Traditional hydrogels are inevitably damaged during practical applications,resulting in a gradual deterioration of their functional efficacy.A primary strategy to address this issue involves developing hydrogels with ...Traditional hydrogels are inevitably damaged during practical applications,resulting in a gradual deterioration of their functional efficacy.A primary strategy to address this issue involves developing hydrogels with inherent self-healing properties.In this study,we report the synthesis of self-healing polyacrylate hydrogels that integrate zwitterions,hydrophilic nano-silica and aluminum ions.Due to the synergistic effect of multiple hydrogen bonds,coordination bonds and electrostatic interactions,the tensile strength of the hydrogel is enhanced from 15.1 to 162.6 kPa.Moreover,the electrical resistance and tensile strength of the hydrogel can almost recover to its initial values after 20 min of healing at room temperature,exhibiting remarkable self-healing performance.Furthermore,the zwitterionic polyacrylate hydrogel serves as a wearable sensor with the capability of accurately response to the bending and stretching of human joints,exhibting a gauge factor of 1.87 under tensile strain ranging from 80% to 100%.Even after being freezed at-20℃ for 3 h,the zwitterionic polyacrylate hydrogel retains its exceptional writing performance.In conclusion,the hydrogels developed in this study demonstrate significant potential for wearable electronics applications.展开更多
In a recent study,Prof.Rui Min and collaborators published their paper in the journal of Opto-Electronic Science that is entitled"Smart photonic wristband for pulse wave monitoring".The paper introduces nove...In a recent study,Prof.Rui Min and collaborators published their paper in the journal of Opto-Electronic Science that is entitled"Smart photonic wristband for pulse wave monitoring".The paper introduces novel realization of a sensor that us-es a polymer optical multi-mode fiber to sense pulse wave bio-signal from a wrist by analyzing the specklegram mea-sured at the output of the fiber.Applying machine learning techniques over the pulse wave signal allowed medical diag-nostics and recognizing different gestures with accuracy rate of 95%.展开更多
Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric lea...Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.展开更多
Inertial Sensor-based Daily Activity Recognition(IS-DAR)requires adaptable,data-efficient methods for effective multi-sensor use.This study presents an advanced detection system using body-worn sensors to accurately r...Inertial Sensor-based Daily Activity Recognition(IS-DAR)requires adaptable,data-efficient methods for effective multi-sensor use.This study presents an advanced detection system using body-worn sensors to accurately recognize activities.A structured pipeline enhances IS-DAR by applying signal preprocessing,feature extraction and optimization,followed by classification.Before segmentation,a Chebyshev filter removes noise,and Blackman window-ing improves signal representation.Discriminative features-Gaussian Mixture Model(GMM)with Mel-Frequency Cepstral Coefficients(MFCC),spectral entropy,quaternion-based features,and Gammatone Cepstral Coefficients(GCC)-are fused to expand the feature space.Unlike existing approaches,the proposed IS-DAR system uniquely inte-grates diverse handcrafted features using a novel fusion strategy combined with Bayesian-based optimization,enabling a more accurate and generalized activity recognition.The key contribution lies in the joint optimization and fusion of features via Bayesian-based subset selection,resulting in a compact and highly discriminative feature representation.These features are then fed into a Convolutional Neural Network(CNN)to effectively detect spatial-temporal patterns in activity signals.Testing on two public datasets-IM-WSHA and ENABL3S-achieved accuracy levels of 93.0%and 92.0%,respectively.The integration of advanced feature extraction methods with fusion and optimization techniques significantly enhanced detection performance,surpassing traditional methods.The obtained results establish the effectiveness of the proposed IS-DAR system for deployment in real-world activity recognition applications.展开更多
Wearable flexible sensor devices have the characteristics of lightweight and miniaturization.Currently,power supply and detection components limit the portability of wearable flexible sensor devices.Meanwhile,conventi...Wearable flexible sensor devices have the characteristics of lightweight and miniaturization.Currently,power supply and detection components limit the portability of wearable flexible sensor devices.Meanwhile,conventional liquid electrolytes are unsuitable for the integration of sensing devices.To address these constraints,wearable biofuel cells and flexible electrochromic displays have been introduced,which can improve integration with other devices,safety,and color-coded display data.Meanwhile,electrode chips prepared through screen printing technology can further improve portability.In this work,a wearable sensor device with screen-printed chips was constructed and used for non-invasive detection of glucose.Agarose gel electrolytes doped with PDA-CNTs were prepared,and the mechanical strength and moisture retention were significantly improved compared with traditional gel electrolytes.Glucose in interstitial fluid was non-invasive extracted to the skin surface using reverse iontophoresis.As a biofuel for wearable biofuel cells,glucose drives self-powered sensor and electrochromic display to produce color change,allowing for visually measurement of glucose levels in body fluids.Accurate detection results can be visualized by reading the RGB value with a cell phone.展开更多
The flexible wearable sensors with excellent stretchability,high sensitivity and good biocompatibility are significantly required for continuously physical condition tracking in health management and rehabilitation mo...The flexible wearable sensors with excellent stretchability,high sensitivity and good biocompatibility are significantly required for continuously physical condition tracking in health management and rehabilitation monitoring.Herein,we present a high-performance wearable sensor.The sensor is prepared with nanocomposite hydrogel by using silk fibroin(SF),polyacrylamide(PAM),polydopamine(PDA)and graphene oxide(GO).It can be used to monitor body motions(including large-scale and small-scale motions)as well as human electrophysiological(ECG)signals with high sensitivity,wide sensing range,and fast response time.Therefore,the proposed sensor is promising in the fields of rehabilitation,motion monitoring and disease diagnosis.展开更多
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 wearabl...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.展开更多
Human Activity Recognition (HAR) is an important way for lower limb exoskeleton robots to implement human-computer collaboration with users. Most of the existing methods in this field focus on a simple scenario recogn...Human Activity Recognition (HAR) is an important way for lower limb exoskeleton robots to implement human-computer collaboration with users. Most of the existing methods in this field focus on a simple scenario recognizing activities for specific users, which does not consider the individual differences among users and cannot adapt to new users. In order to improve the generalization ability of HAR model, this paper proposes a novel method that combines the theories in transfer learning and active learning to mitigate the cross-subject issue, so that it can enable lower limb exoskeleton robots being used in more complex scenarios. First, a neural network based on convolutional neural networks (CNN) is designed, which can extract temporal and spatial features from sensor signals collected from different parts of human body. It can recognize human activities with high accuracy after trained by labeled data. Second, in order to improve the cross-subject adaptation ability of the pre-trained model, we design a cross-subject HAR algorithm based on sparse interrogation and label propagation. Through leave-one-subject-out validation on two widely-used public datasets with existing methods, our method achieves average accuracies of 91.77% on DSAD and 80.97% on PAMAP2, respectively. The experimental results demonstrate the potential of implementing cross-subject HAR for lower limb exoskeleton robots.展开更多
The integration offlexible electronics with plant science has generated various plant-wearable sensors,yet challenges persist in their application to real-world agriculture,particularly in high-throughput set-tings.Ov...The integration offlexible electronics with plant science has generated various plant-wearable sensors,yet challenges persist in their application to real-world agriculture,particularly in high-throughput set-tings.Overcoming the trade-off between sensing sensitivity and range,adapting sensors to a wide range of crop types,and bridging the gap between sensor measurements and biological understandings remain primary obstacles.Here,we introduce PlantRing,an innovative,nano-flexible sensing system designed to address these challenges.PlantRing employs bio-sourced carbonized silk georgette as the strain-sensing material,offering an exceptional detection limit(0.03%–0.17%strain,depending on sensor model),high stretchability(tensile strain up to 100%),and remarkable durability(season-long use).PlantRing effectively monitors plant growth and water status by measuring organ circumference dy-namics,performing reliably under harsh conditions,and adapting to a wide range of plant species.Applying PlantRing to study fruit cracking in tomato and watermelon has revealed a novel hydraulic mechanism characterized by genotype-specific excess sapflow within the plant to fruiting branches.Its high-throughput application has enabled large-scale quantification of stomatal sensitivity to soil drought—a long-standing aspiration in plant biology—facilitating the selection of drought-tolerant germ-plasm.Combining PlantRing with a soybean mutant has led to the discovery of a potential novel function of the circadian clock gene GmLNK2 in stomatal regulation.More practically,integrating PlantRing into feedback irrigation achieves simultaneous water conservation and quality improvement,signifying a paradigm shift from reliance on experience or environmental cues to plant-based feedback control.Collectively,PlantRing represents a groundbreaking tool poised to revolutionize botanical studies,agri-culture,and forestry.展开更多
Sensing technologies have become an indispensable tool in fundamental research and social daily life.In the realm of diverse sensing technologies,biosensors and wearable sensors have emerged as star techniques in rese...Sensing technologies have become an indispensable tool in fundamental research and social daily life.In the realm of diverse sensing technologies,biosensors and wearable sensors have emerged as star techniques in research,having achieved extensive applications in a variety of fields such as healthcare,environmental monitoring,and food safety.They benefit from their high selectivity and sensitivity towards specific biomolecules,enabling the accurate detection of biomarkers related to diseases,pathogens in the environment and contaminants in food.With the continuous advancement of materials science and microelectronics technology,these two sensing modalities are expected to further revolutionize the way we perceive and interact with the surrounding environment and our own health status.展开更多
Hydrogel strain sensors represent an importan development for research into flexible electronics,being able to convert external stimuli into easily monitored electrical signals.However,finding simple and rapid prepara...Hydrogel strain sensors represent an importan development for research into flexible electronics,being able to convert external stimuli into easily monitored electrical signals.However,finding simple and rapid preparation methods,as well as ensuring compatibility between conductive fillers and the polymer matrix are stil the main challenges for conductive hydrogel applications In this work,we utilize MXene to coat liquid metal dro plets that have been broken by ultrasound while incorpo rating cellulose nanofibers to make them stably dispersed Electron paramagnetic resonance spectroscopy revealed that the obtained composite filler could catalyze the releas of additional hydroxyl radicals from ammonium persulfat to enable the rapid gelation of acrylic acid under ambien conditions.This unique property allows for the mold-based fabrication of hydrogels in various shapes,and we also explored the use of microfluidic devices for printing.Th conductive hydrogels showed good tensile properties small hysteresis loops,high self-healing efficiency(97%conductive recovery),and antimicrobial properties.When assembled into flexible sensors,the hydrogel can accu rately monitor body movements with stable repeatability The outstanding characteristics of the hydrogel not only offer a material basis for the development of novel flexibl sensors,but also have the potential for rapid,large-scale and customized preparation through fast gelation.展开更多
The field of human motion data capture and fusion has a broad range of potential applications and market opportunities.The capture of human motion data for wearable sensors is less costly and more convenient than othe...The field of human motion data capture and fusion has a broad range of potential applications and market opportunities.The capture of human motion data for wearable sensors is less costly and more convenient than other methods,but it also suffers from poor data capture accuracy and high latency.Consequently,in order to overcome the limitations of existing wearable sensors in data capture and fusion,the study initially constructed a model of the human joint and bone by combining the quaternion method and root bone human forward kinematics through mathematical modeling.Subsequently,the sensor data calibration was optimized,and the Madgwick algorithm was introduced to address the resulting issues.Finally,a novel human joint motion data capture and fusion model was proposed.The experimental results indicated that the maximum mean error and root mean square error of yaw angle of this new model were 1.21°and 1.17°,respectively.The mean error and root mean square error of pitch angle were maximum 1.24°and 1.19°,respectively.The maximum knee joint and elbow joint data capture errors were 3.8 and 6.1,respectively.The suggested approach,which offers a new path for technological advancement in this area,greatly enhances the precision and dependability of human motion capture,which has a broad variety of application possibilities.展开更多
Holographic optical elements(HOEs)are integral to advancements in optical sensing,augmented reality,solar energy harvesting,biomedical diagnostics,and many other fields,offering precise and versatile light manipulatio...Holographic optical elements(HOEs)are integral to advancements in optical sensing,augmented reality,solar energy harvesting,biomedical diagnostics,and many other fields,offering precise and versatile light manipulation capabilities.This study,to the best of the authors'knowledge,is the first to design and fabricate an HOE mutliwaveguide system using a thermally and environmentally stable photopolymerizable hybrid sol-gel(PHSG)for sensing applications.Using a 476.5 nm recording wavelength,60%diffraction efficiency PHSG holographic waveguides of spatial frequency of 1720 lines/mm were successfully fabricated to function as in-and out-couplers at 632.8 nm and 700 nm wavelength,respectively.The waveguides were integrated into a polydimethylsiloxane(PDMS)microfluidic system,guiding excitation light of 632.8 nm wavelength into and extracting fluorescence light signal peaking at 700 nm from a location filled with methylene blue water solution.Further,to demonstrate the potential of the proposed optical system,four holographic waveguides were recorded by peristrophic and angular multiplexing in the same location of the material and the input beam was delivered into four spatially separated channels by total internal reflection in the sol-gel layer,thus,successfully highlighting the capabilities and advantages of HOE waveguides for parallel interrogation of multiple locations in a wearable sensor.This study demonstrates the efficiency and versatility of PHSG-based HOE waveguides,underscoring their potential to enhance photonic device design and performance across various optical applications.展开更多
Ionogels have garnered significant attention in soft electronics,sensors,and biomedicine due to their combination of flexibility,thermal stability,and ionic conductivity.Nonetheless,challenges associated with designin...Ionogels have garnered significant attention in soft electronics,sensors,and biomedicine due to their combination of flexibility,thermal stability,and ionic conductivity.Nonetheless,challenges associated with designing ionogels with reliable properties for health monitoring scenarios still remain.This review offers a novel perspective on the development of wearable sensors for health monitoring by comprehensively examining ionogel synthesis methodologies,highlighting critical performance parameters,and exploring underexplored applications.First,the design principles governing polymer network optimization and advanced manufacturing techniques for ionogels are elucidated.Then,the strategies for enhancing critical performance are discussed,followed by an exploration of specific application scenarios,including noninvasive biochemical analysis,real-time motion monitoring,and disease-specific assessments.Finally,an outlook on future challenges and opportunities in the emerging field of ionogels is provided.The establishment of a hierarchical health monitoring framework that integrates molecular-,individual-,and systemic-level perspectives offers readers a unique and in-depth understanding,which advances the comprehension of this emerging field.展开更多
Conventional metal-oxide-semiconductor(MOS)gas sensors are limited in wearable gas detection due to their non-flexibility,high operating temperature,and less durability.In this study,a yarn-based superhydrophobic flex...Conventional metal-oxide-semiconductor(MOS)gas sensors are limited in wearable gas detection due to their non-flexibility,high operating temperature,and less durability.In this study,a yarn-based superhydrophobic flexible wearable sensor for room-temperature ammonia gas detection was prepared based on the nano-size effect of both nanocore yarns prepared through electrostatic spinning and MOS gas-sensitive materials synthesized via a two-step hydrothermal synthesis approach.The yarn sensor has a response sensitivity of 13.11 towards 100 ppm(1 ppm=10^(−6))ammonia at room temperature,a response time and a recovery time of 36 and 21 s,respectively,and a detection limit as low as 10 ppm with the sensitivity of up to 4.76 towards ammonia.In addition,it displays commendable linearity within the concentration range of 10‒100 ppm,accompanied by remarkable selectivity and stability,while the hydrophobicity angle reaches 155.74°.Furthermore,its sensing performance still maintains stability even after repeated bending and prolonged operation.The sensor also has stable mechanical properties and flexibility,and can be affixed onto the fabric surface through sewing,which has a specific potential for clothing use.展开更多
In this study,we presented a wearable electrochemical sensor for accurate and reliable cortisol detection in sweat.The sensor was built upon a novel platform by combination of conducting polyaniline(PANI)hydrogel and ...In this study,we presented a wearable electrochemical sensor for accurate and reliable cortisol detection in sweat.The sensor was built upon a novel platform by combination of conducting polyaniline(PANI)hydrogel and hydrophilic polypeptides,endowing the sensor with superior antifouling property.PANI hydrogel's distinctive water storage characteristic and the attachment of numerous antifouling peptides(Pep)effectively prevent nonspecific adsorption in complex human sweat environment.This innovative configuration significantly enhanced the accuracy of cortisol detection in complex sweat samples.The prepared biosensor was able to achieve reliable cortisol detection in both buffer solution and artificial sweat,covering a detection concentration range from 10^(-10)to 10^(-6)g/m L,with the minimum detection limitation of 33 pg/m L.And this electrochemical biosensor demonstrated outstanding selectivity,excellent stability,and good reproducibility.Notably,the cortisol levels were measured in volunteers during both morning and evening.The observed data exhibited distinct circadian rhythm,consistenting with the results gained from commercially available enzyme-linked immunosorption(ELISA)kit.This wearable biosensor shows giant potential for monitoring cortisol levels in human sweat,enabling real-time evaluation for mental and stress state.展开更多
Wearable sensors are pivotal for point-of-care diagnostics,yet their application in extreme conditions is rarely conducted.In this work,we present a wearable pH sensor using tungsten oxide aerogel(TOA)as the sensing m...Wearable sensors are pivotal for point-of-care diagnostics,yet their application in extreme conditions is rarely conducted.In this work,we present a wearable pH sensor using tungsten oxide aerogel(TOA)as the sensing material.With the advantages of large specific surface area,high porosity and interconnected network structures,TOA not only provides excellent pH sensing performance but also demonstrates remarkable structural and sensing stability.The potentiometric pH sensor exhibits a high sensitivity(−63.70 mV/pH),a low detectable limit(0.05)and a superior stability(maintained over 50,000 s).Integrated with a Bluetooth module,the wearable sensor achieves non-invasive and real-time pH monitoring on the human skin with minimal deviation(1.91%)compared to the commercial pH meter.More importantly,the anti-impact behaviors of the TOA-based sensing materials and chip,along with the pH wearable sensor on a pig exhibit an outstanding shock-resistance ability,with variations no more than 7.17%under an impact of 118.38 kPa.Therefore,this study shows great promise for the aerogel-based personalized health management in the extreme environment.展开更多
Flexible electronic technology has laid the foundation for complex human-computer interaction system,and has attracted great attention in the field of human motion detection and soft robotics.Graphene has received an ...Flexible electronic technology has laid the foundation for complex human-computer interaction system,and has attracted great attention in the field of human motion detection and soft robotics.Graphene has received an extensive attention due to its excellent electrical conductivity;however,how to use it to fabricate wearable flexible sensors with complex structures remains challenging.In this study,we studied the rheological behavior of graphene/polydimethylsiloxane ink and proposed an optimal graphene ratio,which makes the ink have an good printability and conductivity at the same time.Then,based on the theory of Peano fractal layout,we proposed a two-dimensional structure that can withstand multi-directional tension by replacing the traditional arris structure with the arc structure.After that,we manufactured circular arc fractal structure sensor by adjusting ink composition and printing structure through direct ink writing method.Finally,we evaluated the detection performance and repeatability of the sensor.This method provides a simple and effective solution for fabricating wearable flexible sensors and exhibits the potential to fabricate 3D complex flexible electronic devices.展开更多
Wearable healthcare sensors can convert various physical signals, physiological signals, and electrophysiological activities of the human body into quantifiable resistive or capacitive changes for real-time health mon...Wearable healthcare sensors can convert various physical signals, physiological signals, and electrophysiological activities of the human body into quantifiable resistive or capacitive changes for real-time health monitoring. Gallium(Ga)-based liquid metal(LM) has become an ideal candidate for wearable healthcare sensors due to its excellent physical and chemical properties, such as high stretchability, high electrical conductivity, self-healing and thermal conductivity, and good biocompatibility. However,the high surface tension of LM makes it difficult to be processed. After LM is modified, the LM surface tension is reduced to be able to form LM composites by tightly bonding with the elastomer matrix, and the LM composites exhibit enhanced electromechanical, thermal, and magnetic properties, among others. Here, we review the fabrication methods of LM composites;we describe in detail the composite forms of LM composites and recent advances in tensile, thermal and electrical conductivity, high dielectric constant and biocompatibility. Sensor devices(e.g.,piezoelectric sensors, friction electric sensors, strain sensors, and magnetic sensors) of LM composites for wearable healthcare monitoring are summarized. Finally, challenges and opportunities of LM composites in the neighborhood of wearable healthcare sensors are also discussed.展开更多
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 ...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.展开更多
基金financially supported by the National Key Research and Development Program of China(2022YFE0138900)the National Natural Science Foundation of China(21972017)+1 种基金the Fundamental Research Funds for the Central Universities of Ministry of Education of China(D5000240188)the"Scientific and Technical Innovation Action Plan"Basic Research Field of Shanghai Science and Technology Committee(19JC1410500)。
文摘Traditional hydrogels are inevitably damaged during practical applications,resulting in a gradual deterioration of their functional efficacy.A primary strategy to address this issue involves developing hydrogels with inherent self-healing properties.In this study,we report the synthesis of self-healing polyacrylate hydrogels that integrate zwitterions,hydrophilic nano-silica and aluminum ions.Due to the synergistic effect of multiple hydrogen bonds,coordination bonds and electrostatic interactions,the tensile strength of the hydrogel is enhanced from 15.1 to 162.6 kPa.Moreover,the electrical resistance and tensile strength of the hydrogel can almost recover to its initial values after 20 min of healing at room temperature,exhibiting remarkable self-healing performance.Furthermore,the zwitterionic polyacrylate hydrogel serves as a wearable sensor with the capability of accurately response to the bending and stretching of human joints,exhibting a gauge factor of 1.87 under tensile strain ranging from 80% to 100%.Even after being freezed at-20℃ for 3 h,the zwitterionic polyacrylate hydrogel retains its exceptional writing performance.In conclusion,the hydrogels developed in this study demonstrate significant potential for wearable electronics applications.
文摘In a recent study,Prof.Rui Min and collaborators published their paper in the journal of Opto-Electronic Science that is entitled"Smart photonic wristband for pulse wave monitoring".The paper introduces novel realization of a sensor that us-es a polymer optical multi-mode fiber to sense pulse wave bio-signal from a wrist by analyzing the specklegram mea-sured at the output of the fiber.Applying machine learning techniques over the pulse wave signal allowed medical diag-nostics and recognizing different gestures with accuracy rate of 95%.
基金financially supported by the National Natural Science Foundation of China(No.52125201)Beijing Natural Science Foundation(No.Z240025)and the Beijing Municipal Science and Technology(No.Z221100002722015).
文摘Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB BremenThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding thiswork through Large Group Project under grant number(RGP.2/568/45)The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University,Arar,KSA for funding this research work through the Project Number“NBU-FFR-2025-231-04”.
文摘Inertial Sensor-based Daily Activity Recognition(IS-DAR)requires adaptable,data-efficient methods for effective multi-sensor use.This study presents an advanced detection system using body-worn sensors to accurately recognize activities.A structured pipeline enhances IS-DAR by applying signal preprocessing,feature extraction and optimization,followed by classification.Before segmentation,a Chebyshev filter removes noise,and Blackman window-ing improves signal representation.Discriminative features-Gaussian Mixture Model(GMM)with Mel-Frequency Cepstral Coefficients(MFCC),spectral entropy,quaternion-based features,and Gammatone Cepstral Coefficients(GCC)-are fused to expand the feature space.Unlike existing approaches,the proposed IS-DAR system uniquely inte-grates diverse handcrafted features using a novel fusion strategy combined with Bayesian-based optimization,enabling a more accurate and generalized activity recognition.The key contribution lies in the joint optimization and fusion of features via Bayesian-based subset selection,resulting in a compact and highly discriminative feature representation.These features are then fed into a Convolutional Neural Network(CNN)to effectively detect spatial-temporal patterns in activity signals.Testing on two public datasets-IM-WSHA and ENABL3S-achieved accuracy levels of 93.0%and 92.0%,respectively.The integration of advanced feature extraction methods with fusion and optimization techniques significantly enhanced detection performance,surpassing traditional methods.The obtained results establish the effectiveness of the proposed IS-DAR system for deployment in real-world activity recognition applications.
基金supported by the National Natural Science Foundation of China(No.22174055)Key R&D Program of Zhenjiang City(No.NY2022012)。
文摘Wearable flexible sensor devices have the characteristics of lightweight and miniaturization.Currently,power supply and detection components limit the portability of wearable flexible sensor devices.Meanwhile,conventional liquid electrolytes are unsuitable for the integration of sensing devices.To address these constraints,wearable biofuel cells and flexible electrochromic displays have been introduced,which can improve integration with other devices,safety,and color-coded display data.Meanwhile,electrode chips prepared through screen printing technology can further improve portability.In this work,a wearable sensor device with screen-printed chips was constructed and used for non-invasive detection of glucose.Agarose gel electrolytes doped with PDA-CNTs were prepared,and the mechanical strength and moisture retention were significantly improved compared with traditional gel electrolytes.Glucose in interstitial fluid was non-invasive extracted to the skin surface using reverse iontophoresis.As a biofuel for wearable biofuel cells,glucose drives self-powered sensor and electrochromic display to produce color change,allowing for visually measurement of glucose levels in body fluids.Accurate detection results can be visualized by reading the RGB value with a cell phone.
基金Smart Medicine Research Project of Chongqing Medical University in 2020(YJSZHYX202022)Smart Medicine Research Project of Chongqing Medical University(ZHYX2019019)Chongqing Research Program of Basic Research and Frontier Technology(cstc2018jcyjAX0165).
文摘The flexible wearable sensors with excellent stretchability,high sensitivity and good biocompatibility are significantly required for continuously physical condition tracking in health management and rehabilitation monitoring.Herein,we present a high-performance wearable sensor.The sensor is prepared with nanocomposite hydrogel by using silk fibroin(SF),polyacrylamide(PAM),polydopamine(PDA)and graphene oxide(GO).It can be used to monitor body motions(including large-scale and small-scale motions)as well as human electrophysiological(ECG)signals with high sensitivity,wide sensing range,and fast response time.Therefore,the proposed sensor is promising in the fields of rehabilitation,motion monitoring and disease diagnosis.
基金supported by the Thailand Science Research and Innovation Fundthe University of Phayao(Grant No.FF66-UoE001)King Mongkut’s University of Technology North Bangkok,Contract No.KMUTNB-66-KNOW-05.
文摘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.
文摘Human Activity Recognition (HAR) is an important way for lower limb exoskeleton robots to implement human-computer collaboration with users. Most of the existing methods in this field focus on a simple scenario recognizing activities for specific users, which does not consider the individual differences among users and cannot adapt to new users. In order to improve the generalization ability of HAR model, this paper proposes a novel method that combines the theories in transfer learning and active learning to mitigate the cross-subject issue, so that it can enable lower limb exoskeleton robots being used in more complex scenarios. First, a neural network based on convolutional neural networks (CNN) is designed, which can extract temporal and spatial features from sensor signals collected from different parts of human body. It can recognize human activities with high accuracy after trained by labeled data. Second, in order to improve the cross-subject adaptation ability of the pre-trained model, we design a cross-subject HAR algorithm based on sparse interrogation and label propagation. Through leave-one-subject-out validation on two widely-used public datasets with existing methods, our method achieves average accuracies of 91.77% on DSAD and 80.97% on PAMAP2, respectively. The experimental results demonstrate the potential of implementing cross-subject HAR for lower limb exoskeleton robots.
基金the Key Scientific and Technological Grant of Zhejiang for Breeding New Agricultural Varieties(2021C02066-5,2021C02067-7)for their support。
文摘The integration offlexible electronics with plant science has generated various plant-wearable sensors,yet challenges persist in their application to real-world agriculture,particularly in high-throughput set-tings.Overcoming the trade-off between sensing sensitivity and range,adapting sensors to a wide range of crop types,and bridging the gap between sensor measurements and biological understandings remain primary obstacles.Here,we introduce PlantRing,an innovative,nano-flexible sensing system designed to address these challenges.PlantRing employs bio-sourced carbonized silk georgette as the strain-sensing material,offering an exceptional detection limit(0.03%–0.17%strain,depending on sensor model),high stretchability(tensile strain up to 100%),and remarkable durability(season-long use).PlantRing effectively monitors plant growth and water status by measuring organ circumference dy-namics,performing reliably under harsh conditions,and adapting to a wide range of plant species.Applying PlantRing to study fruit cracking in tomato and watermelon has revealed a novel hydraulic mechanism characterized by genotype-specific excess sapflow within the plant to fruiting branches.Its high-throughput application has enabled large-scale quantification of stomatal sensitivity to soil drought—a long-standing aspiration in plant biology—facilitating the selection of drought-tolerant germ-plasm.Combining PlantRing with a soybean mutant has led to the discovery of a potential novel function of the circadian clock gene GmLNK2 in stomatal regulation.More practically,integrating PlantRing into feedback irrigation achieves simultaneous water conservation and quality improvement,signifying a paradigm shift from reliance on experience or environmental cues to plant-based feedback control.Collectively,PlantRing represents a groundbreaking tool poised to revolutionize botanical studies,agri-culture,and forestry.
文摘Sensing technologies have become an indispensable tool in fundamental research and social daily life.In the realm of diverse sensing technologies,biosensors and wearable sensors have emerged as star techniques in research,having achieved extensive applications in a variety of fields such as healthcare,environmental monitoring,and food safety.They benefit from their high selectivity and sensitivity towards specific biomolecules,enabling the accurate detection of biomarkers related to diseases,pathogens in the environment and contaminants in food.With the continuous advancement of materials science and microelectronics technology,these two sensing modalities are expected to further revolutionize the way we perceive and interact with the surrounding environment and our own health status.
基金financially supported by China Scholarship Council program(No.202306380028)the National Natural Science Foundation of China(No.11204097)+3 种基金the Spanish Ministry of Science(Nos.RYC2020-945030119-I and PID2023-151682NA-I00 funded by MCIN/AEI/10.13039/501100011033/and FEDER)Unidades de Excelencia Maria de Maeztu 2021(No.CEX2021-001202-M)the Spanish Ministry of Science,Innovation and Universities(MCIU),State Bureau of Investigation(AIE),the European Regional Development Fund(FEDER)(No.PGC2018-096958-B-I00)the Catalonian Government(No.2021 SGR00646)
文摘Hydrogel strain sensors represent an importan development for research into flexible electronics,being able to convert external stimuli into easily monitored electrical signals.However,finding simple and rapid preparation methods,as well as ensuring compatibility between conductive fillers and the polymer matrix are stil the main challenges for conductive hydrogel applications In this work,we utilize MXene to coat liquid metal dro plets that have been broken by ultrasound while incorpo rating cellulose nanofibers to make them stably dispersed Electron paramagnetic resonance spectroscopy revealed that the obtained composite filler could catalyze the releas of additional hydroxyl radicals from ammonium persulfat to enable the rapid gelation of acrylic acid under ambien conditions.This unique property allows for the mold-based fabrication of hydrogels in various shapes,and we also explored the use of microfluidic devices for printing.Th conductive hydrogels showed good tensile properties small hysteresis loops,high self-healing efficiency(97%conductive recovery),and antimicrobial properties.When assembled into flexible sensors,the hydrogel can accu rately monitor body movements with stable repeatability The outstanding characteristics of the hydrogel not only offer a material basis for the development of novel flexibl sensors,but also have the potential for rapid,large-scale and customized preparation through fast gelation.
文摘The field of human motion data capture and fusion has a broad range of potential applications and market opportunities.The capture of human motion data for wearable sensors is less costly and more convenient than other methods,but it also suffers from poor data capture accuracy and high latency.Consequently,in order to overcome the limitations of existing wearable sensors in data capture and fusion,the study initially constructed a model of the human joint and bone by combining the quaternion method and root bone human forward kinematics through mathematical modeling.Subsequently,the sensor data calibration was optimized,and the Madgwick algorithm was introduced to address the resulting issues.Finally,a novel human joint motion data capture and fusion model was proposed.The experimental results indicated that the maximum mean error and root mean square error of yaw angle of this new model were 1.21°and 1.17°,respectively.The mean error and root mean square error of pitch angle were maximum 1.24°and 1.19°,respectively.The maximum knee joint and elbow joint data capture errors were 3.8 and 6.1,respectively.The suggested approach,which offers a new path for technological advancement in this area,greatly enhances the precision and dependability of human motion capture,which has a broad variety of application possibilities.
基金European Space Agency(4000129503/20/NL/PG/pt)Science Foundation Ireland(20/FFP-P/8851)。
文摘Holographic optical elements(HOEs)are integral to advancements in optical sensing,augmented reality,solar energy harvesting,biomedical diagnostics,and many other fields,offering precise and versatile light manipulation capabilities.This study,to the best of the authors'knowledge,is the first to design and fabricate an HOE mutliwaveguide system using a thermally and environmentally stable photopolymerizable hybrid sol-gel(PHSG)for sensing applications.Using a 476.5 nm recording wavelength,60%diffraction efficiency PHSG holographic waveguides of spatial frequency of 1720 lines/mm were successfully fabricated to function as in-and out-couplers at 632.8 nm and 700 nm wavelength,respectively.The waveguides were integrated into a polydimethylsiloxane(PDMS)microfluidic system,guiding excitation light of 632.8 nm wavelength into and extracting fluorescence light signal peaking at 700 nm from a location filled with methylene blue water solution.Further,to demonstrate the potential of the proposed optical system,four holographic waveguides were recorded by peristrophic and angular multiplexing in the same location of the material and the input beam was delivered into four spatially separated channels by total internal reflection in the sol-gel layer,thus,successfully highlighting the capabilities and advantages of HOE waveguides for parallel interrogation of multiple locations in a wearable sensor.This study demonstrates the efficiency and versatility of PHSG-based HOE waveguides,underscoring their potential to enhance photonic device design and performance across various optical applications.
基金supported by the Startup Foundation of Beijing Institute of Technology(3160013532102,3160011182007).
文摘Ionogels have garnered significant attention in soft electronics,sensors,and biomedicine due to their combination of flexibility,thermal stability,and ionic conductivity.Nonetheless,challenges associated with designing ionogels with reliable properties for health monitoring scenarios still remain.This review offers a novel perspective on the development of wearable sensors for health monitoring by comprehensively examining ionogel synthesis methodologies,highlighting critical performance parameters,and exploring underexplored applications.First,the design principles governing polymer network optimization and advanced manufacturing techniques for ionogels are elucidated.Then,the strategies for enhancing critical performance are discussed,followed by an exploration of specific application scenarios,including noninvasive biochemical analysis,real-time motion monitoring,and disease-specific assessments.Finally,an outlook on future challenges and opportunities in the emerging field of ionogels is provided.The establishment of a hierarchical health monitoring framework that integrates molecular-,individual-,and systemic-level perspectives offers readers a unique and in-depth understanding,which advances the comprehension of this emerging field.
基金supported by the Fund of China National-Textile and Apparel Council(Grant Nos.2022033 and 2022015).
文摘Conventional metal-oxide-semiconductor(MOS)gas sensors are limited in wearable gas detection due to their non-flexibility,high operating temperature,and less durability.In this study,a yarn-based superhydrophobic flexible wearable sensor for room-temperature ammonia gas detection was prepared based on the nano-size effect of both nanocore yarns prepared through electrostatic spinning and MOS gas-sensitive materials synthesized via a two-step hydrothermal synthesis approach.The yarn sensor has a response sensitivity of 13.11 towards 100 ppm(1 ppm=10^(−6))ammonia at room temperature,a response time and a recovery time of 36 and 21 s,respectively,and a detection limit as low as 10 ppm with the sensitivity of up to 4.76 towards ammonia.In addition,it displays commendable linearity within the concentration range of 10‒100 ppm,accompanied by remarkable selectivity and stability,while the hydrophobicity angle reaches 155.74°.Furthermore,its sensing performance still maintains stability even after repeated bending and prolonged operation.The sensor also has stable mechanical properties and flexibility,and can be affixed onto the fabric surface through sewing,which has a specific potential for clothing use.
基金supported by the National Natural Science Foundation of China(Nos.22174082,22374085,22105113)the Key Research and Development Program of Shandong Province(No.2021ZDSYS30)Natural Science Foundation of Shandong Province,China(No.ZR2024QB059)。
文摘In this study,we presented a wearable electrochemical sensor for accurate and reliable cortisol detection in sweat.The sensor was built upon a novel platform by combination of conducting polyaniline(PANI)hydrogel and hydrophilic polypeptides,endowing the sensor with superior antifouling property.PANI hydrogel's distinctive water storage characteristic and the attachment of numerous antifouling peptides(Pep)effectively prevent nonspecific adsorption in complex human sweat environment.This innovative configuration significantly enhanced the accuracy of cortisol detection in complex sweat samples.The prepared biosensor was able to achieve reliable cortisol detection in both buffer solution and artificial sweat,covering a detection concentration range from 10^(-10)to 10^(-6)g/m L,with the minimum detection limitation of 33 pg/m L.And this electrochemical biosensor demonstrated outstanding selectivity,excellent stability,and good reproducibility.Notably,the cortisol levels were measured in volunteers during both morning and evening.The observed data exhibited distinct circadian rhythm,consistenting with the results gained from commercially available enzyme-linked immunosorption(ELISA)kit.This wearable biosensor shows giant potential for monitoring cortisol levels in human sweat,enabling real-time evaluation for mental and stress state.
基金supported by the National Natural Science Foundation of China(Nos.22374119 and 22274127)the Research Fund of the State Key Laboratory of Solidification Processing(NPU),China(No.2021-QZ-01)+1 种基金the Key Project of Natural Science Fund of Shaanxi Province(Nos.2023-JC-ZD-06 and 2024JC-YBQN-0636)the Open Project of the State Key Laboratory of Transducer Technology(No.SKT2307).
文摘Wearable sensors are pivotal for point-of-care diagnostics,yet their application in extreme conditions is rarely conducted.In this work,we present a wearable pH sensor using tungsten oxide aerogel(TOA)as the sensing material.With the advantages of large specific surface area,high porosity and interconnected network structures,TOA not only provides excellent pH sensing performance but also demonstrates remarkable structural and sensing stability.The potentiometric pH sensor exhibits a high sensitivity(−63.70 mV/pH),a low detectable limit(0.05)and a superior stability(maintained over 50,000 s).Integrated with a Bluetooth module,the wearable sensor achieves non-invasive and real-time pH monitoring on the human skin with minimal deviation(1.91%)compared to the commercial pH meter.More importantly,the anti-impact behaviors of the TOA-based sensing materials and chip,along with the pH wearable sensor on a pig exhibit an outstanding shock-resistance ability,with variations no more than 7.17%under an impact of 118.38 kPa.Therefore,this study shows great promise for the aerogel-based personalized health management in the extreme environment.
基金the National Key Research and Development Program of China(No.2020YFB1313100)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA16020803)+2 种基金the National Natural Science Foundation of China(Nos.51875557 and 52205319)the Research Equipment Development Program of the Chinese Academy of Sciences(No.YJKYYQ20190045)the Foundation of State Key Laboratory of Robotics(Nos.2021-Z01,2022-Z04 and 2023-Z01)。
文摘Flexible electronic technology has laid the foundation for complex human-computer interaction system,and has attracted great attention in the field of human motion detection and soft robotics.Graphene has received an extensive attention due to its excellent electrical conductivity;however,how to use it to fabricate wearable flexible sensors with complex structures remains challenging.In this study,we studied the rheological behavior of graphene/polydimethylsiloxane ink and proposed an optimal graphene ratio,which makes the ink have an good printability and conductivity at the same time.Then,based on the theory of Peano fractal layout,we proposed a two-dimensional structure that can withstand multi-directional tension by replacing the traditional arris structure with the arc structure.After that,we manufactured circular arc fractal structure sensor by adjusting ink composition and printing structure through direct ink writing method.Finally,we evaluated the detection performance and repeatability of the sensor.This method provides a simple and effective solution for fabricating wearable flexible sensors and exhibits the potential to fabricate 3D complex flexible electronic devices.
基金financially supported by Mianyang Science and Technology Bureau(No.2023ZYDF081)the Research topic of Zhongnanshan Youth Science and Technology Innovation Award Fund of China Youth Entrepreneurship and Employment Foundation
文摘Wearable healthcare sensors can convert various physical signals, physiological signals, and electrophysiological activities of the human body into quantifiable resistive or capacitive changes for real-time health monitoring. Gallium(Ga)-based liquid metal(LM) has become an ideal candidate for wearable healthcare sensors due to its excellent physical and chemical properties, such as high stretchability, high electrical conductivity, self-healing and thermal conductivity, and good biocompatibility. However,the high surface tension of LM makes it difficult to be processed. After LM is modified, the LM surface tension is reduced to be able to form LM composites by tightly bonding with the elastomer matrix, and the LM composites exhibit enhanced electromechanical, thermal, and magnetic properties, among others. Here, we review the fabrication methods of LM composites;we describe in detail the composite forms of LM composites and recent advances in tensile, thermal and electrical conductivity, high dielectric constant and biocompatibility. Sensor devices(e.g.,piezoelectric sensors, friction electric sensors, strain sensors, and magnetic sensors) of LM composites for wearable healthcare monitoring are summarized. Finally, challenges and opportunities of LM composites in the neighborhood of wearable healthcare sensors are also discussed.
基金Jin Wu acknowledges financial support from the National Natural Science Foundation of China(No.61801525)the Guangdong Basic and Applied Basic Research Foundation(No.2020A1515010693)+1 种基金the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(No.22lgqb17)the Independent Fund of the State Key Laboratory of Optoelectronic Materials and Technologies(Sun Yat-sen University)under grant No.OEMT-2022-ZRC-05.
文摘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.
