End-to-end design of wearable sensors

Advanced and personalized healthcare through integrated wearable sensors (versatile)

Applications of integrated wearable sensors for the monitoring of human vital signs and clinically relevant biomarkers.

Hand-held Raman spectrometer-based flexible plasmonic biosensor for label-free multiplex urinalysis

Urinalysis is an effective strategy to non-invasively evaluate human health, and surface-enhanced Raman scattering (SERS) may be a powerful technique for use in detecting analytes in urine. Herein, we report a wearable diaper sensor based on a handheld Raman spectrometer for use in the simple, label-free identification of biomolecules (urea, creatinine, and bilirubin) in urine. The raspberry-shaped Au substrate formed on the surface of an Si wafer provides plasmonic enhancement of the SERS signals, with an excellent uniformity and stability. The SERS sensor combines the advantages of flexibility, portability, and multifunctional detection and may be used in identifying multiple analytes in urine. The sensor exhibits high sensitivities in detecting urea, creatinine, and bilirubin, with respective detection limits of 4.17 × 10-3 M, 5.90 × 10-6 M, and 1.38 × 10-7 M (signal-to-noise ratio = 3). Furthermore, we used the wearable diaper sensor to monitor biomolecules at the diagnostic threshold, facilitating non-invasive diagnosis and medical monitoring of disease-related biomarkers.

Sports Heart Monitors as Reliable Diagnostic Tools for Training Control and Detecting Arrhythmias in Professional and Leisure-Time Endurance Athletes: An Expert Consensus Statement

There are countless types of portable heart rate monitoring medical devices used variously by leisure-time exercisers, professional athletes, and chronically ill patients. Almost all the currently used heart rate monitors are capable of detecting arrhythmias, but this feature is not widely known or used among their millions of consumers. The aims of this paper were as follows: (1) to analyze the currently available sports heart rate monitors and assess their advantages and disadvantage in terms of heart rate and rhythm monitoring in endurance athletes; (2) to discuss what types of currently available commercial heart rate monitors are most convenient/adjustable to the needs of different consumers (including occasionally physically active adults and cardiac patients), bearing in mind the potential health risks, especially heart rhythm disturbances connected with endurance training; (3) to suggest a set of "optimal" design features for next-generation smart wearable devices based on the consensus opinion of an expert panel of athletes, coaches, and sports medicine doctors. Ninety-two experts aged 20 years and over, involved in endurance sports on a daily basis, were invited to participate in consensus-building discussions, including 56 long-distance runners, 18 cyclists, nine coaches, and nine physicians (sports medicine specialists, cardiologists, and family medicine doctors). The overall consensus endorsed by these experts indicates that the "optimal" sports heart rate monitor should be a one-piece device of the smartwatch type (with two or more electrodes), with integrated smartphone features, and able to collect and continually transmit data without exhibiting artifacts. It should continuously record at least a single-lead electrocardiography, send an alert after an unexpected fall, be of reasonable weight, come at an affordable price, and be user friendly.

Navigating the Frontier: Emerging Techniques for Detecting Microvascular Complications in Type 2 Diabetes Mellitus: A Comprehensive Review

This review comprehensively explores emerging techniques for detecting microvascular complications in Type 2 Diabetes Mellitus (T2DM), addressing the critical need for advancements in early detection and management. As T2DM continues to rise globally, microvascular complications, including retinopathy, nephropathy, and neuropathy, contribute significantly to the morbidity and mortality associated with the condition. The review synthesizes key findings, revealing various emerging technologies, from advanced imaging modalities to genomic and proteomic approaches. It underscores the potential for personalized medicine, emphasizing the importance of tailoring diagnostic strategies to individual patient profiles. Challenges, including the lack of standardized criteria and issues related to patient adherence, highlight the necessity for collaborative efforts. The conclusion issues a call to action, advocating for enhanced collaboration, increased research investment, patient empowerment through education, and seamless integration of emerging diagnostic techniques into routine clinical care. The review envisions a transformative shift in detecting and managing microvascular complications in T2DM, ultimately improving patient outcomes and contributing to a healthier future for individuals affected by this prevalent metabolic disorder.

Application of Braided Piezoelectric Poly-l-Lactic Acid Cord Sensor to Sleep Bruxism Detection System with Less Physical or Mental Stress

For many years, we have been developing flexible sensors made of braided piezoelectric poly-l-lactic acid (PLLA) fibers that can be tied and untied for practical applications in society. To ensure good quality of sleep, the occurrence of bruxism has been attracting attention in recent years. Currently, there is a need for a system that can easily and accurately measure the frequency of bruxism at home. Therefore, taking advantage of the braided piezoelectric PLLA cord sensor's unique characteristic of being sewable, we aimed to provide a system that can measure the frequency of bruxism using the braided piezoelectric PLLA cord sensor simply sewn onto a bed sheet on which the subject lies down. After many tests using trial and error, the sheet sensor was completed with zigzag stitching. Twenty subjects slept overnight in a hospital room on sheets integrated with a braided piezoelectric PLLA cord. Polysomnography (PSG) was simultaneously performed on these subjects. The results showed that their bruxism could be detected with an accuracy of more than 95% compared with PSG measurements, which can only be performed in a hospital by a physician and are more burdensome for the subjects, with the subjects simply lying on the bed sheet with a braided piezoelectric PLLA cord sensor sewn into it.

[Development of intelligent monitoring system based on Internet of Things and wearable technology and exploration of its clinical application mode]

Wearable monitoring, which has the advantages of continuous monitoring for a long time with low physiological and psychological load, represents a future development direction of monitoring technology. Based on wearable physiological monitoring technology, combined with Internet of Things (IoT) and artificial intelligence technology, this paper has developed an intelligent monitoring system, including wearable hardware, ward Internet of Things platform, continuous physiological data analysis algorithm and software. We explored the clinical value of continuous physiological data using this system through a lot of clinical practices. And four value points were given, namely, real-time monitoring, disease assessment, prediction and early warning, and rehabilitation training. Depending on the real clinical environment, we explored the mode of applying wearable technology in general ward monitoring, cardiopulmonary rehabilitation, and integrated monitoring inside and outside the hospital. The research results show that this monitoring system can be effectively used for monitoring of patients in hospital, evaluation and training of patients' cardiopulmonary function, and management of patients outside hospital.

Soft Epidermal Paperfluidics for Sweat Analysis by Ratiometric Raman Spectroscopy

The expanding interest in digital biomarker analysis focused on non-invasive human bodily fluids, such as sweat, highlights the pressing need for easily manufactured and highly efficient soft lab-on-skin solutions. Here, we report, for the first time, the integration of microfluidic paper-based devices (μPAD) and non-enhanced Raman-scattering-enabled optical biochemical sensing (Raman biosensing). Their integration merges the enormous benefits of μPAD, with high potential for commercialization and use in resource-limited settings, with biorecognition-element-free (but highly selective) optical Raman biosensing. The introduced thin (0.36 mm), ultra-lightweight (0.19 g), and compact footprint (3 cm2) opto-paperfluidic sweat patch is flexible, stretchable, and conforms, irritation-free, to hairless or minimally haired body regions to enable swift sweat collection. As a great advantage, this new bio-chemical sensory system excels through its absence of onboard biorecognition elements (bioreceptor-free) and omission of plasmonic nanomaterials. The proposed easy fabrication process is adaptable to mass production by following a fully sustainable and cost-effective process utilizing only basic tools by avoiding typically employed printing or laser patterning. Furthermore, efficient collection and transportation of precise sweat volumes, driven exclusively by the wicking properties of porous materials, shows high efficiency in liquid transportation and reduces biosensing latency by a factor of 5 compared to state-of-the-art epidermal microfluidics. The proposed unit enables electronic chip-free and imaging-less visual sweat loss quantification as well as optical biochemical analysis when coupled with Raman spectroscopy. We investigated the multimodal quantification of sweat urea and lactate levels ex vivo (with syntactic sweat including +30 sweat analytes on porcine skin) and achieved a linear dynamic range from 0 to 100 mmol/L during fully dynamic continuous flow characterization.

[Wearable devices: Perspectives on assessing and monitoring human physiological status]

This review article aims to explore the major challenges that the healthcare system is currently facing and propose a new paradigm shift that harnesses the potential of wearable devices and novel theoretical frameworks on health and disease. Lifestyle-induced diseases currently account for a significant portion of all healthcare spending, with this proportion projected to increase with population aging. Wearable devices have emerged as a key technology for implementing large-scale healthcare systems focused on disease prevention and management. Advancements in miniaturized sensors, system integration, the Internet of Things, artificial intelligence, 5G, and other technologies have enabled wearable devices to perform high-quality measurements comparable to medical devices. Through various physical, chemical, and biological sensors, wearable devices can continuously monitor physiological status information in a non-invasive or minimally invasive way, including electrocardiography, electroencephalography, respiration, blood oxygen, blood pressure, blood glucose, activity, and more. Furthermore, by combining concepts and methods from complex systems and nonlinear dynamics, we developed a novel theory of continuous dynamic physiological signal analysis-dynamical complexity. The results of dynamic signal analyses can provide crucial information for disease prevention, diagnosis, treatment, and management. Wearable devices can also serve as an important bridge connecting doctors and patients by tracking, storing, and sharing patient data with medical institutions, enabling remote or real-time health assessments of patients, and providing a basis for precision medicine and personalized treatment. Wearable devices have a promising future in the healthcare field and will be an important driving force for the transformation of the healthcare system, while also improving the health experience for individuals.

Sweat Sensor Based on Wearable Janus Textiles for Sweat Collection and Microstructured Optical Fiber for Surface-Enhanced Raman Scattering Analysis

Wearable sweat sensors provide real-time monitoring of biomarkers, enabling individuals to gain real-time insight into their health status. Current sensors primarily rely on electrochemical mechanisms, limiting their capacity for the concurrent detection of multiple analytes. Surface-enhanced Raman scattering spectroscopy offers an alternative approach by providing molecular fingerprint information to facilitate the identification of intricate analytes. In this study, we combine a wearable Janus fabric for efficient sweat collection and a grapefruit optical fiber embedded with Ag nanoparticles as a sensitive SERS probe. The Janus fabric features a superhydrophobic side in contact with the skin and patterned superhydrophilic regions on the opposite surface, facilitating the unidirectional flow of sweat toward these hydrophilic zones. Grapefruit optical fibers feature sharp tips with the ability to penetrate transparent dressings. Its microchannels extract sweat through capillary force, and nanoliter-scale volumes of sweat are sufficient to completely fill them. The Raman signal of sweat components is greatly enhanced by the plasmonic hot spots and accumulates along the fiber length. We demonstrate sensitive detection of sodium lactate and urea in sweat with a detection limit much lower than the physiological concentration levels. Moreover, the platform shows its capability for multicomponent detection and extends to the analysis of real human sweat.

Materials, Designs, and Implementations of Wearable Antennas and Circuits for Biomedical Applications: A Review

The intersection of biomedicine and radio frequency (RF) engineering has fundamentally transformed self-health monitoring by leveraging soft and wearable electronic devices. This paradigm shift presents a critical challenge, requiring these devices and systems to possess exceptional flexibility, biocompatibility, and functionality. To meet these requirements, traditional electronic systems, such as sensors and antennas made from rigid and bulky materials, must be adapted through material science and schematic design. Notably, in recent years, extensive research efforts have focused on this field, and this review article will concentrate on recent advancements. We will explore the traditional/emerging materials for highly flexible and electrically efficient wearable electronics, followed by systematic designs for improved functionality and performance. Additionally, we will briefly overview several remarkable applications of wearable electronics in biomedical sensing. Finally, we provide an outlook on potential future directions in this developing area.

Facile Fabrication of "Tacky", Stretchable, and Aligned Carbon Nanotube Sheet-Based Electronics for On-Skin Health Monitoring

Point-of-care monitoring of physiological signals such as electrocardiogram, electromyogram, and electroencephalogram is essential for prompt disease diagnosis and quick treatment, which can be realized through advanced skin-worn electronics. However, it is still challenging to design an intimate and nonrestrictive skin-contact device for physiological measurements with high fidelity and artifact tolerance. This research presents a facile method using a "tacky" surface to produce a tight interface between the ACNT skin-like electronic and the skin. The method provides the skin-worn electronic with a stretchability of up to 70% strain, greater than that of most common epidermal electrodes. Low-density ACNT bundles facilitate the infiltration of adhesive and improve the conformal contact between the ACNT sheet and the skin, while dense ACNT bundles lessen this effect. The stretchability and conformal contact allow the ACNT sheet-based electronics to create a tight interface with the skin, which enables the high-fidelity measurement of physiological signals (the Pearson's coefficient of 0.98) and tolerance for motion artifacts. In addition, our method allows the use of degradable substrates to enable reusability and degradability of the electronics based on ACNT sheets, integrating "green" properties into on-skin electronics.

Existing Barriers Faced by and Future Design Recommendations for Direct-to-Consumer Health Care Artificial Intelligence Apps: Scoping Review

BACKGROUND

Direct-to-consumer (DTC) health care artificial intelligence (AI) apps hold the potential to bridge the spatial and temporal disparities in health care resources, but they also come with individual and societal risks due to AI errors. Furthermore, the manner in which consumers interact directly with health care AI is reshaping traditional physician-patient relationships. However, the academic community lacks a systematic comprehension of the research overview for such apps.

OBJECTIVE

This paper systematically delineated and analyzed the characteristics of included studies, identified existing barriers and design recommendations for DTC health care AI apps mentioned in the literature and also provided a reference for future design and development.

METHODS

This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines and was conducted according to Arksey and O'Malley's 5-stage framework. Peer-reviewed papers on DTC health care AI apps published until March 27, 2023, in Web of Science, Scopus, the ACM Digital Library, IEEE Xplore, PubMed, and Google Scholar were included. The papers were analyzed using Braun and Clarke's reflective thematic analysis approach.

RESULTS

Of the 2898 papers retrieved, 32 (1.1%) covering this emerging field were included. The included papers were recently published (2018-2023), and most (23/32, 72%) were from developed countries. The medical field was mostly general practice (8/32, 25%). In terms of users and functionalities, some apps were designed solely for single-consumer groups (24/32, 75%), offering disease diagnosis (14/32, 44%), health self-management (8/32, 25%), and health care information inquiry (4/32, 13%). Other apps connected to physicians (5/32, 16%), family members (1/32, 3%), nursing staff (1/32, 3%), and health care departments (2/32, 6%), generally to alert these groups to abnormal conditions of consumer users. In addition, 8 barriers and 6 design recommendations related to DTC health care AI apps were identified. Some more subtle obstacles that are particularly worth noting and corresponding design recommendations in consumer-facing health care AI systems, including enhancing human-centered explainability, establishing calibrated trust and addressing overtrust, demonstrating empathy in AI, improving the specialization of consumer-grade products, and expanding the diversity of the test population, were further discussed.

CONCLUSIONS

The booming DTC health care AI apps present both risks and opportunities, which highlights the need to explore their current status. This paper systematically summarized and sorted the characteristics of the included studies, identified existing barriers faced by, and made future design recommendations for such apps. To the best of our knowledge, this is the first study to systematically summarize and categorize academic research on these apps. Future studies conducting the design and development of such systems could refer to the results of this study, which is crucial to improve the health care services provided by DTC health care AI apps.

Thread-Embedded-in-PDMS Wearable Strain Sensor for Real-Time Monitoring of Human Joint Motion

Real-time monitoring of human joint motion holds paramount importance in assessing joint health status, preventing and treating joint diseases, and evaluating physical flexibility and coordination. However, traditional strain sensors face limitations in meeting the substantial strain requirements associated with human joint motion. Recently, there has been considerable attention directed towards flexible strain sensors prepared using pliable substrates combined with silk and cotton fabrics. Nonetheless, these sensors exhibit insufficient linearity across the entire measurement range, thereby compromising the predictability of real joint motion based on the output signal. This paper introduced a flexible strain sensor designed to address this issue by offering an enhanced range and high linearity. Specifically, the core wire of the strain sensor was produced by coating a polybutylene terephthalate thread with conductive carbon ink integrated with carbon nanotubes, encapsulated in a thin layer of polydimethylsiloxane in an "S" configuration. The proposed strain sensor maintained excellent linearity within its strain range of 60%, along with advantages such as rapid response speed and robust durability. On-trial tests further affirmed the sensor's capability to effectively monitor the motion of human joints.

Prototype of Data Collector from Textronic Sensors

In the era of miniaturization of electronic equipment and the need to connect sensors with textile materials, including clothing, the processing of signals received from the implemented sensors becomes an important issue. Information obtained by measuring the electrical properties of the sensors must be sent, processed, and visualized. For this purpose, the authors of this article have developed a prototype of a data collector obtained from textronic sensors created on composite textile substrates. The device operates in a system consisting of an electronic module based on the nRF52 platform, which supports wireless communication with sensors using Bluetooth technology and transmits the obtained data to a database hosted on the Microsoft Azure platform. A mobile application based on React Native technology was created to control the data stream. The application enables automatic connection to the selected collector, data download and their presentation in the form of selected charts. Initial verification tests of the system showed the correctness and reliability of its operation, and the presented graphs created from the obtained data indicate the usefulness of the device in applications where measurements and recording of impedance, resistance, and temperature are necessary. The presented prototype of a data collector can be used for resistance, impedance, and temperature measurements in the case of textronic structures but also in other wearable electronic systems.

Implantable Electrochemical Microsensors for In Vivo Monitoring of Animal Physiological Information

In vivo monitoring of animal physiological information plays a crucial role in promptly alerting humans to potential diseases in animals and aiding in the exploration of mechanisms underlying human diseases. Currently, implantable electrochemical microsensors have emerged as a prominent area of research. These microsensors not only fulfill the technical requirements for monitoring animal physiological information but also offer an ideal platform for integration. They have been extensively studied for their ability to monitor animal physiological information in a minimally invasive manner, characterized by their bloodless, painless features, and exceptional performance. The development of implantable electrochemical microsensors for in vivo monitoring of animal physiological information has witnessed significant scientific and technological advancements through dedicated efforts. This review commenced with a comprehensive discussion of the construction of microsensors, including the materials utilized and the methods employed for fabrication. Following this, we proceeded to explore the various implantation technologies employed for electrochemical microsensors. In addition, a comprehensive overview was provided of the various applications of implantable electrochemical microsensors, specifically in the monitoring of diseases and the investigation of disease mechanisms. Lastly, a concise conclusion was conducted on the recent advancements and significant obstacles pertaining to the practical implementation of implantable electrochemical microsensors.

Oral micro-electronic platform for temperature and humidity monitoring

Intraoral theranostics, the integration of diagnostics and therapeutics within the oral cavity, is gaining significant traction. This pioneering approach primarily addresses issues like xerostomia (dry mouth), commonly resulting from cancer treatment, with a specific focus on monitoring temperature and humidity. This paper introduces the innovative Intra-Oral Portable Micro-Electronic (IOPM) fluidic theranostic device platform. It leverages conventional dental spoons by incorporating advanced sensors for precise measurements of oral temperature and humidity. Personalization options include a microfluidic chip and a tooth model, enabling targeted delivery of therapeutic agents to optimize treatment outcomes. The electronic control system simplifies the administration of fluid dosages, intelligently adjusted based on real-time oral cavity temperature and humidity readings. Rigorous experimental evaluations validate the platform's precision in delivering fluid volumes at predefined intervals. This platform represents a transformative advancement for individuals contending with oral health challenges such as xerostomia (dry mouth). Furthermore, it has the potential to elevate oral healthcare standards by providing advanced diagnostics and tailored therapeutic solutions, benefiting both patients and dental professionals alike.

3D Printed Conformal Strain and Humidity Sensors for Human Motion Prediction and Health Monitoring via Machine Learning

Wearable sensors have garnered considerable attention due to their flexibility and lightweight characteristics in the realm of healthcare applications. However, developing robust wearable sensors with facile fabrication and good conformity remains a challenge. In this study, a conductive graphene nanoplate-carbon nanotube (GC) ink is synthesized for multi jet fusion (MJF) printing. The layer-by-layer fabrication process of MJF not only improves the mechanical and flame-retardant properties of the printed GC sensor but also bolsters its robustness and sensitivity. The direction of sensor bending significantly impacts the relative resistance changes, allowing for precise investigations of joint motions in the human body, such as those of the fingers, wrists, elbows, necks, and knees. Furthermore, the data of resistance changes collected by the GC sensor are utilized to train a support vector machine with a 95.83% accuracy rate for predicting human motions. Due to its stable humidity sensitivity, the sensor also demonstrates excellent performance in monitoring human breath and predicting breath modes (normal, fast, and deep breath), thereby expanding its potential applications in healthcare. This work opens up new avenues for using MJF-printed wearable sensors for a variety of healthcare applications.

Direct-Ink-Writing 3D-Printed Bioelectronics

The development of wearable and implantable bioelectronics has garnered significant momentum in recent years, driven by the ever-increasing demand for personalized health monitoring, remote patient management, and real-time physiological data collection. The elevated sophistication and advancement of these devices have thus led to the use of many new and unconventional materials which cannot be fulfilled through traditional manufacturing techniques. Three-dimension (3D) printing, also known as additive manufacturing, is an emerging technology that opens new opportunities to fabricate next-generation bioelectronic devices. Some significant advantages include its capacity for material versatility and design freedom, rapid prototyping, and manufacturing efficiency with enhanced capabilities. This review provides an overview of the recent advances in 3D printing of bioelectronics, particularly direct ink writing (DIW), encompassing the methodologies, materials, and applications that have emerged in this rapidly evolving field. This review showcases the broad range of bioelectronic devices fabricated through 3D printing including wearable biophysical sensors, biochemical sensors, electrophysiological sensors, energy devices, multimodal systems, implantable devices, and soft robots. This review will also discuss the advantages, existing challenges, and outlook of applying DIW 3D printing for the development of bioelectronic devices toward healthcare applications.

Artificial Intelligence-Powered Electronic Skin

Skin-interfaced electronics is gradually changing medical practices by enabling continuous and noninvasive tracking of physiological and biochemical information. With the rise of big data and digital medicine, next-generation electronic skin (e-skin) will be able to use artificial intelligence (AI) to optimize its design as well as uncover user-personalized health profiles. Recent multimodal e-skin platforms have already employed machine learning (ML) algorithms for autonomous data analytics. Unfortunately, there is a lack of appropriate AI protocols and guidelines for e-skin devices, resulting in overly complex models and non-reproducible conclusions for simple applications. This review aims to present AI technologies in e-skin hardware and assess their potential for new inspired integrated platform solutions. We outline recent breakthroughs in AI strategies and their applications in engineering e-skins as well as understanding health information collected by e-skins, highlighting the transformative deployment of AI in robotics, prosthetics, virtual reality, and personalized healthcare. We also discuss the challenges and prospects of AI-powered e-skins as well as predictions for the future trajectory of smart e-skins.

A fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation

Post-surgical treatments of the human throat often require continuous monitoring of diverse vital and muscle activities. However, wireless, continuous monitoring and analysis of these activities directly from the throat skin have not been developed. Here, we report the design and validation of a fully integrated standalone stretchable device platform that provides wireless measurements and machine learning-based analysis of diverse vibrations and muscle electrical activities from the throat. We demonstrate that the modified composite hydrogel with low contact impedance and reduced adhesion provides high-quality long-term monitoring of local muscle electrical signals. We show that the integrated triaxial broad-band accelerometer also measures large body movements and subtle physiological activities/vibrations. We find that the combined data processed by a 2D-like sequential feature extractor with fully connected neurons facilitates the classification of various motion/speech features at a high accuracy of over 90%, which adapts to the data with noise from motion artifacts or the data from new human subjects. The resulting standalone stretchable device with wireless monitoring and machine learning-based processing capabilities paves the way to design and apply wearable skin-interfaced systems for the remote monitoring and treatment evaluation of various diseases.

Strain-induced crystallization and phase separation used for fabricating a tough and stiff slide-ring solid polymer electrolyte

The demand for mechanically robust polymer-based electrolytes is increasing for applications to wearable devices. Young's modulus and breaking energy are essential parameters for describing the mechanical reliability of electrolytes. The former plays a vital role in suppressing the short circuit during charge-discharge, while the latter indicates crack propagation resistance. However, polymer electrolytes with high Young's moduli are generally brittle. In this study, a tough slide-ring solid polymer electrolyte (SR-SPE) breaking through this trade-off between stiffness and toughness is designed on the basis of strain-induced crystallization (SIC) and phase separation. SIC makes the material highly tough (breaking energy, 80 to 100 megajoules per cubic meter). Phase separation in the polymer enhanced stiffness (Young's modulus, 10 to 70 megapascals). The combined effect of phase separation and SIC made SR-SPE tough and stiff, while these mechanisms do not impair ionic conductivity. This SIC strategy could be combined with other toughening mechanisms to design tough polymer gel materials.

Advances in Biocarbon and Soft Material Assembly for Enthalpy Storage: Fundamentals, Mechanisms, and Multimodal Applications

High-value-added biomass materials like biocarbon are being actively pursued integrating them with soft materials in a broad range of advanced renewable energy technologies owing to their advantages, such as lightweight, relatively low-cost, diverse structural engineering applications, and high energy storage potential. Consequently, the hybrid integration of soft and biomass-derived materials shall store energy to mitigate intermittency issues, primarily through enthalpy storage during phase change. This paper introduces the recent advances in the development of natural biomaterial-derived carbon materials in soft material assembly and its applications in multidirectional renewable energy storage. Various emerging biocarbon materials (biochar, carbon fiber, graphene, nanoporous carbon nanosheets (2D), and carbon aerogel) with intrinsic structures and engineered designs for enhanced enthalpy storage and multimodal applications are discussed. The fundamental design approaches, working mechanisms, and feature applications, such as including thermal management and electromagnetic interference shielding, sensors, flexible electronics and transparent nanopaper, and environmental applications of biocarbon-based soft material composites are highlighted. Furthermore, the challenges and potential opportunities of biocarbon-based composites are identified, and prospects in biomaterial-based soft materials composites are presented.

Scalable Manufacturing of Large-Area Pressure Sensor Array for Sitting Posture Recognition in Real Time

Pressure sensors are considered the key technology for potential applications in real-time health monitoring, artificial electronic skins, and human-machine interfaces. Despite the significant progress in developing novel sensitive materials and constructing unique sensor structures, it remains challenging to fabricate large-area pressure sensor arrays due to the involvement of complex procedures including photolithography, laser writing, or coating. Herein, a scalable manufacturing approach for the realization of pressure sensor arrays with substantially enlarged sensitive areas is proposed using a versatile screen-printing technique. A compensation mechanism is introduced into the printing process to ensure the precise alignment of conductive electrodes, insulation layers, and sensitive microstructures with an alignment error of less than 4 μm. The fully screen-printed sensors exhibit excellent collective sensing performance, such as a reasonable pressure sensitivity of -2.2 kPa-1, a fast response time of 40 ms, and superior durability over 3000 consecutive pressures. Additionally, an integrated 16 × 32 pressure sensor array with a sensing area of 190 × 380 mm2 is demonstrated to precisely recognize the sitting postures and the body weights, showing great potential in continuous and real-time health status monitoring.

Smart Wearable Nanopaper Patch for Continuous Multiplexed Optical Monitoring of Sweat Parameters

Notwithstanding the substantial progress in optical wearable sensing devices, developing wearable optical sensors for simultaneous, real-time, and continuous monitoring of multiple biomarkers is still an important, yet unmet, demand. Aiming to address this need, we introduced for the first time a smart wearable optical sensor (SWOS) platform combining a multiplexed sweat sensor sticker with its IoT-enabled readout module. We employed our SWOS system for on-body continuous, real-time, and simultaneous fluorimetric monitoring of sweat volume (physical parameter) and pH (chemical marker). Herein, a variation in moisture (5-45 μL) or pH (4.0-7.0) causes a color/fluorescence change in the copper chloride/fluorescein immobilized within a transparent chitin nanopaper (ChNP) in a selective and reversible manner. Human experiments conducted on athletic volunteers during exercise confirm that our developed SWOS platform can be efficiently exploited for smart perspiration analysis toward personalized health monitoring. Moreover, our system can be further extended for the continuous and real-time multiplexed monitoring of various biomarkers (metabolites, proteins, or drugs) of sweat or other biofluids (for example, analyzing exhaled breath by integrating onto a facemask).

Strong, Tough, and Anti-Swelling Supramolecular Conductive Hydrogels for Amphibious Motion Sensors

Conductive polymer hydrogels (CPHs) are widely employed in emerging flexible electronic devices because they possess both the electrical conductivity of conductors and the mechanical properties of hydrogels. However, the poor compatibility between conductive polymers and the hydrogel matrix, as well as the swelling behavior in humid environments, greatly compromises the mechanical and electrical properties of CPHs, limiting their applications in wearable electronic devices. Herein, a supramolecular strategy to develop a strong and tough CPH with excellent anti-swelling properties by incorporating hydrogen, coordination bonds, and cation-π interactions between a rigid conducting polymer and a soft hydrogel matrix is reported. Benefiting from the effective interactions between the polymer networks, the obtained supramolecular hydrogel has homogeneous structural integrity, exhibiting remarkable tensile strength (1.63 MPa), superior elongation at break (453%), and remarkable toughness (5.5 MJ m-3 ). As a strain sensor, the hydrogel possesses high electrical conductivity (2.16 S m-1 ), a wide strain linear detection range (0-400%), and excellent sensitivity (gauge factor = 4.1), sufficient to monitor human activities with different strain windows. Furthermore, this hydrogel with high swelling resistance has been successfully applied to underwater sensors for monitoring frog swimming and underwater communication. These results reveal new possibilities for amphibious applications of wearable sensors.

A Miniaturized, Battery-Free, Wireless Wound Monitor That Predicts Wound Closure Rate Early

Diabetic foot ulcers are chronic wounds that affect millions and increase the risk of amputation and mortality, highlighting the critical need for their early detection. Recent demonstrations of wearable sensors enable real-time wound assessment, but they rely on bulky electronics, making them difficult to interface with wounds. Herein, a miniaturized, wireless, battery-free wound monitor that measures lactate in real-time and seamlessly integrates with bandages for conformal attachment to the wound bed is introduced. Lactate is selected due to its multifaceted role in initiating healing. Studies in healthy and diabetic mice reveal distinct lactate profiles for normal and impaired healing wounds. A mathematical model based on the sensor data predicts wound closure rate within the first 3 days post-injury with ≈76% accuracy, which increases to ≈83% when pH is included. These studies underscore the significance of monitoring biomarkers during the inflammation phase, which can offer several benefits, including short-term use of wound monitors and their easy removal, resulting in lower risks of injury and infection at the wound site. Improvements in prediction accuracy can be achieved by designing mathematical models that build on multiple wound parameters such as pro-inflammatory and metabolic markers. Achieving this goal will require designing multi-analyte wound monitors.

Sustainable electronic textiles towards scalable commercialization

Textiles represent a fundamental material format that is extensively integrated into our everyday lives. The quest for more versatile and body-compatible wearable electronics has led to the rise of electronic textiles (e-textiles). By enhancing textiles with electronic functionalities, e-textiles define a new frontier of wearable platforms for human augmentation. To realize the transformational impact of wearable e-textiles, materials innovations can pave the way for effective user adoption and the creation of a sustainable circular economy. We propose a repair, recycle, replacement and reduction circular e-textile paradigm. We envisage a systematic design framework embodying material selection and biofabrication concepts that can unify environmental friendliness, market viability, supply-chain resilience and user experience quality. This framework establishes a set of actionable principles for the industrialization and commercialization of future sustainable e-textile products.

Modulating piezoelectricity and mechanical strength via three-dimensional gradient structure for piezoelectric composites

Advanced flexible electronic devices make urgent demand for wearing comfort and data accuracy. Piezoelectric composites exhibit great potential, but mutually constrained mechanical strength and electrical output limit their further applications. Here, we design a gradient PMN-PT/PVDF nanocomposite via a non-equilibrium process integrated with a modified electrospinning and hot-pressing process to modulate the piezoelectric output and mechanical strength. The enhanced piezoelectric output together with the mechanical strength of the gradient structure are verified from both the experimental and simulation results. Ascribed to a unique three-dimensional gradient distribution, the prepared PMN-PT/PVDF nanocomposite exhibits an excellent mechanical strength (830 MPa) and piezoelectric performance (1.08 V), which are substantially higher than those of a randomly dispersed nanocomposite. The enhancement mechanism is revealed in terms of polarization, stress and crystallinity. These results of the gradient structure offer new opportunities to understand the structure-related mechanical and electrical behaviors of a nanocomposite, and support the design of a nanocomposite with overall performance.

Individualized monitoring of heat illness risk: novel adaptive physiological strain index to assess exercise-heat strain from athletes to fully encapsulated workers

Objective. Exercise-heat strain estimation approaches often involve combinations of body core temperature (Tcore), skin temperature (Tsk) and heart rate (HR). A successful existing measure is the 'Physiological Strain Index' (PSI), which combines HR and Tcore values to estimate strain. However, depending on variables such as aerobic fitness and clothing, the equation's 'maximal/critical' Tcore must be changed to accurately represent the strain, in part because high Tsk (small Tcore-Tsk) can increase cardiovascular strain and thereby negatively affect performance. Here, an 'adaptive PSI' (aPSI) is presented where the original PSI Tcorecriticalvalue is 'adapted' dynamically by the delta between Tcore and Tsk.Approach. PSI and aPSI were computed for athletes (ELITE,N= 11 male and 8 female, 8 km time-trial) and soldiers in fully encapsulating personal protective equipment (PPE,N= 8 male, 2 km approach-march). While these were dissimilar events, it was anticipated given that the clothing and work rates would elicit similar very-high exercise-heat strain values.Main results. Mean end HR values were similar (∼180 beats min-1) with higher Tcore = 40.1 ± 0.4 °C for ELITE versus PPE 38.4 ± 0.6 °C (P< 0.05). PSI end values were different between groups (P< 0.01) and appeared 'too-high' for ELITE (11.4 ± 0.8) and 'too-low' for PPE (7.6 ± 2.0). However, aPSI values were not different (9.9 ± 1.4 versus 9.0 ± 2.5 versus;p> 0.05) indicating a 'very high' level of exercise-heat strain for both conditions.Significance. A simple adaptation of the PSI equation, which accounts for differences in Tcore-to-Tsk gradients, provides a physiological approach to dynamically adapt PSI to provide a more accurate index of exercise-heat strain under very different working conditions.

Smart Contact Lenses-A Step towards Non-Invasive Continuous Eye Health Monitoring

According to the age-old adage, while eyes are often considered the gateway to the soul, they might also provide insights into a more pragmatic aspect of our health: blood sugar levels. This potential breakthrough could be realized through the development of smart contact lenses (SCLs). Although contact lenses were first developed for eyesight correction, new uses have recently become available. In the near future, it might be possible to monitor a variety of ocular and systemic disorders using contact lens sensors. Within the realm of glaucoma, SCLs present a novel prospect, offering a potentially superior avenue compared to traditional management techniques. These lenses introduce the possibility of non-invasive and continuous monitoring of intraocular pressure (IOP) while also enabling the personalized administration of medication as and when needed. This convergence holds great promise for advancing glaucoma care. In this review, recent developments in SCLs, including their potential applications, such as IOP and glucose monitoring, are briefly discussed.

Advanced Self-Powered Biofuel Cells with Capacitor and Nanogenerator for Biomarker Sensing

Self-powered biofuel cells (BFCs) have evolved for highly sensitive detection of biomarkers such as noncodon micro ribonucleic acids (miRNAs) in the presence of interfering substrates. Self-charging supercapacitive BFCs for in vivo and in vitro cellular microenvironments represent the most prevalent sensing mechanism for diagnosis. Therefore, self-powered biosensing (SPB) with a capacitor and contact separation with a triboelectric nanogenerator (TENG) offers electrochemical and colorimetric dual-mode detection via improved electrical signal intensity. In this review, we discuss three major components: stretchable self-powered BFC design, miRNA sensing, and impedance spectroscopy. A specific focus is given to 1) assembling of sensors for biomarkers, 2) electrical output signal intensification, and 3) role of supercapacitors and nanogenerators in SPBs. We outline the key features of stretchable SPBs and the sequence of miRNA sensing by SPBs. We have emphasized the need of a supercapacitor and nanogenerator for SPBs in the context of advanced assembly of the sensing unit. Finally, we outline the role of impedance spectroscopy in the detection and estimation of biomarkers. We highlight key challenges in SPBs for biomarker sensing, which needs improved sensing accuracy, integration strategies of electrochemical biosensing for in vitro and in vivo microenvironments, and the impact of miRNA sensing on cancer diagnostics. This article attempts a specific focus on the accuracy and limitations of sensing unit for miRNA biomarkers and associated tool for boosting electrical signal intensity for a potential big step further.

COVID-19 scent dog research highlights and synthesis during the pandemic of December 2019-April 2023

CONTEXT

This review was undertaken to provide information concerning the advancement of research in the area of COVID-19 screening and testing during the worldwide pandemic from December 2019 through April 2023. In this review, we have examined the safety, effectiveness, and practicality of utilizing trained scent dogs in clinical and public situations for COVID-19 screening. Specifically, results of 29 trained scent dog screening peer-reviewed studies were compared with results of real-time reverse-transcription polymerase chain reaction (RT-PCR) and rapid antigen (RAG) COVID-19 testing methods.

OBJECTIVES

The review aims to systematically evaluate the strengths and weaknesses of utilizing trained scent dogs in COVID-19 screening.

METHODS

At the time of submission of our earlier review paper in August 2021, we found only four peer-reviewed COVID-19 scent dog papers: three clinical research studies and one preprint perspective paper. In March and April 2023, the first author conducted new literature searches of the MEDLINE/PubMed, Google Scholar, and Cochrane Library websites. Again, the keyword phrases utilized for the searches included "COVID detection dogs," "COVID scent dogs," and "COVID sniffer dogs." The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 Checklist was followed to ensure that our review adhered to evidence-based guidelines for reporting. Utilizing the results of the reviewed papers, we compiled statistics to intercompare and summarize basic information concerning the scent dogs and their training, the populations of the study participants, the types of sampling methods, the comparative tests utilized, and the effectiveness of the scent dog screening.

RESULTS

A total of 8,043 references were identified through our literature search. After removal of duplicates, there were 7,843 references that were screened. Of these, 100 were considered for full-text eligibility, 43 were included for qualitative synthesis, and 29 were utilized for quantitative analysis. The most relevant peer-reviewed COVID-19 scent dog references were identified and categorized. Utilizing all of the scent dog results provided for this review, we found that 92.3 % of the studies reached sensitivities exceeding 80 and 32.0 % of the studies exceeding specificities of 97 %. However, 84.0 % of the studies reported specificities above 90 %. Highlights demonstrating the effectiveness of the scent dogs include: (1) samples of breath, saliva, trachea-bronchial secretions and urine as well as face masks and articles of clothing can be utilized; (2) trained COVID-19 scent dogs can detect presymptomatic and asymptomatic patients; (3) scent dogs can detect new SARS-CoV-2 variants and Long COVID-19; and (4) scent dogs can differentiate SARS-CoV-2 infections from infections with other novel respiratory viruses.

CONCLUSIONS

The effectiveness of the trained scent dog method is comparable to or in some cases superior to the real-time RT-PCR test and the RAG test. Trained scent dogs can be effectively utilized to provide quick (seconds to minutes), nonintrusive, and accurate results in public settings and thus reduce the spread of the COVID-19 virus or other viruses. Finally, scent dog research as described in this paper can serve to increase the medical community's and public's knowledge and acceptance of medical scent dogs as major contributors to global efforts to fight diseases.

Sensors for in situ monitoring of oral and dental health parameters in saliva

OBJECTIVES

The oral cavity is an easily accessible unique environment and open system which is influenced by the oral fluids, microbiota, and nutrition. Little is known about the kinetics and dynamics of metabolic processes at the intraoral surfaces. Real-time monitoring of salivary biomarkers, e.g., glucose, lactate, fluoride, calcium, phosphate, and pH with intraoral sensors is therefore of major interest. The aim of this review is to overview the existing literature for intraoral saliva sensors.

MATERIALS AND METHODS

A comprehensive literature search was performed to review the most relevant studies on intraoral saliva sensor technology.

RESULTS

There is limited literature about the in situ saliva monitoring of salivary biomarkers. Bioadhesion and biofouling processes at the intraoral surfaces limit the performances of the sensors. Real-time, long-term, and continuous intraoral measurement of salivary metabolites remains challenging and needs further investigation as only few well-functioning sensors have been developed until today. Until now, there is no sensor that measures reliably beyond hours for any analyte other than glucose.

CONCLUSIONS

Saliva's complex and dynamic structure as well as bioadhesion are key challenges and should be addressed in the future developments. Consequently, more studies that focus particularly on biofouling processes and interferential effects of the salivary matrix components on sensor surfaces are required.

CLINICAL RELEVANCE

By monitoring fluids in the oral cavity, as the entrance to the digestive system, extensive information can be obtained regarding the effects of foods and preventive agents on the oral microbiota and the tooth surfaces. This may lead to a better understanding of strategies to modulate oral and general health.

A three-level model for therapeutic drug monitoring of antimicrobials at the site of infection

The silent pandemic of bacterial antimicrobial resistance is a leading cause of death worldwide, prolonging hospital stays and raising health-care costs. Poor incentives to develop novel pharmacological compounds and the misuse of antibiotics contribute to the bacterial antimicrobial resistance crisis. Therapeutic drug monitoring (TDM) based on blood analysis can help alleviate the emergence of bacterial antimicrobial resistance and effectively decreases the risk of toxic drug concentrations in patients' blood. Antibiotic tissue penetration can vary in patients who are critically or chronically ill and can potentially lead to treatment failure. Antibiotics such as β-lactams and glycopeptides are detectable in non-invasively collectable biofluids, such as sweat and exhaled breath. The emergence of wearable sensors enables easy access to these non-invasive biofluids, and thus a laboratory-independent analysis of various disease-associated biomarkers and drugs. In this Personal View, we introduce a three-level model for TDM of antibiotics to describe concentrations at the site of infection (SOI) by use of wearable sensors. Our model links blood-based drug measurement with the analysis of drug concentrations in non-invasively collectable biofluids stemming from the SOI to characterise drug concentrations at the SOI. Finally, we outline the necessary clinical and technical steps for the development of wearable sensing platforms for SOI applications.

Water-Resistant Conductive Gels toward Underwater Wearable Sensing

Conductive gels are developing vigorously as superior wearable sensing materials due to their intrinsic conductivity, softness, stretchability, and biocompatibility, showing a great potential in many aspects of lives. However, compared to their wide application on land, it is significant yet rather challenging for traditional conductive gels to realize sensing application under water. The swelling of gels and the loss of conductive components in the aqueous environment, resulted from the diffusion across the interface, lead to structural instability and sensing performance decline. Fortunately, great efforts are devoted to improving the water resistance of conductive gels and employing them in the field of underwater wearable sensing in recent years, and some exciting achievements are obtained, which are of great significance for promoting the safety and efficiency of underwater activities. However, there is no review to thoroughly summarize the underwater sensing application of conductive gels. This review presents a brief overview of the representative design strategies for developing water-resistant conductive gels and their diversified applications in the underwater sensing field as wearable sensors. Finally, the ongoing challenges for further developing water-resistant conductive gels for underwater wearable sensing are also discussed along with recommendations for the future.

Wearable Devices and Explainable Unsupervised Learning for COVID-19 Detection and Monitoring

Despite the declining COVID-19 cases, global healthcare systems still face significant challenges due to ongoing infections, especially among fully vaccinated individuals, including adolescents and young adults (AYA). To tackle this issue, cost-effective alternatives utilizing technologies like Artificial Intelligence (AI) and wearable devices have emerged for disease screening, diagnosis, and monitoring. However, many AI solutions in this context heavily rely on supervised learning techniques, which pose challenges such as human labeling reliability and time-consuming data annotation. In this study, we propose an innovative unsupervised framework that leverages smartwatch data to detect and monitor COVID-19 infections. We utilize longitudinal data, including heart rate (HR), heart rate variability (HRV), and physical activity measured via step count, collected through the continuous monitoring of volunteers. Our goal is to offer effective and affordable solutions for COVID-19 detection and monitoring. Our unsupervised framework employs interpretable clusters of normal and abnormal measures, facilitating disease progression detection. Additionally, we enhance result interpretation by leveraging the language model Davinci GPT-3 to gain deeper insights into the underlying data patterns and relationships. Our results demonstrate the effectiveness of unsupervised learning, achieving a Silhouette score of 0.55. Furthermore, validation using supervised learning techniques yields high accuracy (0.884 ± 0.005), precision (0.80 ± 0.112), and recall (0.817 ± 0.037). These promising findings indicate the potential of unsupervised techniques for identifying inflammatory markers, contributing to the development of efficient and reliable COVID-19 detection and monitoring methods. Our study shows the capabilities of AI and wearables, reflecting the pursuit of low-cost, accessible solutions for addressing health challenges related to inflammatory diseases, thereby opening new avenues for scalable and widely applicable health monitoring solutions.

A Highly Flexible Piezoelectric Ultrasonic Sensor for Wearable Bone Density Testing

Driven by the loss of bone calcium, the elderly are prone to osteoporosis, and regular routine checks on bone status are necessary, which mainly rely on bone testing equipment. Therefore, wearable real-time healthcare devices have become a research hotspot. Herein, we designed a high-performance flexible ultrasonic bone testing system using axial transmission technology based on quantitative ultrasound theory. First, a new rare-earth-element-doped PMN-PZT piezoelectric ceramic was synthesized using a solid-state reaction, and characterized by X-ray diffraction and SEM. Both a high piezoelectric coefficient d33 = 525 pC/N and electromechanical coupling factors of k33 = 0.77, kt = 0.58 and kp = 0.63 were achieved in 1%La/Sm-doped 0.17 PMN-0.47 PZ-0.36 PT ceramics. Combining a flexible PDMS substrate with an ultrasonic array, a flexible hardware circuit was designed which includes a pulse excitation module, ultrasound array module, amplification module, filter module, digital-to-analog conversion module and wireless transmission module, showing high power transfer efficiency and power intensity with values of 35% and 55.4 mW/cm2, respectively. Finally, the humerus, femur and fibula were examined by the flexible device attached to the skin, and the bone condition was displayed in real time on the mobile client, which indicates the potential clinical application of this device in the field of wearable healthcare.

Transparent, High Stretchable, Environmental Tolerance, and Excellent Sensitivity Hydrogel for Flexible Sensors and Capacitive Pens

The prospect of ionic conductive hydrogels in multifunctional sensors has generated widespread scientific interest. The new generation of flexible materials should be combined with superior mechanical properties, high conductivity, transparency, sensitivity, good self-restoring fatigue properties, and other multifunctional characteristics, while the current materials are difficult to meet these requirements. Herein, we prepared poly(acrylamide-acrylic acid) (P(AM-AA))/gelatin/glycerol-Al3+ (PG1G2A) ionic conducting hydrogel by one-pot polymerization under UV light. The prepared PG1G2A ionic conductive hydrogel had high tensile strength (539.18 kPa), excellent tensile property (1412.96%), good fast self-recovery and fatigue resistance, high transparency (>80%), excellent moisturizing, and antifreezing/drying properties. In addition, the ionic conductive hydrogel-based strain sensor can respond to mechanical stimulation and generate accurate, stable, and recyclable electrical signals, with excellent sensitivity (GF 5.81). In addition, the PG1G2A hydrogel could be used as flexible wearable devices for monitoring multiple strain and subtle movements of different body parts at different temperatures. Interestingly, the PG1G2A hydrogel capacitive pen embedded in the mold can be used to write and draw on the screen of a phone or tablet. This new multifunctional ionic conducting hydrogel shows broad application prospects in E-skin, motion monitoring, and human-computer interaction in extreme environments.

Microfluidic Wearable Devices for Sports Applications

This study aimed to systematically review the application and research progress of flexible microfluidic wearable devices in the field of sports. The research team thoroughly investigated the use of life signal-monitoring technology for flexible wearable devices in the domain of sports. In addition, the classification of applications, the current status, and the developmental trends of similar products and equipment were evaluated. Scholars expect the provision of valuable references and guidance for related research and the development of the sports industry. The use of microfluidic detection for collecting biomarkers can mitigate the impact of sweat on movements that are common in sports and can also address the issue of discomfort after prolonged use. Flexible wearable gadgets are normally utilized to monitor athletic performance, rehabilitation, and training. Nevertheless, the research and development of such devices is limited, mostly catering to professional athletes. Devices for those who are inexperienced in sports and disabled populations are lacking. Conclusions: Upgrading microfluidic chip technology can lead to accurate and safe sports monitoring. Moreover, the development of multi-functional and multi-site devices can provide technical support to athletes during their training and competitions while also fostering technological innovation in the field of sports science.

3D-printed epifluidic electronic skin for machine learning-powered multimodal health surveillance

The amalgamation of wearable technologies with physiochemical sensing capabilities promises to create powerful interpretive and predictive platforms for real-time health surveillance. However, the construction of such multimodal devices is difficult to be implemented wholly by traditional manufacturing techniques for at-home personalized applications. Here, we present a universal semisolid extrusion-based three-dimensional printing technology to fabricate an epifluidic elastic electronic skin (e3-skin) with high-performance multimodal physiochemical sensing capabilities. We demonstrate that the e3-skin can serve as a sustainable surveillance platform to capture the real-time physiological state of individuals during regular daily activities. We also show that by coupling the information collected from the e3-skin with machine learning, we were able to predict an individual's degree of behavior impairments (i.e., reaction time and inhibitory control) after alcohol consumption. The e3-skin paves the path for future autonomous manufacturing of customizable wearable systems that will enable widespread utility for regular health monitoring and clinical applications.

Recent advances in wearable sensors and data analytics for continuous monitoring and analysis of biomarkers and symptoms related to COVID-19

The COVID-19 pandemic has changed the lives of many people around the world. Based on the available data and published reports, most people diagnosed with COVID-19 exhibit no or mild symptoms and could be discharged home for self-isolation. Considering that a substantial portion of them will progress to a severe disease requiring hospitalization and medical management, including respiratory and circulatory support in the form of supplemental oxygen therapy, mechanical ventilation, vasopressors, etc. The continuous monitoring of patient conditions at home for patients with COVID-19 will allow early determination of disease severity and medical intervention to reduce morbidity and mortality. In addition, this will allow early and safe hospital discharge and free hospital beds for patients who are in need of admission. In this review, we focus on the recent developments in next-generation wearable sensors capable of continuous monitoring of disease symptoms, particularly those associated with COVID-19. These include wearable non/minimally invasive biophysical (temperature, respiratory rate, oxygen saturation, heart rate, and heart rate variability) and biochemical (cytokines, cortisol, and electrolytes) sensors, sensor data analytics, and machine learning-enabled early detection and medical intervention techniques. Together, we aim to inspire the future development of wearable sensors integrated with data analytics, which serve as a foundation for disease diagnostics, health monitoring and predictions, and medical interventions.

A Computationally Assisted Approach for Designing Wearable Biosensors toward Non-Invasive Personalized Molecular Analysis

Wearable sweat sensors have the potential to revolutionize precision medicine as they can non-invasively collect molecular information closely associated with an individual's health status. However, the majority of clinically relevant biomarkers cannot be continuously detected in situ using existing wearable approaches. Molecularly imprinted polymers (MIPs) are a promising candidate to address this challenge but haven't yet gained widespread use due to their complex design and optimization process yielding variable selectivity. Here, QuantumDock is introduced, an automated computational framework for universal MIP development toward wearable applications. QuantumDock utilizes density functional theory to probe molecular interactions between monomers and the target/interferent molecules to optimize selectivity, a fundamentally limiting factor for MIP development toward wearable sensing. A molecular docking approach is employed to explore a wide range of known and unknown monomers, and to identify the optimal monomer/cross-linker choice for subsequent MIP fabrication. Using an essential amino acid phenylalanine as the exemplar, experimental validation of QuantumDock is performed successfully using solution-synthesized MIP nanoparticles coupled with ultraviolet-visible spectroscopy. Moreover, a QuantumDock-optimized graphene-based wearable device is designed that can perform autonomous sweat induction, sampling, and sensing. For the first time, wearable non-invasive phenylalanine monitoring is demonstrated in human subjects toward personalized healthcare applications.

Wearable sweat analysis to determine biological age

A real-time, noninvasive, and clinically applicable aging test in humans has yet to be established. Herein we propose a sweat- and wearable-based test to determine biological age. This test would empower users to monitor their aging process and take an active role in managing their lifestyle and health.

Fibrous wearable and implantable bioelectronics

Fibrous wearable and implantable devices have emerged as a promising technology, offering a range of new solutions for minimally invasive monitoring of human health. Compared to traditional biomedical devices, fibers offer a possibility for a modular design compatible with large-scale manufacturing and a plethora of advantages including mechanical compliance, breathability, and biocompatibility. The new generation of fibrous biomedical devices can revolutionize easy-to-use and accessible health monitoring systems by serving as building blocks for most common wearables such as fabrics and clothes. Despite significant progress in the fabrication, materials, and application of fibrous biomedical devices, there is still a notable absence of a comprehensive and systematic review on the subject. This review paper provides an overview of recent advancements in the development of fibrous wearable and implantable electronics. We categorized these advancements into three main areas: manufacturing processes, platforms, and applications, outlining their respective merits and limitations. The paper concludes by discussing the outlook and challenges that lie ahead for fiber bioelectronics, providing a holistic view of its current stage of development.

Artificial intelligence enabled smart digital eye wearables

PURPOSE OF REVIEW

Smart eyewear is a head-worn wearable device that is evolving as the next phase of ubiquitous wearables. Although their applications in healthcare are being explored, they have the potential to revolutionize teleophthalmology care. This review highlights their applications in ophthalmology care and discusses future scope.

RECENT FINDINGS

Smart eyewear equips advanced sensors, optical displays, and processing capabilities in a wearable form factor. Rapid technological developments and the integration of artificial intelligence are expanding their reach from consumer space to healthcare applications. This review systematically presents their applications in treating and managing eye-related conditions. This includes remote assessments, real-time monitoring, telehealth consultations, and the facilitation of personalized interventions. They also serve as low-vision assistive devices to help visually impaired, and can aid physicians with operational and surgical tasks.

SUMMARY

Wearables such as smart eyewear collects rich, continuous, objective, individual-specific data, which is difficult to obtain in a clinical setting. By leveraging sophisticated data processing and artificial intelligence based algorithms, these data can identify at-risk patients, recognize behavioral patterns, and make timely interventions. They promise cost-effective and personalized treatment for vision impairments in an effort to mitigate the global burden of eye-related conditions and aging.

Flexible and Stretchable Electrochemical Sensors for Biological Monitoring

The rise of flexible and stretchable electronics has revolutionized biosensor techniques for probing biological systems. Particularly, flexible and stretchable electrochemical sensors (FSECSs) enable the in situ quantification of numerous biochemical molecules in different biological entities owing to their exceptional sensitivity, fast response, and easy miniaturization. Over the past decade, the fabrication and application of FSECSs have significantly progressed. This review highlights key developments in electrode fabrication and FSECSs functionalization. It delves into the electrochemical sensing of various biomarkers, including metabolites, electrolytes, signaling molecules, and neurotransmitters from biological systems, encompassing the outer epidermis, tissues/organs in vitro and in vivo, and living cells. Finally, considering electrode preparation and biological applications, current challenges and future opportunities for FSECSs are discussed.

Flexible thermoelectric generator and energy management electronics powered by body heat

Uninterrupted, efficient power supplies have posed a significant hurdle to the ubiquitous adoption of wearable devices, despite their potential for revolutionizing human‒machine interactions. This challenge is further compounded by the requirement of these devices to supply dependable energy for data-intensive sensing and transmission. Traditional thermoelectric solutions fail to deliver satisfactory performance under conditions of extremely low voltages. Here, we present a novel solution of a wearable thermoelectric generator integrated with an energy management system, which is capable of powering sensors and Bluetooth by harnessing body heat. Distinct from previous works, our innovation lies in its ability to consistently operate even with a minimal temperature difference (i.e., 4 K) between the human skin and the ambient environment, ensuring reliable data transmission within a time as short as 1.6 s. Furthermore, our system can recharge utilizing body heat under ultralow voltage conditions (30 mV). Our developed system provides a novel pathway for the continuous, reliable monitoring of self-contained wearable devices without depending on batteries.