected to provide a new and practical strategy and technology for daily human respiratory monitoring and clinical diagnosis.

Electronic Supplementary Material

Supplementary material (additional figures and movies, including the production process of respiratory monitoring straps, the mechanical analysis of RSPS, RTF-TENG versus vector TENG sensors, the simulation studies of TE-TENG and FT-TENG, the additional characterization of RTF-TENG, the tensile and robustness tests of RSPS, the characterizations of the MWRMS during different sleeping positions, detailed circuit schematic of the MWRMS, the displacements and phase relations of RSPS, MWRMS for multifunctional respiratory monitoring) is available in the online version of this article at 10.1007/s12274-023-5420-1.

Electrothermal sterilization and self-powered real-time respiratory monitoring of reusable mask based on Ag micro-mesh films

Since the COVID-19 pandemic outbreaks, the utilization of medical masks plays a critical role in reducing the infected risk. However, constructing multifunctional masks to achieve simultaneously self-sterilization, reusability, and respiratory monitoring capability remains still a huge challenge. Herein, a reusable Ag micro-mesh film-based mask is proposed, which enables the capabilities of electrothermal sterilization and self-powered real-time respiratory monitoring. Highly conductive Ag micro-mesh films prepared by continuous draw spinning method demonstrate excellent electrothermal performances for thermal sterilization and serve as working electrode to fabricate triboelectric nanogenerator (TENG) for real-time respiratory monitoring, respectively. Under a low driving voltage of 3.0 V, the surface temperature of Ag micro-mesh film enables a quick increase to over 60 °C within 30 s, which endows thermal sterilization against S. aureus with antibacterial efficiency of 95.58 % within 20 min to achieve the self-sterilization of medical masks. Furthermore, a self-powered alarm system based on the fabricated TENG as respiratory monitor is developed for real-time respiratory monitoring to render a timely treatment for patients in danger of tachypnea and apnea. Consequently, this work has paved a new and practical avenue to achieve reusable multifunctional masks with capabilities of electrothermal sterilization and real-time respiratory monitoring in clinical medicine.

Printable Graphene-Sustainable Elastomer-Based Cross Talk Free Sensor for Point of Care Diagnostics

Developing sensors for monitoring physiological parameters such as temperature and strain for point of care (POC) diagnostics is critical for better care of the patients. Various commercial sensors are available to get the job done; however, challenges like the structural rigidity of such sensors confine their usage. As an alternative, flexible sensors have been looked upon recently. In most cases, flexible sensors cannot discriminate the signals from different stimuli. While there have been reports on the printable sensors providing cross-talk-free solutions, research related to developing sensors from a sustainable source providing discriminability between signals is not well-explored. Herein, we report the development of a stencil printable composition made of graphene and epoxidized natural rubber. The stencil printability index was vetted using rheological studies. Post usage, the developed sensor was dissolved in an organic solvent at room temperature. This, along with the choice of a sustainable elastomer, warrants the minimization of electronic waste and carbon footprint. The developed material demonstrated good conformability with the skin and could perceive and decouple the signals from temperature and strain without inducing any crosstalks. Using a representative volume element model, a comparison between experimental findings and computation studies was made. The developed sensors demonstrated gauge factors of -506 and 407 in the bending strain regimes of 0-0.04% and 0.04%-0.09%, respectively, while the temperature sensitivity was noted to be -0.96%/°C. The printed sensors demonstrated a multifunctional sensing behavior for monitoring various active physiological parameters ranging from temperature, strain, pulse, and breathing to auditory responses. Using a Bluetooth module, various parameters like temperature and strain could be monitored seamlessly in a smart-phone. The current development would be crucial to open new avenues to fabricate crosstalk-free sensors from sustainable sources for POC diagnostics.

Elastic Fibers/Fabrics for Wearables and Bioelectronics

Wearables and bioelectronics rely on breathable interface devices with bioaffinity, biocompatibility, and smart functionality for interactions between beings and things and the surrounding environment. Elastic fibers/fabrics with mechanical adaptivity to various deformations and complex substrates, are promising to act as fillers, carriers, substrates, dressings, and scaffolds in the construction of biointerfaces for the human body, skins, organs, and plants, realizing functions such as energy exchange, sensing, perception, augmented virtuality, health monitoring, disease diagnosis, and intervention therapy. This review summarizes and highlights the latest breakthroughs of elastic fibers/fabrics for wearables and bioelectronics, aiming to offer insights into elasticity mechanisms, production methods, and electrical components integration strategies with fibers/fabrics, presenting a profile of elastic fibers/fabrics for energy management, sensors, e-skins, thermal management, personal protection, wound healing, biosensing, and drug delivery. The trans-disciplinary application of elastic fibers/fabrics from wearables to biomedicine provides important inspiration for technology transplantation and function integration to adapt different application systems. As a discussion platform, here the main challenges and possible solutions in the field are proposed, hopefully can provide guidance for promoting the development of elastic e-textiles in consideration of the trade-off between mechanical/electrical performance, industrial-scale production, diverse environmental adaptivity, and multiscenario on-spot applications.

Self-Powered Respiratory Monitoring Strategy Based on Adaptive Dual-Network Thermogalvanic Hydrogels

As a low-grade sustainable heat source, the breath waste heat exhaled by human bodies is always ignored, although producing a greater temperature than ambient. Converting this heat into electric energy for use as power sources or detecting signals is extremely important in cutting-edge wearable medicine. This heat-to-electricity conversion is possible with thermogalvanic hydrogels. However, challenges remain in their antifreezing and antidrying properties, significantly restricting the durability of thermogalvanic gels in practical applications. Herein, a dual-network poly(vinyl alcohol)/gelatin (PVA/GEL) gel thermogalvanic device with Fe(CN)₆^3-/4- as a redox pair is developed, with an outstanding low-temperature durability and antidrying capacity. These features result from the use of a binary H₂O/GL (glycerin) solvent to limit hydrogen bonding between water molecules. The prepared thermogalvanic gel patch is capable of easily converting physiological data into understandable electrical impulses using the temperature difference between the ambient environment and the heat produced by human breathing, realizing a simple self-powered respiratory monitoring strategy for the first time. Even below zero temperature, the gel patch-based mask can operate normally, implying it fits into low-temperature environments. This study sheds fresh light on the development of active wearable medical electronics that are powered by demic low-level heat.

Wearable respiratory sensors for COVID-19 monitoring

Since its outbreak in 2019, COVID-19 becomes a pandemic, severely burdening the public healthcare systems and causing an economic burden. Thus, societies around the world are prioritizing a return to normal. However, fighting the recession could rekindle the pandemic owing to the lightning-fast transmission rate of SARS-CoV-2. Furthermore, many of those who are infected remain asymptomatic for several days, leading to the increased possibility of unintended transmission of the virus. Thus, developing rigorous and universal testing technologies to continuously detect COVID-19 for entire populations remains a critical challenge that needs to be overcome. Wearable respiratory sensors can monitor biomechanical signals such as the abnormities in respiratory rate and cough frequency caused by COVID-19, as well as biochemical signals such as viral biomarkers from exhaled breaths. The point-of-care system enabled by advanced respiratory sensors is expected to promote better control of the pandemic by providing an accessible, continuous, widespread, noninvasive, and reliable solution for COVID-19 diagnosis, monitoring, and management.

Advances in Photoplethysmography for Personalized Cardiovascular Monitoring

Photoplethysmography (PPG) is garnering substantial interest due to low cost, noninvasiveness, and its potential for diagnosing cardiovascular diseases, such as cardiomyopathy, heart failure, and arrhythmia. The signals obtained through PPG can yield information based on simple analyses, such as heart rate. In contrast, when accompanied by the complex analysis of sophisticated signals, valuable information, such as blood pressure, sympathetic nervous system activity, and heart rate variability, can be obtained. For a complex analysis, a better understanding of the sources of noise, which create limitations in the application of PPG, is needed to get reliable information to assess cardiovascular health. Therefore, this Special Issue handles literature about noises and how they affect the waveform of the PPG caused by individual variations (e.g., skin tone, obesity, age, and gender), physiology (e.g., respiration, venous pulsation, body site of measurement, and body temperature), and external factors (e.g., motion artifact, ambient light, and applied pressure to the skin). It also covers the issues that still need to be considered in each situation.

Printable Carbon Nanotube-Liquid Elastomer-Based Multifunctional Adhesive Sensors for Monitoring Physiological Parameters

Developing a printed elastomeric wearable sensor with good conformity and proper adhesion to skin, coupled with the capability of monitoring various physiological parameters, is very crucial for the development of point-of-care sensing devices with high precision and sensitivity. While there have been previous reports on the fabrication of elastomeric multifunctional sensors, research on the printable elastomeric multifunctional adhesive sensor is not very well explored. Herein, we report the development of a stencil printable multifunctional adhesive sensor fabricated in a solvent-free condition, which demonstrated the capability of having good contact with skin and its ability to function as a temperature and strain sensor. Functionalized liquid isoprene rubber was selected as the matrix while carboxylated multiwalled carbon nanotubes (c-CNTs) were used as the nanofiller. The selection of the above model compounds facilitated the printability and also helped the same composition to demonstrate stretchability and adhesiveness. A realistic three-dimensional microstructure (representative volume element model) was generated through a computational framework for the current c-CNT-liquid elastomer. Further computational simulations were performed to test and validate the correlation between electrical responses to that of experimental studies. Various physiological parameters like motion sensing, pulse, respiratory rate, and phonetics detection were detected by leveraging the electrically resistive nature of the sensor. This development route can be extended toward developing different innovative adhesives for point-of-care sensing applications.

Self-Powered Smart Gloves Based on Triboelectric Nanogenerators

The hands are used in all facets of daily life, from simple tasks such as grasping and holding to complex tasks such as communication and using technology. Finding a way to not only monitor hand movements and gestures but also to integrate that data with technology is thus a worthwhile task. Gesture recognition is particularly important for those who rely on sign language to communicate, but the limitations of current vision-based and sensor-based methods, including lack of portability, bulkiness, low sensitivity, highly expensive, and need for external power sources, among many others, make them impractical for daily use. To resolve these issues, smart gloves can be created using a triboelectric nanogenerator (TENG), a self-powered technology that functions based on the triboelectric effect and electrostatic induction and is also cheap to manufacture, small in size, lightweight, and highly flexible in terms of materials and design. In this review, an overview of the existing self-powered smart gloves will be provided based on TENGs, both for gesture recognition and human-machine interface, concluding with a discussion on the future outlook of these devices.

High-Performance Strain Sensors Based on Au/Graphene Composite Films with Hierarchical Cracks for Wide Linear-Range Motion Monitoring

Stretchable strain sensors based on nanomaterial thin films have aroused extensive interest for the strain perception of smart skins. However, it still remains challenging to have them achieve high sensitivity over wide linear working ranges. Herein, we propose a facile strategy to fabricate stretchable strain sensors based on Au/graphene composite films (AGCFs) with hierarchical cracks and demonstrate their superior sensing performances. The polydimethylsiloxane substrates were covered with self-assembled graphene films (SAGFs) and sputtered with Au, and then prestretching was applied to introduce hierarchical cracks. The AGCF strain sensors exhibited high sensitivity (gauge factor (GF) ≈ 153) and favorable linearity (R² ≈ 0.9975) in the wide working range (0-20%) with ultralow overshooting (∼1.7% at 20%), fast response (<42.5 ms), and also excellent cycling stability (1500 cycles). Besides, these patternable sensors could further achieve higher GF (∼320) via pattern designing. The dominant effect of the intermediate wrinkled SAGFs in forming hierarchical cracks was studied, and the linear sensing mechanism of the as-formed fractal microstructures was also revealed in detail. Moreover, the AGCF strain sensors were tested for motion monitoring of the human body and electronic bird. Due to the remarkable versatility, scalable fabrication, and integration capability, these sensors demonstrate great potential to construct smart skins.