Recent Advances in Multifunctional Wearable Sensors and Systems: Design, Fabrication, and Applications

Wearable textile sensors for continuous glucose monitoring

Diabetes and cardiovascular disease are interlinked chronic conditions that necessitate continuous and precise monitoring of physiological and environmental parameters to prevent complications. Non-invasive monitoring technologies have garnered significant interest due to their potential to alleviate the current burden of diabetes and cardiovascular disease management. However, these technologies face limitations in accuracy and reliability due to interferences from physiological and environmental factors. This review investigates electronic textiles (e-textiles) that integrate biomedical sensors into wearable fabrics that can enable a multimodal platform for non-invasive continuous glucose monitoring (CGM). Current advancements in e-textiles show the potential of four key methods for glucose monitoring: optical, biochemical, biomechanical, and thermal sensing techniques. Biochemical sensing through sweat-based glucose detection has demonstrated potential for accurate and non-invasive monitoring but still faces numerous challenges. While optical, biomechanical and thermal sensing are less explored in e-textiles, they offer additional physiological and environmental insights that can improve the precision of glucose readings by providing cross-validation of data. This review proposes that integrating multiple sensing modalities into a single multimodal e-textile wearable can address the accuracy and reliability challenges by providing cross-validation of data. The development of such multimodal e-textiles has the potential to revolutionise diabetes and cardiovascular disease management by providing continuous, accurate, and holistic monitoring in real-time, which could significantly improve patient outcomes and quality of life. Further research and development are crucial to fully realise the potential of these integrated systems in clinical and everyday settings.

Miniaturized Wearable Biosensors for Continuous Health Monitoring Fabricated Using the Femtosecond Laser-Induced Graphene Surface and Encapsulated Traces and Electrodes

Wearable sensors are increasingly being used as biosensors for health monitoring. Current wearable devices are large, heavy, invasive, skin irritants, or not continuous. Miniaturization was chosen to address these issues, using a femtosecond laser-conversion technique to fabricate miniaturized laser-induced graphene (LIG) sensor arrays on and encapsulated within a polyimide substrate. The femtosecond laser-converted conductive traces can have a size of 20 to 2 μm compared to the traditionally larger CO2 laser dimensions of around 300 to 100 μm. This marks a 93-98% decrease in trace size when using a femtosecond laser. This miniaturization allows for the ability to process temperature, electrocardiography (ECG), electromyography (EMG), and glucose data in the same space that would have been occupied by a single sensor. The femtosecond laser-converted graphene (FSLIG) electrodes were modified to function as glucose sensors, and comprehensive electrochemical analyses using cyclic voltammetry (CV) and chronoamperometry (CA) were performed. These tests confirmed the capability of the sensors to detect glucose levels, showing a stability of 96.14%. Encapsulation of FSLIG within polyimide was achieved for the first time, demonstrating the ability to nondestructively create FSLIG electrodes within existing materials, thereby protecting them from external environmental factors. The encapsulated FSLIG shows potential as a method to produce LIG-coated Cu traces for improved multilayered printed circuit boards or layered circuits with complex geometries in polyamide to reduce size and increase functionality. Even sterile probes for use inside the body or under dermis polyamide injections and subsequent FSLIG circuit tattoos are possible. This study demonstrates the novel miniaturization and encapsulation capabilities enabled by the femtosecond laser, developing next-generation wearable biosensors focusing on miniaturization, flexibility, continuous monitoring, multifunctionality, and comfort.

Vertical Graphene-Based Multiparametric Sensing Array for Integration of Smart Catheter to Electrochemically Monitor Peritoneal Dialysis

Renal failure is typical chronic kidney disease that required peritoneal dialysis as the primary treatment, but current catheter devices lack functionality to monitor changes in chemical analytes during peritoneal dialysis. Fabrication of miniatured sensing modules with good electrochemical performance in tiny catheter devices is the key to realize the smart monitoring of peritoneal dialysis. In this work, a vertical graphene-based multiparametric sensing array (VG-MSA) is developed to continuously measure fluctuations of various analyte concentrations for peritoneal dialysis monitoring. Vertical graphene (VG) electrode with good electrochemical properties serves as the core module in VG-MSA, allowing the development of miniatured sensing modules with sufficient electrochemical performance. The VG-MSA enables sensitive and multiplexed measurement of dialysate components like metabolites (reactive oxygen species, uric acid, and glucose) and ions (K+, Ca2+, and H+). The VG-MSA is demonstrated to effectively detect biochemical signals in peritoneal dialysate in vivo on rat models. The VG-MSA catheter can be inserted into abdominal cavity, allowing full contact with dialysate for in situ, real-time, and continuous collection of biochemical information during peritoneal dialysis. The VG-MSA catheter device offers a valuable tool for monitoring dialysis quality and facilitating treatment adjustments, potentially as a promising platform for high-quality therapy of renal failure.

New Carbon Materials for Multifunctional Soft Electronics

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

Leather-Based Shoe Soles for Real-Time Gait Recognition and Automatic Remote Assistance Using Machine Learning

Real-time monitoring of gait characteristics is crucial for applications in health monitoring, patient rehabilitation feedback, and telemedicine. However, the effective and stable acquisition and automatic analysis of gait information remain significant challenges. In this study, we present a flexible sensor based on a carbon nanotube/graphene composite conductive leather (CGL), which uses collagen fiber with a three-dimensional network structure as the flexible substrate. The CGL-based sensor demonstrates a high dynamic range, with notable pressure responses ranging from 0.6 to 14.5 kPa and high sensitivity (S = 0.2465 kPa-1). We further developed a device incorporating the CGL-based sensor to collect foot characteristic signals from human motion and designed smart sports shoes to facilitate effective human-computer interaction. Machine learning was employed to collect and process gait characteristic information in various states, including standing, sitting, walking, and falling. For real-time monitoring of falls, we optimized the K-Nearest Time Series Classifier (KNTC) algorithm, achieving an accuracy of 0.99 and a prediction time of only 13 ms, which highlights the system's excellent intelligent response capabilities. The system maintained a gait recognition accuracy of 90% across diverse populations, with low false-positive (3.3%) and false-negative (3.3%) rates. This work demonstrates stable gait recognition capabilities and provides valuable methods and insights for plantar behavior monitoring and data analysis, contributing to the development of advanced real-time gait monitoring systems.

Advancements in Airborne Viral Nucleic Acid Detection with Wearable Devices

Wearable health sensors for an expanding range of physiological parameters have experienced rapid development in recent years and are poised to disrupt the way healthcare is tracked and administered. The monitoring of environmental contaminants with wearable technologies is an additional layer of personal and public healthcare and is also receiving increased focus. Wearable sensors that detect exposure to airborne viruses could alert wearers of viral exposure and prompt proactive testing and minimization of viral spread, benefitting their own health and decreasing community risk. With the high levels of asymptomatic spread of COVID-19 observed during the pandemic, such devices could dramatically enhance our pandemic response capabilities in the future. To facilitate advancements in this area, this review summarizes recent research on airborne viral detection using wearable sensing devices as well as technologies suitable for wearables. Since the low concentration of viral particles in the air poses significant challenges to detection, methods for airborne viral particle collection and viral sensing are discussed in detail. A special focus is placed on nucleic acid-based viral sensing mechanisms due to their enhanced ability to discriminate between viral subtypes. Important considerations for integrating airborne viral collection and sensing on a single wearable device are also discussed.

Engineering of graphene-based composites with hexagonal boron nitride and PEDOT:PSS for sensing applications

A unique nanomaterial has been developed for sweat analysis, including glucose level monitoring. Simple resusable low-cost sensors from composite materials based on graphene, hexagonal boron nitride, and conductive PEDOT:PSS (poly(3,4-ethylenedioxythiophene)polystyrene sulfonate) polymer have been developed and fabricated via 2D printing on flexible substrates. The sensors were tested as biosensors using different water-based solutions. A strong increase in the current response (several orders of magnitude) was observed for aqua vapors or glucose solution vapors. This property is associated with the sorption capacity of graphene synthesized in a volume of plasma jets and thus having many active centers on the surface. The structure and properties of graphene synthesized in a plasma are different from those of graphene created by other methods. As a result, the current response for a wearable sensor is 3-5 orders of magnitude higher for the reference blood glucose concentration range of 4-14 mM. It has been found that the most promising sensor with the highest response was fabricated based on the graphene:PEDOT:PSS composite. The graphene:h-BN:PEDOT:PSS (h-BN is hexagonal boron nitride) sensors demonstrated a longer response and the highest response after the functionalization of the sensors with a glucose oxidase enzyme. The reusable wearable graphene:PEDOT:PSS glucose sensors on a paper substrate demonstrated a current response of 10-10 to 10-5 A for an operating voltage of 0.5 V and glucose range of 4-10 mM.

Recent Advances in Nanowire-Based Wearable Physical Sensors

Wearable electronics is a technology that closely integrates electronic devices with the human body or clothing, which can realize human-computer interaction, health monitoring, smart medical, and other functions. Wearable physical sensors are an important part of wearable electronics. They can sense various physical signals from the human body or the surrounding environment and convert them into electrical signals for processing and analysis. Nanowires (NW) have unique properties such as a high surface-to-volume ratio, high flexibility, high carrier mobility, a tunable bandgap, a large piezoresistive coefficient, and a strong light-matter interaction. They are one of the ideal candidates for the fabrication of wearable physical sensors with high sensitivity, fast response, and low power consumption. In this review, we summarize recent advances in various types of NW-based wearable physical sensors, specifically including mechanical, photoelectric, temperature, and multifunctional sensors. The discussion revolves around the structural design, sensing mechanisms, manufacture, and practical applications of these sensors, highlighting the positive role that NWs play in the sensing process. Finally, we present the conclusions with perspectives on current challenges and future opportunities in this field.

The Application of Wearable Sensors and Machine Learning Algorithms in Rehabilitation Training: A Systematic Review

The integration of wearable sensor technology and machine learning algorithms has significantly transformed the field of intelligent medical rehabilitation. These innovative technologies enable the collection of valuable movement, muscle, or nerve data during the rehabilitation process, empowering medical professionals to evaluate patient recovery and predict disease development more efficiently. This systematic review aims to study the application of wearable sensor technology and machine learning algorithms in different disease rehabilitation training programs, obtain the best sensors and algorithms that meet different disease rehabilitation conditions, and provide ideas for future research and development. A total of 1490 studies were retrieved from two databases, the Web of Science and IEEE Xplore, and finally 32 articles were selected. In this review, the selected papers employ different wearable sensors and machine learning algorithms to address different disease rehabilitation problems. Our analysis focuses on the types of wearable sensors employed, the application of machine learning algorithms, and the approach to rehabilitation training for different medical conditions. It summarizes the usage of different sensors and compares different machine learning algorithms. It can be observed that the combination of these two technologies can optimize the disease rehabilitation process and provide more possibilities for future home rehabilitation scenarios. Finally, the present limitations and suggestions for future developments are presented in the study.

MXene nanomaterials in biomedicine: A bibliometric perspective

Purpose: MXene is two-dimensional (2D) nanomaterials that comprise transition metal carbides, nitrides, and carbonitrides. Their unique nanostructure attributes it a special role in medical applications. However, bibliometric studies have not been conducted in this field. Therefore, the aim of the present study was to conduct a bibliometric analysis to evaluate the global scientific output of MXene in biomedical research, explore the current situation of this field in the past years and predicte its research hotpots. Methods: We utilized visual analysis softwares Citespace and Bibliometrix to analyze all relevant documents published in the period of 2011-2022. The bibliometric records were obtained from the Web of Science Core Collection. Results: A total of 1,489 publications were analyzed in this study. We observed that China is the country with the largest number of publications, with Sichuan University being the institution with the highest number of publications in this field. The most publications on MXene medicine research in the past year were found primarily in journals about Chemistry/Materials/Physics. Moreover, ACS Applied Materials and Interfaces was found to be the most productive journal in this field. Co-cited references and keyword cluster analysis revealed that #antibacterial# and #photothermal therapy# are the research focus keyword and burst detection suggested that driven wearable electronics were newly-emergent research hot spots. Conclusion: Our bibliometric analysis indicates that research on MXene medical application remains an active field of study. At present, the research focus is on the application of MXene in the field of antibacterial taking advantage of its photothermal properties. In the future, wearable electronics is the research direction of MXene medical application.