Nanomaterial-assisted wearable glucose biosensors for noninvasive real-time monitoring:Pioneering point-of-care and beyond

This review explores glucose monitoring and management strategies,emphasizing the need for reliable and userfriendly wearable sensors that are the next generation of sensors for continuous glucose detection.In addition,examines key strategies for designing glucose sensors that are multi-functional,reliable,and cost-effective in a variety of contexts.The unique features of effective diabetes management technology are highlighted,with a focus on using nano/biosensor devices that can quickly and accurately detect glucose levels in the blood,improving patient treatment and control of potential diabetes-related infections.The potential of next-generation wearable and touch-sensitive nano biomedical sensor engineering designs for providing full control in assessing implantable,continuous glucose monitoring is also explored.The challenges of standardizing drug or insulin delivery doses,low-cost,real-time detection of increased blood sugar levels in diabetics,and early digital health awareness controls for the adverse effects of injectable medication are identified as unmet needs.Also,the market for biosensors is expected to expand significantly due to the rising need for portable diagnostic equipment and an ever-increasing diabetic population.The paper concludes by emphasizing the need for further research and development of glucose biosensors to meet the stringent requirements for sensitivity and specificity imposed by clinical diagnostics while being cost-effective,stable,and durable.

Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

Wearable multilead ECG sensing systems using on-skin stretchable and breathable dry adhesives

Electrocardiogram(ECG)monitoring is used to diagnose cardiovascular diseases,for which wearable electronics have attracted much attention due to their lightweight,comfort,and long-term use.This study developed a wearablemultilead ECG sensing system with on-skin stretchable and conductive silver(Ag)-coated fiber/silicone(AgCF-S)dry adhesives.Tangential and normal adhesion to pigskin(0.43 and 0.20 N/cm2,respectively)was optimized by the active control of fiber density and mixing ratio,resulting in close contact in the electrode–skin interface.The breathableAgCF-S dry electrodewas nonallergenic after continuous fit for 24 h and can be reused/cleaned(>100 times)without loss of adhesion.The AgCF encapsulated inside silicone elastomers was overlapped to construct a dynamic network under repeated stretching(10%strain)and bending(90°)deformations,enabling small intrinsic impedance(0.3,0.1 Hz)and contact impedance variation(0.7 k)in high-frequency vibration(70 Hz).All hard/soft modules of the multilead ECG system were integrated into lightweight clothing and equipped with wireless transmission for signal visualization.By synchronous acquisition of I–III,aVR,aVL,aVF,and V4 lead data,the multilead ECG sensing system was suitable for various scenarios,such as exercise,rest,and sleep,with extremely high signal-to-noise ratios.

Measuring Pedestrian Stress Response (MPSR) Using Wearable Technologies

Walkability is an essential aspect of urban transportation systems. Properly designed walking paths can enhance transportation safety, encourage pedestrian activity, and improve community quality of life. This, in turn, can help achieve sustainable development goals in urban areas. This pilot study uses wearable technology data to present a new method for measuring pedestrian stress in urban environments and the results were presented as an interactive geographic information system map to support risk-informed decision-making. The approach involves analyzing data from wearable devices using heart rate variability (RMSSD and slope analysis) to identify high-stress locations. This data-driven approach can help urban planners and safety experts identify and address pedestrian stressors, ultimately creating safer, more walkable cities. The study addresses a significant challenge in pedestrian safety by providing insights into factors and locations that trigger stress in pedestrians. During the pilot study, high-stress pedestrian experiences were identified due to issues like pedestrian-scooter interaction on pedestrian paths, pedestrian behavior around high foot traffic areas, and poor visibility at pedestrian crossings due to inadequate lighting.

Wearable Inflatable Massage Chair:The Future of Comfort

With the continuous advancement of science and technology,our lifestyles are undergoing significant changes,with wearable technology emerging as a captivating trend.In this digital era,there is a growing demand for solutions that cater to people’s needs for health and comfort.The wearable inflatable massage chair represents one such innovation designed to meet these evolving needs.This project is focused on creating a“wearable and portable massage chair”that is both convenient and lightweight.It serves as a massage solution particularly beneficial for the elderly and sedentary individuals.This innovative chair can be used by the elderly during outings or errands,as well as by office workers on business trips,while driving,or commuting via subway.Users can simply lean against the seat or a wall,enjoying moments of relaxation amid the busy and fast-paced modern era.

Personalized Health Monitoring Systems: Integrating Wearable and AI

The integration of wearable technologies and artificial intelligence (AI) has revolutionized healthcare, enabling advanced personal health monitoring systems. This article explores the transformative impact of wearable technologies and AI on healthcare, highlighting the development and theoretical application of the Integrated Personal Health Monitoring System (IPHMS). By integrating data from various wearable devices, such as smartphones, Apple Watches, and Oura Rings, the IPHMS framework aims to revolutionize personal health monitoring through real-time alerts, comprehensive tracking, and personalized insights. Despite its potential, the practical implementation faces challenges, including data privacy, system interoperability, and scalability. The evolution of healthcare technology from traditional methods to AI-enhanced wearables underscores a significant advancement towards personalized care, necessitating further research and innovation to address existing limitations and fully realize the benefits of such integrated health monitoring systems.

Functional Materials and Innovative Strategies for Wearable Thermal Management Applications

Thermal management is essential in our body as it affects various bodily functions,ranging from thermal discomfort to serious organ failures,as an example of the worst-case scenario.There have been extensive studies about wearable materials and devices that augment thermoregulatory functionalities in our body,employing diverse materials and systematic approaches to attaining thermal homeostasis.This paper reviews the recent progress of functional materials and devices that contribute to thermoregulatory wearables,particularly emphasizing the strategic methodology to regulate body temperature.There exist several methods to promote personal thermal management in a wearable form.For instance,we can impede heat transfer using a thermally insulating material with extremely low thermal conductivity or directly cool and heat the skin surface.Thus,we classify many studies into two branches,passive and active thermal management modes,which are further subdivided into specific strategies.Apart from discussing the strategies and their mechanisms,we also identify the weaknesses of each strategy and scrutinize its potential direction that studies should follow to make substantial contributions to future thermal regulatory wearable industries.

Engineering Smart Composite Hydrogels for Wearable Health Monitoring

Growing health awareness triggers the public's concern about health problems. People want a timely and comprehensive picture of their condition without frequent trips to the hospital for costly and cumbersome general check-ups. The wearable technique provides a continuous measurement method for health monitoring by tracking a person's physiological data and analyzing it locally or remotely.During the health monitoring process,different kinds of sensors convert physiological signals into electrical or optical signals that can be recorded and transmitted, consequently playing a crucial role in wearable techniques. Wearable application scenarios usually require sensors to possess excellent flexibility and stretchability. Thus, designing flexible and stretchable sensors with reliable performance is the key to wearable technology. Smart composite hydrogels, which have tunable electrical properties, mechanical properties, biocompatibility, and multi-stimulus sensitivity, are one of the best sensitive materials for wearable health monitoring. This review summarizes the common synthetic and performance optimization strategies of smart composite hydrogels and focuses on the current application of smart composite hydrogels in the field of wearable health monitoring.

A Thermoregulatory Flexible Phase Change Nonwoven for All‑Season High‑Efficiency Wearable Thermal Management

Phase change materials have a key role for wearable thermal management,but suffer from poor water vapor permeability,low enthalpy value and weak shape stability caused by liquid phase leakage and intrinsic rigidity of solid–liquid phase change materials.Herein,we report for the first time a versatile strategy for designed assembly of high-enthalpy flexible phase change nonwovens(GB-PCN)by wet-spinning hybrid grapheneboron nitride(GB)fiber and subsequent impregnating paraffins(e.g.,eicosane,octadecane).As a result,our GB-PCN exhibited an unprecedented enthalpy value of 206.0 J g^(−1),excellent thermal reliability and anti-leakage capacity,superb thermal cycling ability of 97.6%after 1000 cycles,and ultrahigh water vapor permeability(close to the cotton),outperforming the reported PCM films and fibers to date.Notably,the wearable thermal management systems based on GB-PCN for both clothing and face mask were demonstrated,which can maintain the human body at a comfortable temperature range for a significantly long time.Therefore,our results demonstrate huge potential of GB-PCN for human-wearable passive thermal management in real scenarios.

Recent progress in graphene-based wearable piezoresistive sensors:From 1D to 3D device geometries

Electronic skin and flexible wearable devices have attracted tremendous attention in the fields of human-machine interaction,energy storage,and intelligent robots.As a prevailing flexible pressure sensor with high performance,the piezoresistive sensor is believed to be one of the fundamental components of intelligent tactile skin.Furthermore,graphene can be used as a building block for highly flexible and wearable piezoresistive sensors owing to its light weight,high electrical conductivity,and excellent mechanical.This review provides a comprehensive summary of recent advances in graphene-based piezoresistive sensors,which we systematically classify as various configurations including one-dimensional fiber,two-dimensional thin film,and threedimensional foam geometries,followed by examples of practical applications for health monitoring,human motion sensing,multifunctional sensing,and system integration.We also present the sensing mechanisms and evaluation parameters of piezoresistive sensors.This review delivers broad insights on existing graphene-based piezoresistive sensors and challenges for the future generation of high-performance,multifunctional sensors in various applications.

Integrated photonic convolution acceleration core for wearable devices

With the advancement of deep learning and neural networks,the computational demands for applications in wearable devices have grown exponentially.However,wearable devices also have strict requirements for long battery life,low power consumption,and compact size.In this work,we propose a scalable optoelectronic computing system based on an integrated optical convolution acceleration core.This system enables high-precision computation at the speed of light,achieving 7-bit accuracy while maintaining extremely low power consumption.It also demonstrates peak throughput of 3.2 TOPS(tera operations per second)in parallel processing.We have successfully demonstrated image convolution and the typical application of an interactive first-person perspective gesture recognition application based on depth information.The system achieves a comparable recognition accuracy to traditional electronic computation in all blind tests.

Rational Design of Cellulosic Triboelectric Materials for Self‑Powered Wearable Electronics

With the rapid development of the Internet of Things and flexible electronic technologies,there is a growing demand for wireless,sustainable,multifunctional,and independently operating self-powered wearable devices.Nevertheless,structural flexibility,long operating time,and wearing comfort have become key requirements for the widespread adoption of wearable electronics.Triboelectric nanogenerators as a distributed energy harvesting technology have great potential for application development in wearable sensing.Compared with rigid electronics,cellulosic self-powered wearable electronics have significant advantages in terms of flexibility,breathability,and functionality.In this paper,the research progress of advanced cellulosic triboelectric materials for self-powered wearable electronics is reviewed.The interfacial characteristics of cellulose are introduced from the top-down,bottom-up,and interfacial characteristics of the composite material preparation process.Meanwhile,the modulation strategies of triboelectric properties of cellulosic triboelectric materials are presented.Furthermore,the design strategies of triboelectric materials such as surface functionalization,interfacial structure design,and vacuum-assisted self-assembly are systematically discussed.In particular,cellulosic self-powered wearable electronics in the fields of human energy harvesting,tactile sensing,health monitoring,human–machine interaction,and intelligent fire warning are outlined in detail.Finally,the current challenges and future development directions of cellulosic triboelectric materials for self-powered wearable electronics are discussed.

Wearable sweat biosensors on textiles for health monitoring

With the rapid technological innovation in materials engineering and device integration,a wide variety of textilebased wearable biosensors have emerged as promising platforms for personalized healthcare,exercise monitoring,and pre-diagnostics.This paper reviews the recent progress in sweat biosensors and sensing systems integrated into textiles for wearable body status monitoring.The mechanisms of biosensors that are commonly adopted for biomarkers analysis are first introduced.The classification,fabrication methods,and applications of textile conductors in different configurations and dimensions are then summarized.Afterward,innovative strategies to achieve efficient sweat collection with textile-based sensing patches are presented,followed by an in-depth discussion on nanoengineering and system integration approaches for the enhancement of sensing performance.Finally,the challenges of textile-based sweat sensing devices associated with the device reusability,washability,stability,and fabrication reproducibility are discussed from the perspective of their practical applications in wearable healthcare.

Functionalized Hydrogel-Based Wearable Gas and Humidity Sensors

Breathing is an inherent human activity;however,the composition of the air we inhale and gas exhale remains unknown to us.To address this,wearable vapor sensors can help people monitor air composition in real time to avoid underlying risks,and for the early detection and treatment of diseases for home healthcare.Hydrogels with three-dimensional polymer networks and large amounts of water molecules are naturally flexible and stretchable.Functionalized hydrogels are intrinsically conductive,self-healing,self-adhesive,biocompatible,and room-temperature sensitive.Compared with traditional rigid vapor sensors,hydrogel-based gas and humidity sensors can directly fit human skin or clothing,and are more suitable for real-time monitoring of personal health and safety.In this review,current studies on hydrogel-based vapor sensors are investigated.The required properties and optimization methods of wearable hydrogel-based sensors are introduced.Subsequently,existing reports on the response mechanisms of hydrogel-based gas and humidity sensors are summarized.Related works on hydrogel-based vapor sensors for their application in personal health and safety monitoring are presented.Moreover,the potential of hydrogels in the field of vapor sensing is elucidated.Finally,the current research status,challenges,and future trends of hydrogel gas/humidity sensing are discussed.

Wearable and stretchable conductive polymer composites for strain sensors:How to design a superior one?

Wearable and stretchable strain sensors have potential values in the fields of human motion and health monitoring,flexible electronics,and soft robotic skin.The wearable and stretchable strain sensors can be directly attached to human skin,providing visualized detection for human motions and personal healthcare.Conductive polymer composites(CPC)composed of conductive fillers and flexible polymers have the advantages of high stretchability,good flexibility,superior durability,which can be used to prepare flexible strain sensors with large working strain and outstanding sensitivity.This review has put forward a comprehensive summary on the fabrication methods,advanced mechanisms and strain sensing abilities of CPC strain sensors reported in recent years,especially the sensors with superior performance.Finally,the structural design,bionic function,integration technology and further application of CPC strain sensors are prospected.

Inducing Fe 3d Electron Delocalization and Spin‑State Transition of FeN_(4) Species Boosts Oxygen Reduction Reaction for Wearable Zinc–Air Battery

Transition metal-nitrogen-carbon materials(M-N-Cs),particularly Fe-N-Cs,have been found to be electroactive for accelerating oxygen reduction reaction(ORR)kinetics.Although substantial efforts have been devoted to design Fe-N-Cs with increased active species content,surface area,and electronic conductivity,their performance is still far from satisfactory.Hitherto,there is limited research about regulation on the electronic spin states of Fe centers for Fe-N-Cs electrocatalysts to improve their catalytic performance.Here,we introduce Ti_(3)C_(2) MXene with sulfur terminals to regulate the electronic configuration of FeN_(4) species and dramatically enhance catalytic activity toward ORR.The MXene with sulfur terminals induce the spin-state transition of FeN_(4) species and Fe 3d electron delocalization with d band center upshift,enabling the Fe(II)ions to bind oxygen in the end-on adsorption mode favorable to initiate the reduction of oxygen and boosting oxygen-containing groups adsorption on FeN_(4) species and ORR kinetics.The resulting FeN_(4)-Ti_(3)C_(2)Sx exhibits comparable catalytic performance to those of commercial Pt-C.The developed wearable ZABs using FeN_(4)-Ti_(3)C_(2)Sx also exhibit fast kinetics and excellent stability.This study confirms that regulation of the electronic structure of active species via coupling with their support can be a major contributor to enhance their catalytic activity.

Review:Wearable Sweat Sensors for Diseases Prevention and Monitoring

Advanced in wireless technologies and flexible materials with great biocompatibility,wearable devices have been utilized in the field of healthcare,sports management,and diseases prevention,which have been widely applied in current electronic equipment.Sweat,as a common metabolite on the skin surface,contains a wealth of biomarkers for disease detection and diagnosis.Therefore,developing wearable sweat sensors can provide a non⁃invasive method for health data collecting,sports monitoring,and clinical diagnosis in a convenient way.Recent research in sweat metabolomics has offered a lot of information for sweat analysis and the wearable sweat sensors with small size,various sensing,and transmission units,and good skin contact has exhibited dynamic multi⁃signal detection.This article introduces the biomarkers in sweat related to different diseases and the current development of sweat sensors for user􀆳s activation monitoring and diseases detection.The barriers and difficulties in the future are also discussed and perspectives in the next generation sweat sensors are proposed.

Automatic Recognition of Construction Worker Activities Using Deep Learning Approaches and Wearable Inertial Sensors

The automated evaluation and analysis of employee behavior in an Industry 4.0-compliant manufacturingfirm are vital for the rapid and accurate diagnosis of work performance,particularly during the training of a new worker.Various techniques for identifying and detecting worker performance in industrial applications are based on computer vision techniques.Despite widespread com-puter vision-based approaches,it is challenging to develop technologies that assist the automated monitoring of worker actions at external working sites where cam-era deployment is problematic.Through the use of wearable inertial sensors,we propose a deep learning method for automatically recognizing the activities of construction workers.The suggested method incorporates a convolutional neural network,residual connection blocks,and multi-branch aggregate transformation modules for high-performance recognition of complicated activities such as con-struction worker tasks.The proposed approach has been evaluated using standard performance measures,such as precision,F1-score,and AUC,using a publicly available benchmark dataset known as VTT-ConIoT,which contains genuine con-struction work activities.In addition,standard deep learning models(CNNs,RNNs,and hybrid models)were developed in different empirical circumstances to compare them to the proposed model.With an average accuracy of 99.71%and an average F1-score of 99.71%,the experimentalfindings revealed that the suggested model could accurately recognize the actions of construction workers.Furthermore,we examined the impact of window size and sensor position on the identification efficiency of the proposed method.

Deep Pyramidal Residual Network for Indoor-Outdoor Activity Recognition Based on Wearable Sensor

Recognition of human activity is one of the most exciting aspects of time-series classification,with substantial practical and theoretical impli-cations.Recent evidence indicates that activity recognition from wearable sensors is an effective technique for tracking elderly adults and children in indoor and outdoor environments.Consequently,researchers have demon-strated considerable passion for developing cutting-edge deep learning sys-tems capable of exploiting unprocessed sensor data from wearable devices and generating practical decision assistance in many contexts.This study provides a deep learning-based approach for recognizing indoor and outdoor movement utilizing an enhanced deep pyramidal residual model called Sen-PyramidNet and motion information from wearable sensors(accelerometer and gyroscope).The suggested technique develops a residual unit based on a deep pyramidal residual network and introduces the concept of a pyramidal residual unit to increase detection capability.The proposed deep learning-based model was assessed using the publicly available 19Nonsens dataset,which gathered motion signals from various indoor and outdoor activities,including practicing various body parts.The experimental findings demon-strate that the proposed approach can efficiently reuse characteristics and has achieved an identification accuracy of 96.37%for indoor and 97.25%for outdoor activity.Moreover,comparison experiments demonstrate that the SenPyramidNet surpasses other cutting-edge deep learning models in terms of accuracy and F1-score.Furthermore,this study explores the influence of several wearable sensors on indoor and outdoor action recognition ability.

Higher Order OAM Mode Generation Using Wearable Antenna for 5G NR Bands

This paper presents a flexible and wearable textile array antenna designed to generate Orbital Angular Momentum(OAM)waves with Mode+2 at 3.5 GHz(3.4 to 3.6 GHz)of the sub-6 GHz fifth-generation(5G)New Radio(NR)band.The proposed antenna is based on a uniform circular array of eight microstrip patch antennas on a felt textile substrate.In contrast to previous works involving the use of rigid substrates to generate OAM waves,this work explored the use of flexible substrates to generate OAM waves for the first time.Other than that,the proposed antenna was simulated,analyzed,fabricated,and tested to confirm the generation of OAMMode+2.With the same design,OAM Mode−2 can be generated readily simply by mirror imaging the feed network.Note that the proposed antenna operated at the desired frequency of 3.5 GHz with an overall bandwidth of 400 MHz in free space.Moreover,mode purity analysis is carried out to verify the generation of OAM Mode+2,and the purity obtained was 41.78%at free space flat condition.Furthermore,the effect of antenna bending on the purity of the generated OAM mode is also investigated.Lastly,the influence of textile properties on OAM modes is examined to assist future researchers in choosing suitable fabrics to design flexible OAM-based antennas.After a comprehensive analysis considering different factors related to wearable applications,this paper demonstrates the feasibility of generating OAMwaves using textile antennas.Furthermore,as per the obtained Specific Absorption Rate(SAR),it is found that the proposed antenna is safe to be deployed.The findings of this work have a significant implication for body-centric communications.