Flexible Graphene Field‑Effect Transistors and Their Application in Flexible Biomedical Sensing

Flexible electronics are transforming our lives by making daily activities more convenient.Central to this innovation are field-effect transistors(FETs),valued for their efficient signal processing,nanoscale fabrication,low-power consumption,fast response times,and versatility.Graphene,known for its exceptional mechanical properties,high electron mobility,and biocompatibility,is an ideal material for FET channels and sensors.The combination of graphene and FETs has given rise to flexible graphene field-effect transistors(FGFETs),driving significant advances in flexible electronics and sparked a strong interest in flexible biomedical sensors.Here,we first provide a brief overview of the basic structure,operating mechanism,and evaluation parameters of FGFETs,and delve into their material selection and patterning techniques.The ability of FGFETs to sense strains and biomolecular charges opens up diverse application possibilities.We specifically analyze the latest strategies for integrating FGFETs into wearable and implantable flexible biomedical sensors,focusing on the key aspects of constructing high-quality flexible biomedical sensors.Finally,we discuss the current challenges and prospects of FGFETs and their applications in biomedical sensors.This review will provide valuable insights and inspiration for ongoing research to improve the quality of FGFETs and broaden their application prospects in flexible biomedical sensing.

A Fully‑Printed Wearable Bandage‑Based Electrochemical Sensor with pH Correction for Wound Infection Monitoring

Wearable sensing systems have been designed to monitor health conditions in real-time by detecting analytes in human biofluids.Wound diagnosis remains challenging,necessitating suitable materials for high-performance wearable sensors to offer prompt feedback.Existing devices have limitations in measuring pH and the concentration of pH-dependent electroactive species simultaneously,which is crucial for obtaining a comprehensive understanding of wound status and optimizing biosensors.Therefore,improving materials and analysis system accuracy is essential.This article introduces the first example of a flexible array capable of detecting pyocyanin,a bacterial virulence factor,while correcting dynamic pH fluctuations.We demonstrate that this combined sensor enhances accuracy by mitigating the impact of pH variability on pyocyanin sensor response.Customized screen-printable inks were developed to enhance analytical performance.The analytical performances of two sensitive sensor systems(i.e.,fully-printed porous graphene/multiwalled carbon nanotube(CNT)and polyaniline/CNT composites for pyocyanin and pH sensors)are evaluated.Partial least square regression is employed to analyze nonzero-order data arrays from square wave voltammetric and potentiometric measurements of pyocyanin and pH sensors to establish a predictive model for pyocyanin concentration in complex fluids.This sensitive and effective strategy shows potential for personalized applications due to its affordability,ease of use,and ability to adjust for dynamic pH changes.

A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily activities.Unlike existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple scenarios.It features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance output.Through wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist movements.Remarkably,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various tasks.The system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and letters.The proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific training.Its utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

Smart Gas Sensors:Recent Developments and Future Prospective

Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated feature.Various electronicand optoelectronic gas sensors have been developed for high-performancesmart gas analysis.With the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas analysis.This review highlights recent advances of smart gassensors in diverse applications.The structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are highlighted.Moreover,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are introduced.Finally,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.

可穿戴设备在卒中风险预测及卒中后管理中的应用进展

卒中是全球范围内导致死亡和残疾的主要疾病之一,传统的监测与管理手段已难以满足卒中高危人群及患者日益增长的健康管理需求。可穿戴设备凭借其实时性和便携性,为卒中风险预测和卒中后管理提供了新的解决方案,通过与健康管理平台和人工智能算法相结合,可显著提高风险评估的精确性,优化康复治疗方案,从而改善患者的预后。本文综述了可穿戴设备在卒中危险因素监测、风险预测、个性化康复及自我管理中的研究进展。未来,随着技术的进一步发展,可穿戴设备有望为卒中防治策略的优化提供更加精准和高效的支持。

国内外老年智能健康穿戴产品研究态势分析

智能健康穿戴产品在老年群体中展现出的巨大应用潜力和发展前景,引发学术界广泛研究探讨。为全面剖析国内外老年智能健康穿戴产品领域的研究态势,本文采用文献计量方法,通过共现、聚类及突现分析等多维手段,系统梳理与评估2013—2023年中国知网和Web of Science数据库收录的相关文献,借助VOSviewer和CiteSpace进行可视化呈现。结果表明:美国和中国在国际研究中占据主导地位;国内外的研究热点各有侧重,且国外已从技术设备开发与系统集成应用转向探讨老年人对技术的接受与采用;国际研究的知识基础可分为老年技术采纳评估、健康监测技术创新和智能健康管理应用三类。后续应加强工程学和医学多领域的跨学科交叉研究,在健康监测技术与医疗产品融合、用户体验优化及长期效用验证等方面进行深入探讨。

基于消费需求的夜间登山智能鞋类设计

伴随着登山运动的不断普及以及鞋服智能化程度的不断加深,登山鞋靴的设计也亟待转型升级。以夜间登山智能鞋为研究对象,从消费者视角出发,通过词频分析法识别夜间登山鞋在实用性和智能化方面的关键需求,即发光和定位两大功能。总结出发光和定位两大类功能中的10项细分功能点,采用问卷调查法分析消费群体对各功能点的需求程度和需求差异。最后采用发光二极管(Light Emitting Diode,LED)、荧光面料、全球定位系统(Global Positioning System,GPS)和智能互联技术,设计了一款集成照明、提示、导航、求助和互动等多种功能的智能夜间登山鞋。设计方案不仅拓展了登山鞋的功能性设计思路,且为夜间登山智能鞋的设计和制作提供了实践参考,有助于推动户外运动产业的智能化发展,满足消费者对夜间登山活动安全性和便捷性的要求。

A smart finger patch with coupled magnetoelastic and resistive bending sensors

In the era of Metaverse and virtual reality(VR)/augmented reality(AR),capturing finger motion and force interactions is crucial for immersive human-machine interfaces.This study introduces a flexible electronic skin for the index finger,addressing coupled perception of both state and process in dynamic tactile sensing.The device integrates resistive and giant magnetoelastic sensors,enabling detection of surface pressure and finger joint bending.This e-skin identifies three phases of finger action:bending state,dynamic normal force and tangential force(sweeping).The system comprises resistive carbon nanotubes(CNT)/polydimethylsiloxane(PDMS)films for bending sensing and magnetoelastic sensors(NdFeB particles,EcoFlex,and flexible coils)for pressure detection.The inward bending resistive sensor,based on self-assembled microstructures,exhibits directional specificity with a response time under 120 ms and bending sensitivity from 0°to 120°.The magnetoelastic sensors demonstrate specific responses to frequency and deformation magnitude,as well as sensitivity to surface roughness during sliding and material hardness.The system’s capability is demonstrated through tactile-based bread type and condition recognition,achieving 92%accuracy.This intelligent patch shows broad potential in enhancing interactions across various fields,from VR/AR interfaces and medical diagnostics to smart manufacturing and industrial automation.

Integration of wearable electronics and heart rate variability for human physical and mental well-being assessment

Heart rate variability(HRV)that can reflect the dynamic balance between the sympathetic nervous and parasympathetic nervous of human autonomic nervous system(ANS)has attracted considerable attention.However,traditional electrocardiogram(ECG)devices for HRV analysis are bulky,and hard wires are needed to attach measuring electrodes to the chest,resulting in the poor wearable experience during the long-term measurement.Compared with that,wearable electronics enabling continuously cardiac signals monitoring and HRV assessment provide a desirable and promising approach for helping subjects determine sleeping issues,cardiovascular diseases,or other threats to physical and mental well-being.Until now,significant progress and advances have been achieved in wearable electronics for HRV monitoring and applications for predicting human physical and mental well-being.In this review,the latest progress in the integration of wearable electronics and HRV analysis as well as practical applications in assessment of human physical and mental health are included.The commonly used methods and physiological signals for HRV analysis are briefly summarized.Furthermore,we highlighted the research on wearable electronics concerning HRV assessment and diverse applications such as stress estimation,drowsiness detection,etc.Lastly,the current limitations of the integrated wearable HRV system are concluded,and possible solutions in such a research direction are outlined.

用于可穿戴热管理的智能纤维及织物

保持热舒适对维持人体正常生命活动至关重要。利用纤维和织物进行个人热管理不仅能提升热舒适度,还有助于降低建筑能耗。然而,传统的织物无法满足人类在不同环境下的热舒适需求,迫使研究人员开发新型可穿戴热管理材料。基于材料化学、物理和纳米技术,目前已经开发出许多具有优异热管理性能的纤维及织物。本文综述了体温调节的创新策略和可穿戴热管理材料的最新进展,重点介绍了各种先进的被动和主动热管理材料,旨在梳理热管理材料的工作机理,并为相关领域的研究人员提供全面的参考。首先介绍了人体体温调节的生理基础,随后详细探讨了被动和主动热管理纤维和织物的工作原理及在不同应用场景下的优缺点,最后从商业应用的角度对可穿戴热管理纤维及织物的未来前景和挑战进行了展望。

基于镓基液态金属的柔性传感的研究进展

镓基液态金属(Gallium-based liquid metal,Ga-LM)具有高导电性、高拉伸性、高生物相容性和低毒性等优异性能,在柔性电子领域表现出巨大的应用潜力。然而由于Ga-LM特殊的流变性和氧化性,在控制成型和实际应用方面带来了一定的挑战。基于此,本文综述了Ga-LM在柔性传感领域研究与应用进展,介绍了Ga-LM传感器的不同基底特性及成型工艺,并分析了各自对应的优势、存在的问题和解决方案,旨为Ga-LM在柔性传感器领域的进一步研究和应用提供经验与参考。

穿戴式外骨骼结合姿势反馈训练改善脑卒中后患者的异常步态

背景:越来越多的证据表明,早期正确姿势的强化对于改善脑卒中患者的异常步态尤为重要;穿戴式外骨骼辅助训练能在短时间内改善患者的步行功能,也可辅助骨盆、髋、膝、踝多关节周围肌群协同运动,控制脑卒中患者下肢步行运动轨迹,提高患者的步行能力。目的:探讨穿戴式外骨骼结合姿势反馈训练对于脑卒中后患者异常步态的改善状况,并探究康复机制。方法:纳入2023年1月至2024年1月济宁医学院附属医院收治的52例脑卒中恢复期患者,采用随机数字表法随机分为试验组(n=26)与对照组(n=26)。在常规康复训练的基础上,试验组患者接受外骨骼辅助结合姿势反馈训练(15 min/d,每周6 d),对照组患者接受常规步行辅助训练(15 min/d,每周6 d),两组均连续训练4周。训练前及训练结束后,对比两组患者下肢运动功能评分、步态参数(步长、步速、步宽)及步态对称性,采用便携式近红外脑功能成像检测前额运动区、初级运动皮质和感觉运动区的脑功能连接值。结果与结论:(1)与训练前比较,两组患者训练结束后的下肢运动功能评分、步态参数及步态对称性均明显改善(P<0.05);训练结束后,试验组患者步态参数、步态对称性改善明显优于对照组(P<0.05);(2)训练结束后,两组患者右感觉运动区-左前额运动区与右感觉运动区-右前额运动区功能连接值均高于训练前(P<0.05),试验组患者左感觉运动区-右侧初级运动皮质与左感觉运动区-左初级运动皮质功能连接值均高于训练前(P<0.05),试验组患者左感觉运动区-右侧初级运动皮质与左感觉运动区-左初级运动皮质功能连接值高于对照组(P<0.05);(3)结果表明,在常规康复训练的基础上,穿戴式外骨骼结合姿势反馈训练不仅可有效改善脑卒中患者的异常步态,还能激活与异常步态相关的脑功能感觉与运动区。

基于可穿戴电子设备干预对健康青少年身体活动和久坐行为影响的Meta分析

目的:虽然可穿戴电子设备作为干预工具在增进身体活动方面展现出潜在效用,但关于其对健康青少年群体具体效果的全面评估仍显不足。为此,文章系统地探索和总结基于可穿戴电子设备的干预对健康青少年身体活动及久坐行为的影响,以期为公共卫生实践提供更精准和可靠的循证支持。方法:从Web of Science,PubMed,Scopus,The Cochrane Library和EBSCO数据库中检索关于可穿戴电子设备的干预对健康青少年身体活动和久坐行为影响的随机对照试验。利用RevMan 5.4和Stata 17软件进行Meta分析,通过标准化均数差评价干预对身体活动及久坐行为的效果。为确保研究结果的稳健性,采用Leave-One-Out方法进行敏感性分析,并通过亚组分析深入探究不同因素对结果的可能影响。该方案已在国际系统综述前瞻性注册中心注册(CRD42023406645)。结果:①最终纳入12篇文献,其中包含3项随机对照试验和9项整群随机对照试验,共纳入4933名健康青少年对象。②Meta分析结果发现,基于可穿戴电子设备的干预对中高强度身体活动产生了积极影响(SMD=0.10,95%CI:0.04-0.17;P<0.05),然而,该干预未能显著改善低强度身体活动(SMD=-0.15,95%CI:-0.32-0.02;P>0.05)、每日步数(SMD=0.13,95%CI:-0.65-0.91;P>0.05)和久坐行为(SMD=0.00,95%CI:-0.09-0.09;P>0.05)。③亚组分析结果表明,短期(≤12周)干预(SMD=0.11,95%CI:0.03-0.18;P=0.008)、佩戴在腰或臀部的计步器的研究(SMD=0.10,95%CI:0.04-0.17;P=0.002),以及在临床注册中心注册的试验(SMD=0.11,95%CI:0.04-0.17;P=0.001)对提升每日中高强度身体活动的效果更为显著。结论:当前证据表明,基于可穿戴电子设备的干预措施在提升健康青少年每日中高强度身体活动方面具有一定优势;建议通过不超过12周的干预时间、使用腰部或臀部计步器的干预设备以获得更好的促进效果;然而,每日步数、低强度身体活动以及久坐行为的干预效果存在一定的局限性,未来仍需要更高质量、大样本的随机对照试验进一步验证。

可穿戴设备在急诊医学领域的应用及进展

通过在PubMed和万方数据库中以“可穿戴电子设备”和“急诊医学”为关键词检索相关文献,分析了可穿戴设备技术的发展、在急诊临床中的应用现状以及面临的挑战。该研究显示,可穿戴设备在某些急诊场景中已初步显示出早期预警、早期诊断和协助决策的能力,从而在一定程度上提高了急诊诊疗的质量。然而,部分设备在急诊应用中的临床有效性仍存在争议。因此,研究者认为,未来仍需进行大量的临床试验,以推动可穿戴设备与急救医疗服务的结合。

基于机器学习的人体热舒适度建模与预测

热舒适度是衡量室内环境质量和影响人类健康的重要指标之一,是建筑、空调控制等系统智能化的重要参考依据,同时能够有效降低建筑热环境控制的能源需求.目前可穿戴设备如智能手环、柔性传感器等已广泛应用,可构建人体的健康大数据.但由于存在个体差异因素,不同个体对相同热环境所表现的生理热反应不同,基于单一个人的热舒适模型难以对群体热状态实现有效地预测.考虑到以往研究样本量相对较小、模型复杂难以部署等局限性,本文建立人工气候室,利用环境传感器和可穿戴设备收集了60名受试者的热舒适数据,采用机器学习实现人体热舒适度建模与预测.研究考虑身高、体重、性别等个体差异因素,采用XGBoost、随机森林和SVC共3种机器学习算法,得到了基于人体生理参数的增强型预测热态模型并对热舒适度进行分类.结果表明:对皮肤温度及其梯度进行归一化处理发现,归一化过程能够将冷不舒适、舒适、热不舒适3种状态拉开,有利于SVC算法在高维空间寻找最优超平面,对特征进行分类.对比归一化前后随机森林模型的特征重要性发现,归一化过程降低了体重、身高、性别等个体差异对模型预测效果的影响程度;在XGBoost、随机森林和SVC这3种机器学习算法中,SVC在测试集上的准确率和3种热状态的AUC值都高于XGBoost和随机森林,其分类效果和泛化能力最好.

基于电刺激触觉再现的可穿戴触觉信息表达系统

在人们的视觉和听觉无法发挥作用的场合下,触觉再现系统为人们感知周围的信息提供了一条非常有效的途径。该文设计并研制了基于电刺激的可穿戴式的触觉信息表达系统,采用动态循环显示技术在8×8个球形电极组成的电极阵列上通过手腕感知信息。进行了3组实验即不同频率和占空比条件下的电压感知阈值实验、空间分辨率实验和简单汉字感知实验。实验结果表明,在频率为100 Hz、占空比为35%时的电压感知阈值最低且感知效果最好;相邻电极之间的最小间距为4.5 mm时可以清楚地分辨出两列;简单汉字的感知成功率均高于90%。实验结果验证了该系统的有效性,同时为将来识别复杂汉字信息奠定了基础。

Toward Enhancing Wearability and Fashion of Wearable Supercapacitor with Modified Polyurethane Artificial Leather Electrolyte

Inspired by the sophisticated artificial leather garment industry and toward enhancing wearability of energy storage devices, we demonstrate a polyurethane artificial leather supercapacitor with large sheet electrodes embedded in theleather layer simultaneously working as a polyelectrolyte. This design totally reserves textiles underneath and thus addresses the well-known challenge of wearing comfortability. It provides a revolutionary configuration of wearable supercapacitors: the artificial leather on garment is also a supercapacitor.Unlike the polyvinyl alcohol-based acidic electrolytes, which are widely used, sodium chloride is used to modify the intrinsically fluorescent polyurethane leather for ionic transportation, which has no harm to human. The fluorescent leather supercapacitor is easily transferrable from any arbitrary substrates to form various patterns, enabling multifunctionalities of practical wearability, fashion, and energy storage.

On Mechanism of The Effect of Rare Earth on Wearability of Nickel Base Self-Fluxing Alloy Spray-Welding Layers

The mechansim of the effect of rare earth(RE)on wearability of spray-welding layers has been investi- gated by adding RE in ppm into Nickel base self-fluxing alloy powder.The test results show that the microalloy- ing effect of RE can refine the structure of spray-welding layers,and change the amount,size,shape and distri- bution of hard phase in spray-welding layers.The wearability of spray-welding layers is increased consequently.

可穿戴设备干预促进老年人身体活动的Meta分析

目的:虽然可穿戴设备在促进老年人身体活动方面的潜在效益已得到认可,但现有研究针对该人群的具体效果尚未进行全面系统的评估。文章旨在系统评价可穿戴设备干预对老年人中高强度身体活动、低强度身体活动、总身体活动、每日步数以及久坐行为等身体活动相关指标的影响。方法:通过PubMed、EMbase、Scopus、Ovid-Medline、The Cochrane Library、SPORTDiscus、CNKI、维普和万方等数据库检索文献,搜集关于可穿戴设备干预对老年人身体活动影响的随机对照试验,检索时限为各数据库建库至2024-03-10。采用Cochrane偏倚风险评估工具对纳入文献进行方法学质量评价,运用Review Manager 5.2和Stata 12.0软件进行数据合并、亚组分析、森林图绘制、敏感性分析、发表偏倚评价及单因素Meta回归分析。结果:①最终纳入43篇文献,包含5194个样本量;②Meta分析结果显示,可穿戴设备干预对老年人每日步数(SMD=0.48,95%CI:0.33-0.62,P<0.00001)、中高强度身体活动(SMD=0.29,95%CI:0.20-0.38,P<0.00001)、低强度身体活动(SMD=0.17,95%CI:0.02-0.32,P=0.03)和总身体活动(SMD=0.15,95%CI:0.02-0.28,P=0.02)均有显著的促进效果,然而对改善老年人久坐行为无明显效果(SMD=-0.08,95%CI:-0.21-0.05,P=0.22);③亚组分析结果显示,采用综合干预措施、干预时间≤12周以及使用计步器作为干预设备对促进老年人低强度身体活动和总身体活动的效果更佳;采用综合干预措施、干预时间≤12周及使用加速度计为干预设备可能对促进老年人每日步数和中高强度身体活动更有效;④Meta回归结果表明,年龄(P=0.038)和健康状况(P=0.083)是影响每日步数异质性的重要因素。结论:当前证据表明,可穿戴设备干预在促进老年人每日步数、中高强度身体活动、低强度身体活动和总身体活动方面具有积极作用,建议在设计可穿戴设备干预方案时,考虑采用综合干预方式、干预时间≤12周并根据干预目标选择合适的设备。尽管如此,对于减少久坐行为的干预效果尚需更多高质量随机对照试验来进一步验证。