This study focuses on the design and validation of a behavior classification system for cattle using behavioral data collected through accelerometer sensors.Data collection and behavioral analysis are achieved using m...This study focuses on the design and validation of a behavior classification system for cattle using behavioral data collected through accelerometer sensors.Data collection and behavioral analysis are achieved using machine learning(ML)algorithms through accelerometer sensors.However,behavioral analysis poses challenges due to the complexity of cow activities.The task becomes more challenging in a real-time behavioral analysis system with the requirement for shorter data windows and energy constraints.Shorter windows may lack sufficient information,reducing algorithm performance.Additionally,the sensor’s position on the cowsmay shift during practical use,altering the collected accelerometer data.This study addresses these challenges by employing a 3-s data window to analyze cow behaviors,specifically Feeding,Lying,Standing,and Walking.Data synchronization between accelerometer sensors placed on the neck and leg compensates for the lack of information in short data windows.Features such as the Vector of Dynamic Body Acceleration(VeDBA),Mean,Variance,and Kurtosis are utilized alongside the Decision Tree(DT)algorithm to address energy efficiency and ensure computational effectiveness.This study also evaluates the impact of sensor misalignment on behavior classification.Simulated datasets with varying levels of sensor misalignment were created,and the system’s classification accuracy exceeded 0.95 for the four behaviors across all datasets(including original and simulated misalignment datasets).Sensitivity(Sen)and PPV for all datasets were above 0.9.The study provides farmers and the dairy industry with a practical,energy-efficient system for continuously monitoring cattle behavior to enhance herd productivity while reducing labor costs.展开更多
Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial...Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.展开更多
Real-time detection of low-speed motion and precise monitoring of low-intensity exercise are crucial for smart fitness systems.These capabilities enable continuous data acquisition,capture subtle motion variations for...Real-time detection of low-speed motion and precise monitoring of low-intensity exercise are crucial for smart fitness systems.These capabilities enable continuous data acquisition,capture subtle motion variations for personalized guidance,and enhance training effectiveness while reducing the risk of injury.However,conventional rotational speed sensors often exhibit signal loss and limited responsiveness at low speeds,leading to inaccurate feedback and constraining the development of intelligent fitness devices.Therefore,this paper proposes a triboelectric rotational speed sensor(TRSS),which employs a coaxial reverse magnetic modulation transmission mechanism to enhance low-speed monitoring,thereby overcoming low-speed signal loss.The sensor enables real-time detection of rotational speed in fitness equipment,and features a compact structure,doubled resolution,and high detection accuracy of 0.21 rad s−1.Performance test indicates a sensitivity of 3.15 Hz(rad s−1)−1,a linear correlation coefficient of 0.99892,and an average error of 1.19%in simulated tests,which demonstrates the capability of the sensor for accurate motion monitoring at low speeds.Furthermore,a triboelectric magnetic-modulated rotational monitoring system(TMRMS)is developed and validated through cycling experiments,demonstrating excellent performance across a wide speed range.These findings highlight the strong potential of the system for advancing next-generation smart fitness applications.展开更多
Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming pr...Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming procedures,complex operations,and delayed results.Colorimetric analysis techniques have gained attention in recent years due to their advantages of short analysis time,simple operation,and suitability for on-site testing.This study successfully developed a series of colorimetric sensor platforms for biogenic amines by loading the natural active ingredient curcumin(CUR)and its derivative of Boron complex BFCUR onto filter paper and electrospun nanofibre films(ENFs),respectively.By analyzing the color response differences of these sensors upon contact with biogenic amines,the colorimetric sensors with superior detection performance were selected and further applied to the visual monitoring and indication of shrimp spoilage processes.展开更多
Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexib...Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we prese...Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we present a bioinspired piezoelectric vibration sensor that mimics the graded stiffness and stress-based transduction mechanism of otolithic cilia in the human vestibular system.The device consists of a trapezoidal cantilever array with tip inertial masses,fabricated through a hybrid stereolithography 3D printing and laser micromachining process for rapid prototyping without cleanroom facilities.Finite-element modeling and experimental measurements demonstrate a fundamental resonance near 1.2 kHz,a 5%flat-bandwidth of 350 Hz,and an in-band charge sensitivity of 3.17 pC/g.A wearable proof-of-concept test further verifies the sensor's ability to reproducibly distinguish phoneme-specific vibration patterns in both time and frequency domains.This work establishes a foundation for bioinspired tactile sensing front-ends in wearable voice interfaces and other intelligent diagnostic systems integrated with machine-learning algorithms.展开更多
Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations...Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.展开更多
This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on th...This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.展开更多
Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ion...Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ionic liquid(IL),using 1-ethyl-3-methylimidazolium bromide([EMIM]Br)IL as solvent.Benefiting from the compatibility of ILs and alkene-PR,the cross-linked network slide-ring gel not only maintains excellent conductivity(1.52×10^(−2) S/m),but also has effectively improved mechanical properties(513%fracture strain,0.713 MPa fracture stress,211 kPa elastic modulus and 1366 kJ/m^(3) toughness)and adhesive properties(472.3±25.9 kPa).The supramolecular gel can be used as a strain sensor to efficiently monitor deformation signals in real-time at least 200 times.Especially,the slide-ring gel can self-power generated by triboelectric effect and electrostatic induction between the skin layer and the polydimethylsiloxane(PDMS)layer that encapsulates the gel,achieving reversible and durable motion sensing,which provides a convenient pathway for constructing supramolecular self-powered flexible electronic materials.展开更多
Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framew...Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framework that jointly designs distributed observers and local controllers to ensure robust formation control in the presence of external disturbances and sensor malfunctions.Treating the spacecraft formation as a single interconnected system,each spacecraft constructs a distributed observer that estimates the overall system state by incorporating both its own measurements and the predicted control information shared among the spacecraft.Based on the observer estimates,a local control law is synthesized to maintain the desired formation.Rigorous theoretical analysis and numerical simulations demonstrate that the proposed integrated approach effectively guarantees formation stability and resilience against sensor failures and disturbances.展开更多
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,...Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.展开更多
Silicone-based pressure-sensitive adhesives(Si-PSAs)are valued for their thermal stability,flexibility,and biocompatibility,but their weak bonding strength restricts high-performance use.Polyurethane-modified Si-PSAs ...Silicone-based pressure-sensitive adhesives(Si-PSAs)are valued for their thermal stability,flexibility,and biocompatibility,but their weak bonding strength restricts high-performance use.Polyurethane-modified Si-PSAs enhance adhesion,however diisocyanates remain essential.The raw materials of isocyanates are toxic,and their synthesis involves phosgene.To make up for those shortcomings,a series of poly(hydroxy urethane-siloxane)PSAs,named as PHUSi here,were synthesized through the ring-opening reaction of cyclic carbonate-functionalized polysiloxanes(PSi_(x)-VEC_(z))with various aliphatic diamines.The PSi_(x)-VEC_(z) precursors were prepared via the hydrosilylation of hydrogen-containing polysiloxanes(PSi_(x)-H_(y))with 4-vinyl-1,3-dioxolan-2-one(VEC).The chemical structures of PSi_(x)-H_(y),PSi_(x)-VEC_(z) and PHUSi were characterized,and bonding properties of PHUSi were systematically evaluated.The influence of architectures on adhesive performance was elucidated through comprehensive analyses,including rheology,crosslink density assessment,and so on.These studies revealed that the tailored design of PHUSi adhesives combine the advantages of traditional Si-PSAs with enhanced adhesion while eliminating isocyanate toxicity.The optimized PHUSi formulation achieved remarkable 180°peel strength(76.5 N/m on skin)and maximum probe tack force(1.61 N),enabling secure 24 h attachment of flexible sensors to skin.These properties make PHUSi particularly suitable for medical applications,as demonstrated by successful implementation in flexible electrocardiogram devices,offering a biocompatible,high-performance adhesive.展开更多
As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and el...As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.展开更多
Real-time health monitoring and ongoing evaluation of physiological conditions are becoming increasingly vital for the advancement of future medical diagnostics and personalized healthcare solutions.Given that certain...Real-time health monitoring and ongoing evaluation of physiological conditions are becoming increasingly vital for the advancement of future medical diagnostics and personalized healthcare solutions.Given that certain illnesses necessitate prompt and accessible detection methods,wearable chemical sensors have garnered considerable interest for their capability to monitor health through physiological signals and chemical indicators.This review delivers a thorough examination of recent developments in four primary categories of wearable chemical sensors:biosensors,humidity sensors,gas sensors,and ion sensors.We explore the representative materials,device structures,operating mechanisms,and various application scenarios for each type of sensor.By investigating the latest innovations in these technologies,we aim to provide a detailed overview of the current research landscape,highlight existing challenges,and present potential future directions of wearable chemical sensors in healthcare monitoring.展开更多
The development of intrinsically conductive piezoresistive sensors with high strain tolerance has garnered significant interest.While elastomeric polymers exhibit excellent strain capabilities,their utility in sensing...The development of intrinsically conductive piezoresistive sensors with high strain tolerance has garnered significant interest.While elastomeric polymers exhibit excellent strain capabilities,their utility in sensing applications has been limited by inherent challenges such as high electrical resistivity,poor aging resistance,and interfacial incompatibility.To address these limitations,hydroxyl-terminated polybutadiene(HTPB)-based polyurethane was chemically modified with acetylferrocene-polyaniline conductive moieties to enhance charge transport properties.Remarkably,this covalent functionalization endowed the resulting ferrocene-polyaniline hybrid polyurethane(FPHP)with a conductivity of2.33 n A at 1 V bias while preserving piezoresistive functionality.The FPHP demonstrated exceptional mechanical-electrical performance,achieving 254% elongation at break with strain-dependent gauge factors of 7.28(0%-12.5% strain,R^(2)=0.9504)and 19.66(12.5%-35.0% strain,R^(2)=0.9929).Further characterization revealed a rapid 0.60 s response time and stability over 3500 strain-release cycles at compression strain,underscoring its durability under repetitive loading.The FPHP sensor was capable of monitoring various human movements and recognizing writing signals.These advances establish a materials design paradigm for fabricating flexible sensors that synergistically integrate high deformability,tunable sensitivity,and robust operational stability,positioning FPHP as a promising candidate for next-generation wearable electronics and soft robotics.展开更多
Flexible and wearable sensors offer immense potential for rehabilitation medicine,but most rely solely on electrical signals,lacking real-time visual feedback and limiting trainee's interactivity.Inspired by the s...Flexible and wearable sensors offer immense potential for rehabilitation medicine,but most rely solely on electrical signals,lacking real-time visual feedback and limiting trainee's interactivity.Inspired by the structural coloration of Cyanocitta stelleri feathers,we developed a dual-mode sensor by utilizing black conductive polymer hydrogel(CPH)-enhanced structural color strategy.This sensor integrates a hydroxypropyl cellulose(HPC)-based structural color interface with a designed CPH sensing component.Highly visible light-absorbing CPH(absorption rate>88%)serves as the critical substrate for enhancing structural color performance.By absorbing incoherent scattered light and suppressing background interference,it significantly enhances the saturation of structural color,thereby achieving a high contrast index of 4.92.Unlike the faint and hardly visible structural colors on non-black substrates,the HPC on CPH displays vivid,highly perceptible colors and desirable mechanochromic behavior.Moreover,the CPH acts as a flexible sensing element,fortified by hydrogen and coordination bond networks,and exhibits exceptional electromechanical properties,including 867.1 kPa tensile strength,strain sensitivity(gauge factor of 4.24),and outstanding durability(over 4400 cycles).Compared to traditional single-mode sensors,the integrated sensor provides real-time visual and digital dual feedback,enhancing the accuracy and interactivity of rehabilitation assessments.This technology holds promise for advancing next-generation rehabilitation medicine.展开更多
Flexible pressure sensors(FPSs)offer unique benefits for fall detection and rehabilitation training,but conventional FPSs made from synthetic materials have drawbacks,including resource-heavy manufacturing,high costs,...Flexible pressure sensors(FPSs)offer unique benefits for fall detection and rehabilitation training,but conventional FPSs made from synthetic materials have drawbacks,including resource-heavy manufacturing,high costs,and environmental pollution.To address these limitations,this study proposes an innovative fabrication strategy for FPS based on natural materials.The upper and lower electrodes were made by treating a natural wood strip with a flame retardant,converting it into high-quality graphene via a costeffective infrared laser,and transferring it onto starch-based substrates.The dielectric layer was created by electrospinning a composite nanofiber membrane with cyclodextrin and carbon nanotubes.The resulting capacitive FPS shows high sensitivity(2.15 kPa^(-1) within 0-10 kPa),a low detection limit(~6.5 Pa),fast response and recovery times(29 and 39 ms),and excellent long-term stability(over 5000 cycles).It also demonstrates excellent biocompatibility(cell viability>98%)and fully degrades within 6 h.By integrating this sensor with wireless technology,a fall detection and rehabilitation monitoring system was developed.Data processing was handled by a Tiny Machine Learning module on a mobile platform,which transmitted relevant data to a cloud-based platform.The system accurately identified five common fall postures and assisted clinicians in guiding rehabilitation exercises,achieving recognition accuracies of 99%and 100%,respectively,offering a sustainable healthcare solution for the elderly.展开更多
基金funded by Vietnam National Foundation for Science and Technology Development(NAFOSTED)under grant number:02/2022/TN.
文摘This study focuses on the design and validation of a behavior classification system for cattle using behavioral data collected through accelerometer sensors.Data collection and behavioral analysis are achieved using machine learning(ML)algorithms through accelerometer sensors.However,behavioral analysis poses challenges due to the complexity of cow activities.The task becomes more challenging in a real-time behavioral analysis system with the requirement for shorter data windows and energy constraints.Shorter windows may lack sufficient information,reducing algorithm performance.Additionally,the sensor’s position on the cowsmay shift during practical use,altering the collected accelerometer data.This study addresses these challenges by employing a 3-s data window to analyze cow behaviors,specifically Feeding,Lying,Standing,and Walking.Data synchronization between accelerometer sensors placed on the neck and leg compensates for the lack of information in short data windows.Features such as the Vector of Dynamic Body Acceleration(VeDBA),Mean,Variance,and Kurtosis are utilized alongside the Decision Tree(DT)algorithm to address energy efficiency and ensure computational effectiveness.This study also evaluates the impact of sensor misalignment on behavior classification.Simulated datasets with varying levels of sensor misalignment were created,and the system’s classification accuracy exceeded 0.95 for the four behaviors across all datasets(including original and simulated misalignment datasets).Sensitivity(Sen)and PPV for all datasets were above 0.9.The study provides farmers and the dairy industry with a practical,energy-efficient system for continuously monitoring cattle behavior to enhance herd productivity while reducing labor costs.
基金supported by the projects funded by the Education Department of Shaanxi Provincial Government(NO.23JP116)the Natural Science Fund of Shaanxi Province(NO.2024JC-YBMS-396)+3 种基金the National Natural Science Foundation of China(NO.52171191,52371198,U22A20137)the Constructing National Independent Innovation Demonstration Zones(XM2024XTGXQ05)Shenzhen Science and Technology Innovation Program(JCYJ20220818102215033,GJHZ20210705142542015,JCYJ20220530160811027)Guangdong HUST Industrial Technology Research Institute,Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization(2023B1212060012).
文摘Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.
基金supported by the National Key R&D Project from Minister of Science and Technology(Grant No.2021YFA1201604)Beijing Natural Science Foundation(Grant No.3244038)+1 种基金GuangDong Basic and Applied Basic Research Foundation(Grant No.2024A1515140103)Jilin Province Development and Reform Commission(Grant No.2024C006-3).
文摘Real-time detection of low-speed motion and precise monitoring of low-intensity exercise are crucial for smart fitness systems.These capabilities enable continuous data acquisition,capture subtle motion variations for personalized guidance,and enhance training effectiveness while reducing the risk of injury.However,conventional rotational speed sensors often exhibit signal loss and limited responsiveness at low speeds,leading to inaccurate feedback and constraining the development of intelligent fitness devices.Therefore,this paper proposes a triboelectric rotational speed sensor(TRSS),which employs a coaxial reverse magnetic modulation transmission mechanism to enhance low-speed monitoring,thereby overcoming low-speed signal loss.The sensor enables real-time detection of rotational speed in fitness equipment,and features a compact structure,doubled resolution,and high detection accuracy of 0.21 rad s−1.Performance test indicates a sensitivity of 3.15 Hz(rad s−1)−1,a linear correlation coefficient of 0.99892,and an average error of 1.19%in simulated tests,which demonstrates the capability of the sensor for accurate motion monitoring at low speeds.Furthermore,a triboelectric magnetic-modulated rotational monitoring system(TMRMS)is developed and validated through cycling experiments,demonstrating excellent performance across a wide speed range.These findings highlight the strong potential of the system for advancing next-generation smart fitness applications.
基金Supported by the Guangdong-Hong Kong-Macao Joint Laboratory on Micro-Nano Manufacturing Technology,China(No.2021LSYS004)Guangdong Provincial Key Laboratory of Sustainable Biomimetic Materials and Green Energy,China(No.2024B1212010003)。
文摘Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming procedures,complex operations,and delayed results.Colorimetric analysis techniques have gained attention in recent years due to their advantages of short analysis time,simple operation,and suitability for on-site testing.This study successfully developed a series of colorimetric sensor platforms for biogenic amines by loading the natural active ingredient curcumin(CUR)and its derivative of Boron complex BFCUR onto filter paper and electrospun nanofibre films(ENFs),respectively.By analyzing the color response differences of these sensors upon contact with biogenic amines,the colorimetric sensors with superior detection performance were selected and further applied to the visual monitoring and indication of shrimp spoilage processes.
基金supported by the National Key Research and Development Program of China(2023YFB3809800)the National Natural Science Foundation of China(52172249,52525601)+2 种基金the Chinese Academy of Sciences Talents Program(E2290701)the Jiangsu Province Talents Program(JSSCRC2023545)the Special Fund Project of Carbon Peaking Carbon Neutrality Science and Technology Innovation of Jiangsu Province(BE2022011).
文摘Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
文摘Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we present a bioinspired piezoelectric vibration sensor that mimics the graded stiffness and stress-based transduction mechanism of otolithic cilia in the human vestibular system.The device consists of a trapezoidal cantilever array with tip inertial masses,fabricated through a hybrid stereolithography 3D printing and laser micromachining process for rapid prototyping without cleanroom facilities.Finite-element modeling and experimental measurements demonstrate a fundamental resonance near 1.2 kHz,a 5%flat-bandwidth of 350 Hz,and an in-band charge sensitivity of 3.17 pC/g.A wearable proof-of-concept test further verifies the sensor's ability to reproducibly distinguish phoneme-specific vibration patterns in both time and frequency domains.This work establishes a foundation for bioinspired tactile sensing front-ends in wearable voice interfaces and other intelligent diagnostic systems integrated with machine-learning algorithms.
基金supported by the National Natural Science Foundation of China(General Program)under Grant 52571385National Key R&D Program of China(Grant No.2024YFC2815000 and No.2024YFB3816000)+12 种基金Open Fund of State Key Laboratory of Deep-sea Manned Vehicles(Grant No.2025SKLDMV07)Shenzhen Science and Technology Program(WDZC20231128114452001,JCYJ20240813112107010 and JCYJ20240813111910014)the Tsinghua SIGS Scientific Research Startup Fund(QD2022021C)the Dreams Foundation of Jianghuai Advance Technology Center(2023-ZM 01 Z006)the Ocean Decade International Cooperation Center(ODCC)(GHZZ3702840002024020000026)Shenzhen Key Laboratory of Advanced Technology for Marine Ecology(ZDSYS20230626091459009)Shenzhen Science and Technology Program(No.KJZD20240903100905008)the National Natural Science Foundation of China(No.22305141)Pearl River Talent Program(No.2023QN10C114)General Program of Guangdong Province(No.2025A1515011700)the Guangdong Innovative and Entrepreneurial Research Team Program(2023ZT10C040)Scientific Research Foundation from Shenzhen Finance Bureau(No.GJHZ20240218113600002)Tsinghua University(JC2023001).
文摘Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.
文摘This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.
基金Natural Science Foundation of China(NSFC,No.22131008)Natural Science Foundation of Tianjin(No.22JCYBJC00500)the Haihe Laboratory of Sustainable Chemical Transformations for financial support.
文摘Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ionic liquid(IL),using 1-ethyl-3-methylimidazolium bromide([EMIM]Br)IL as solvent.Benefiting from the compatibility of ILs and alkene-PR,the cross-linked network slide-ring gel not only maintains excellent conductivity(1.52×10^(−2) S/m),but also has effectively improved mechanical properties(513%fracture strain,0.713 MPa fracture stress,211 kPa elastic modulus and 1366 kJ/m^(3) toughness)and adhesive properties(472.3±25.9 kPa).The supramolecular gel can be used as a strain sensor to efficiently monitor deformation signals in real-time at least 200 times.Especially,the slide-ring gel can self-power generated by triboelectric effect and electrostatic induction between the skin layer and the polydimethylsiloxane(PDMS)layer that encapsulates the gel,achieving reversible and durable motion sensing,which provides a convenient pathway for constructing supramolecular self-powered flexible electronic materials.
基金supported by the National Natural Science Foundation of China(62088101,62522307,62273045,U2341213)Beijing Nova Program(20230484481)。
文摘Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framework that jointly designs distributed observers and local controllers to ensure robust formation control in the presence of external disturbances and sensor malfunctions.Treating the spacecraft formation as a single interconnected system,each spacecraft constructs a distributed observer that estimates the overall system state by incorporating both its own measurements and the predicted control information shared among the spacecraft.Based on the observer estimates,a local control law is synthesized to maintain the desired formation.Rigorous theoretical analysis and numerical simulations demonstrate that the proposed integrated approach effectively guarantees formation stability and resilience against sensor failures and disturbances.
基金supported by the Basic Science Research Program(2023R1A2C3004336,RS-202300243807)&Regional Leading Research Center(RS-202400405278)through the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)。
文摘Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.
基金financially supported by the Shandong Provincial Natural Science Foundation,China(Nos.ZR2022MB051 and ZR2021MB112)Postdoctoral Science Foundation of China(No.2022M712343)+2 种基金Jinan City University Integration Development Strategy Project(No.JNSX2024030)Key Laboratory of Special Functional Aggregates of the Ministry of Education,Shandong University(No.JJT-2023-02)Shandong SD-Link New Material Technology Co.,LTD.
文摘Silicone-based pressure-sensitive adhesives(Si-PSAs)are valued for their thermal stability,flexibility,and biocompatibility,but their weak bonding strength restricts high-performance use.Polyurethane-modified Si-PSAs enhance adhesion,however diisocyanates remain essential.The raw materials of isocyanates are toxic,and their synthesis involves phosgene.To make up for those shortcomings,a series of poly(hydroxy urethane-siloxane)PSAs,named as PHUSi here,were synthesized through the ring-opening reaction of cyclic carbonate-functionalized polysiloxanes(PSi_(x)-VEC_(z))with various aliphatic diamines.The PSi_(x)-VEC_(z) precursors were prepared via the hydrosilylation of hydrogen-containing polysiloxanes(PSi_(x)-H_(y))with 4-vinyl-1,3-dioxolan-2-one(VEC).The chemical structures of PSi_(x)-H_(y),PSi_(x)-VEC_(z) and PHUSi were characterized,and bonding properties of PHUSi were systematically evaluated.The influence of architectures on adhesive performance was elucidated through comprehensive analyses,including rheology,crosslink density assessment,and so on.These studies revealed that the tailored design of PHUSi adhesives combine the advantages of traditional Si-PSAs with enhanced adhesion while eliminating isocyanate toxicity.The optimized PHUSi formulation achieved remarkable 180°peel strength(76.5 N/m on skin)and maximum probe tack force(1.61 N),enabling secure 24 h attachment of flexible sensors to skin.These properties make PHUSi particularly suitable for medical applications,as demonstrated by successful implementation in flexible electrocardiogram devices,offering a biocompatible,high-performance adhesive.
基金supported by the NSFC(12474071)Natural Science Foundation of Shandong Province(ZR2024YQ051,ZR2025QB50)+6 种基金Guangdong Basic and Applied Basic Research Foundation(2025A1515011191)the Shanghai Sailing Program(23YF1402200,23YF1402400)funded by Basic Research Program of Jiangsu(BK20240424)Open Research Fund of State Key Laboratory of Crystal Materials(KF2406)Taishan Scholar Foundation of Shandong Province(tsqn202408006,tsqn202507058)Young Talent of Lifting engineering for Science and Technology in Shandong,China(SDAST2024QTB002)the Qilu Young Scholar Program of Shandong University。
文摘As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.
基金supported by the Shandong Excellent Young Scientists Fund Program(Overseas)(2023HWYQ-035)the Taishan Scholar Program of Shandong Province(tsqn202306078)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(2024A1515011635)the Natural Science Foundation of Shandong Province(ZR2023MF108)the Jinan Central Hospital(1190022050)。
文摘Real-time health monitoring and ongoing evaluation of physiological conditions are becoming increasingly vital for the advancement of future medical diagnostics and personalized healthcare solutions.Given that certain illnesses necessitate prompt and accessible detection methods,wearable chemical sensors have garnered considerable interest for their capability to monitor health through physiological signals and chemical indicators.This review delivers a thorough examination of recent developments in four primary categories of wearable chemical sensors:biosensors,humidity sensors,gas sensors,and ion sensors.We explore the representative materials,device structures,operating mechanisms,and various application scenarios for each type of sensor.By investigating the latest innovations in these technologies,we aim to provide a detailed overview of the current research landscape,highlight existing challenges,and present potential future directions of wearable chemical sensors in healthcare monitoring.
文摘The development of intrinsically conductive piezoresistive sensors with high strain tolerance has garnered significant interest.While elastomeric polymers exhibit excellent strain capabilities,their utility in sensing applications has been limited by inherent challenges such as high electrical resistivity,poor aging resistance,and interfacial incompatibility.To address these limitations,hydroxyl-terminated polybutadiene(HTPB)-based polyurethane was chemically modified with acetylferrocene-polyaniline conductive moieties to enhance charge transport properties.Remarkably,this covalent functionalization endowed the resulting ferrocene-polyaniline hybrid polyurethane(FPHP)with a conductivity of2.33 n A at 1 V bias while preserving piezoresistive functionality.The FPHP demonstrated exceptional mechanical-electrical performance,achieving 254% elongation at break with strain-dependent gauge factors of 7.28(0%-12.5% strain,R^(2)=0.9504)and 19.66(12.5%-35.0% strain,R^(2)=0.9929).Further characterization revealed a rapid 0.60 s response time and stability over 3500 strain-release cycles at compression strain,underscoring its durability under repetitive loading.The FPHP sensor was capable of monitoring various human movements and recognizing writing signals.These advances establish a materials design paradigm for fabricating flexible sensors that synergistically integrate high deformability,tunable sensitivity,and robust operational stability,positioning FPHP as a promising candidate for next-generation wearable electronics and soft robotics.
基金supported by the Science and Technology Development Fund,Macao SAR(0065/2023/AFJ,0116/2022/A3)the National Natural Science Foundation of China(52402166)+4 种基金the Natural Science Foundation of Guangdong Province(2025A1515011120)the Australian Research Council(DE220100154)the financial support from the Science and Technology Development Fund(FDCT),Macao SAR(No.0149/2022/A),and(No.0046/2024/AFJ)Guangdong Science and Technology Department(2023QN10C305)for this workthe financial support from the National Natural Science Foundation of China(Grant No.22305185)。
文摘Flexible and wearable sensors offer immense potential for rehabilitation medicine,but most rely solely on electrical signals,lacking real-time visual feedback and limiting trainee's interactivity.Inspired by the structural coloration of Cyanocitta stelleri feathers,we developed a dual-mode sensor by utilizing black conductive polymer hydrogel(CPH)-enhanced structural color strategy.This sensor integrates a hydroxypropyl cellulose(HPC)-based structural color interface with a designed CPH sensing component.Highly visible light-absorbing CPH(absorption rate>88%)serves as the critical substrate for enhancing structural color performance.By absorbing incoherent scattered light and suppressing background interference,it significantly enhances the saturation of structural color,thereby achieving a high contrast index of 4.92.Unlike the faint and hardly visible structural colors on non-black substrates,the HPC on CPH displays vivid,highly perceptible colors and desirable mechanochromic behavior.Moreover,the CPH acts as a flexible sensing element,fortified by hydrogen and coordination bond networks,and exhibits exceptional electromechanical properties,including 867.1 kPa tensile strength,strain sensitivity(gauge factor of 4.24),and outstanding durability(over 4400 cycles).Compared to traditional single-mode sensors,the integrated sensor provides real-time visual and digital dual feedback,enhancing the accuracy and interactivity of rehabilitation assessments.This technology holds promise for advancing next-generation rehabilitation medicine.
基金supported by the National Natural Science Foundation of China(62301291,61904092,and 62181240278)Natural Science Foundation of Shandong Province(ZR2025MS1072)+1 种基金Youth Innovation Team Project of Shandong Provincial Education Department(2022KJ141)Taishan Scholars Project Special Funds(tsqn202312035)。
文摘Flexible pressure sensors(FPSs)offer unique benefits for fall detection and rehabilitation training,but conventional FPSs made from synthetic materials have drawbacks,including resource-heavy manufacturing,high costs,and environmental pollution.To address these limitations,this study proposes an innovative fabrication strategy for FPS based on natural materials.The upper and lower electrodes were made by treating a natural wood strip with a flame retardant,converting it into high-quality graphene via a costeffective infrared laser,and transferring it onto starch-based substrates.The dielectric layer was created by electrospinning a composite nanofiber membrane with cyclodextrin and carbon nanotubes.The resulting capacitive FPS shows high sensitivity(2.15 kPa^(-1) within 0-10 kPa),a low detection limit(~6.5 Pa),fast response and recovery times(29 and 39 ms),and excellent long-term stability(over 5000 cycles).It also demonstrates excellent biocompatibility(cell viability>98%)and fully degrades within 6 h.By integrating this sensor with wireless technology,a fall detection and rehabilitation monitoring system was developed.Data processing was handled by a Tiny Machine Learning module on a mobile platform,which transmitted relevant data to a cloud-based platform.The system accurately identified five common fall postures and assisted clinicians in guiding rehabilitation exercises,achieving recognition accuracies of 99%and 100%,respectively,offering a sustainable healthcare solution for the elderly.
