Chronic diseases are a growing concern worldwide,with nearly 25% of adults suffering from one or more chronic health conditions,thus placing a heavy burden on individuals,families,and healthcare systems.With the adven...Chronic diseases are a growing concern worldwide,with nearly 25% of adults suffering from one or more chronic health conditions,thus placing a heavy burden on individuals,families,and healthcare systems.With the advent of the“Smart Healthcare”era,a series of cutting-edge technologies has brought new experiences to the management of chronic diseases.Among them,smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state.However,how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management,in terms of quality of life,patient outcomes,and privacy protection,is an urgent issue that needs to be addressed.Artificial intelligence(AI)can provide intelligent suggestions by analyzing a patient’s physiological data from wearable devices for the diagnosis and treatment of diseases.In addition,blockchain can improve healthcare services by authorizing decentralized data sharing,protecting the privacy of users,providing data empowerment,and ensuring the reliability of data management.Integrating AI,blockchain,and wearable technology could optimize the existing chronic disease management models,with a shift from a hospital-centered model to a patient-centered one.In this paper,we conceptually demonstrate a patient-centric technical framework based on AI,blockchain,and wearable technology and further explore the application of these integrated technologies in chronic disease management.Finally,the shortcomings of this new paradigm and future research directions are also discussed.展开更多
The field of gastroenterology has recently seen a surge in wearable technology to monitor physical activity,sleep quality,pain,and even gut activity.The past decade has seen the emergence of wearable devices including...The field of gastroenterology has recently seen a surge in wearable technology to monitor physical activity,sleep quality,pain,and even gut activity.The past decade has seen the emergence of wearable devices including Fitbit,Apple Watch,AbStats,and ingestible sensors.In this review,we discuss current and future devices designed to measure sweat biomarkers,steps taken,sleep efficiency,gastric electrical activity,stomach pH,and intestinal contents.We also summarize several clinical studies to better understand wearable devices so that we may assess their potential benefit in improving healthcare while also weighing the challenges that must be addressed.展开更多
Wearable technology in the management of chronic diseases has emerged as a significant and growing concern in healthcare.These technologies,including smartwatches,fitness trackers,and other sensor-based devices,offer ...Wearable technology in the management of chronic diseases has emerged as a significant and growing concern in healthcare.These technologies,including smartwatches,fitness trackers,and other sensor-based devices,offer continuous monitoring and real-time data collection for individuals with chronic conditions.The data collected can include vital signs,activity levels,sleep patterns,and more,providing valuable insights into a patient's health.This trend is particularly relevant in the context of chronic diseases,such as diabetes,cardiovascular conditions,and respiratory disorders,where continuous monitoring is crucial for effective management.Wearable devices empower patients to actively participate in their healthcare by facilitating self-monitoring and promoting healthy behaviors.Healthcare providers can also leverage the data generated by these devices to make informed decisions,personalize treatment plans,and intervene proactively.However,challenges exist,such as data security and privacy concerns,the accuracy of the collected information,and the need for effective integration into existing healthcare systems.Despite these challenges,the increasing adoption of wearable technology in chronic disease management reflects a promising avenue for improving patient outcomes and reducing healthcare costs through preventive and personalized care.展开更多
The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activit...The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activity, sedentary habits, sleep patterns) within the 24-h cycle of daily life. Wearables are applied in research, clinical practice, and as lifestyle devices;most obvious, they promise to be a key element for increasing human physical activity, one of the biggest health challenges nowadays.展开更多
Introduction:Consumer wearables increasingly provide users with Composite Health Scores(CHS)–integrated biometric indices that claim to quantify readiness,recovery,stress,or overall well-being.Despite their growing a...Introduction:Consumer wearables increasingly provide users with Composite Health Scores(CHS)–integrated biometric indices that claim to quantify readiness,recovery,stress,or overall well-being.Despite their growing adoption,the validity,transparency,and physiological relevance of these scores remain unclear.This study systematically evaluates CHS fromleading wearablemanufacturers to assess their underlying methodologies,contributors,and scientific basis.Content:Information was synthesised from publicly available company documentation,including technical white papers,user manuals,app interfaces,and research literature where available.We identified 14 CHS across 10 major wearable manufacturers,including Fitbit(Daily Readiness),Garmin(Body Battery^(TM)and Training Readiness),Oura(Readiness and Resilience),WHOOP(Strain,Recovery,and Stress Monitor),Polar(Nightly Recharge^(TM)),Samsung(Energy Score),Suunto(Body Resources),Ultrahuman(Dynamic Recovery),Coros(Daily Stress),and Withings(Health Improvement Score).The most frequently incorporated biometric contributors in this catalogue of CHS were heart rate variability(86%),resting heart rate(79%),physical activity(71%),and sleep duration(71%).However,significant discrepancies were identified in data collection timeframes,metric weighting,and proprietary scoring methodologies.None of the manufacturers disclosed their exact algorithmic formulas,and few provided empirical validation or peer-reviewed evidence supporting the accuracy or clinical relevance of their scores.Summary and outlook:While the concept of CHS represent a promising innovation in digital health,their scientific validity,transparency,and clinical applicability remain uncertain.Future research should focus on establishing standardized sensor fusion frameworks,improving algorithmic transparency,and evaluating CHS across diverse populations.Greater collaboration between industry,researchers,and clinicians is essential to ensure these indices serve as meaningful health metrics rather than opaque consumer tools.展开更多
Adolescent idiopathic scoliosis(AIS)is a dynamic progression during growth,which requires long-term collaborations and efforts from clinicians,patients and their families.It would be beneficial to have a precise inter...Adolescent idiopathic scoliosis(AIS)is a dynamic progression during growth,which requires long-term collaborations and efforts from clinicians,patients and their families.It would be beneficial to have a precise intervention based on cross-scale understandings of the etiology,real-time sensing and actuating to enable early detection,screening and personalized treatment.We argue that merging computational intelligence and wearable technologies can bridge the gap between the current trajectory of the techniques applied to AIS and this vision.Wearable technologies such as inertial measurement units(IMUs)and surface electromyography(sEMG)have shown great potential in monitoring spinal curvature and muscle activity in real-time.For instance,IMUs can track the kinematics of the spine during daily activities,while sEMG can detect asymmetric muscle activation patterns that may contribute to scoliosis progression.Computational intelligence,particularly deep learning algorithms,can process these multi-modal data streams to identify early signs of scoliosis and adapt treatment strategies dynamically.By using their combination,we can find potential solutions for a better understanding of the disease,a more effective and intelligent way for treatment and rehabilitation.展开更多
Objective:Behavioral interventions have been shown to ameliorate the electroencephalogram(EEG)dynamics underlying the behavioral symptoms of autism spectrum disorder(ASD),while studies have also demonstrated that mirr...Objective:Behavioral interventions have been shown to ameliorate the electroencephalogram(EEG)dynamics underlying the behavioral symptoms of autism spectrum disorder(ASD),while studies have also demonstrated that mirror neuron mu rhythm-based EEG neurofeedback training improves the behavioral functioning of individuals with ASD.This study aimed to test the effects of a wearable mu rhythm neurofeedback training system based on machine learning algorithms for children with autism.Methods:A randomized,placebo-controlled study was carried out on 60 participants aged 3 to 6 years who were diagnosed with autism,at two center-based intervention sites.The neurofeedback group received active mu rhythm neurofeedback training,while the control group received a sham neurofeedback training.Other behavioral intervention programs were similar between the two groups.Results:After 60 sessions of treatment,both groups showed significant improvements in several domains including language,social and problem behavior.The neurofeedback group showed significantly greater improvements in expressive language(P=0.013)and cognitive awareness(including joint attention,P=0.003)than did the placebo-controlled group.Conclusion:Artificial intelligence-powered wearable EEG neurofeedback,as a type of brain-computer interface application,is a promising assistive technology that can provide targeted intervention for the core brain mechanisms underlying ASD symptoms.展开更多
Walkability is an essential aspect of urban transportation systems. Properly designed walking paths can enhance transportation safety, encourage pedestrian activity, and improve community quality of life. This, in tur...Walkability is an essential aspect of urban transportation systems. Properly designed walking paths can enhance transportation safety, encourage pedestrian activity, and improve community quality of life. This, in turn, can help achieve sustainable development goals in urban areas. This pilot study uses wearable technology data to present a new method for measuring pedestrian stress in urban environments and the results were presented as an interactive geographic information system map to support risk-informed decision-making. The approach involves analyzing data from wearable devices using heart rate variability (RMSSD and slope analysis) to identify high-stress locations. This data-driven approach can help urban planners and safety experts identify and address pedestrian stressors, ultimately creating safer, more walkable cities. The study addresses a significant challenge in pedestrian safety by providing insights into factors and locations that trigger stress in pedestrians. During the pilot study, high-stress pedestrian experiences were identified due to issues like pedestrian-scooter interaction on pedestrian paths, pedestrian behavior around high foot traffic areas, and poor visibility at pedestrian crossings due to inadequate lighting.展开更多
The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical r...The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.展开更多
The integration of digital technologies into oral health care is transforming the field, driving advancements in diagnostic precision, patient engagement, and access to care. This review evaluates the impact of mobile...The integration of digital technologies into oral health care is transforming the field, driving advancements in diagnostic precision, patient engagement, and access to care. This review evaluates the impact of mobile health (mHealth) applications, tele-dentistry, artificial intelligence (AI), wearable devices, and advanced imaging systems on modern dentistry. Synthesizing findings from 125 studies published between 2010 and 2024, the paper identifies key achievements, including improved patient compliance, enhanced diagnostic capabilities, and expanded access to care in underserved areas. Tele-dentistry has been pivotal in bridging geographical gaps, particularly during the COVID-19 pandemic, while AI tools have revolutionized diagnostics and personalized treatment planning. Wearable devices and mHealth applications have empowered patients with real-time feedback, fostering sustained adherence to oral hygiene practices. The review also highlights the potential of digital tools to reduce healthcare disparities and operational costs, paving the way for more equitable and efficient dental care. By outlining critical advancements and future directions, this paper underscores the transformative potential of digital health technologies in dentistry. It advocates for further research on data security, interoperability, and innovative applications of AI to maximize the benefits of these tools, ultimately shaping a more accessible and patient-focused oral health ecosystem.展开更多
As the population across the globe continues to dramatically increase,the prevalence of cognitive impairment and dementia will inevitably increase as well,placing increasing burden on families and health care systems....As the population across the globe continues to dramatically increase,the prevalence of cognitive impairment and dementia will inevitably increase as well,placing increasing burden on families and health care systems.Technological advancements over the past decade provide potential benefit in not only relieving caregiver burden of caring for a loved one with dementia,but also enables individuals with dementia to age in place.Technological devices have served to improve functioning,tracking and mobility.Similarly,smartphones,tablets and the ubiquitous world wide web have facilitated the dissemination of health information to previously hard to reach populations largely through use of various social media platforms.In this review,we discuss the current and future uses of technology via devices and social media to promote healthy aging in individuals with dementia,and also limitations and challenges to consider in the future.展开更多
Wearable technologies have the potential to become a valuable influence on human daily life where they may enable observing the world in new ways,including,for example,using augmented reality(AR)applications.Wearable ...Wearable technologies have the potential to become a valuable influence on human daily life where they may enable observing the world in new ways,including,for example,using augmented reality(AR)applications.Wearable technology uses electronic devices that may be carried as accessories,clothes,or even embedded in the user's body.Although the potential benefits of smart wearables are numerous,their extensive and continual usage creates several privacy concerns and tricky information security challenges.In this paper,we present a comprehensive survey of recent privacy-preserving big data analytics applications based on wearable sensors.We highlight the fundamental features of security and privacy for wearable device applications.Then,we examine the utilization of deep learning algorithms with cryptography and determine their usability for wearable sensors.We also present a case study on privacy-preserving machine learning techniques.Herein,we theoretically and empirically evaluate the privacy-preserving deep learning framework's performance.We explain the implementation details of a case study of a secure prediction service using the convolutional neural network(CNN)model and the Cheon-Kim-Kim-Song(CHKS)homomorphic encryption algorithm.Finally,we explore the obstacles and gaps in the deployment of practical real-world applications.Following a comprehensive overview,we identify the most important obstacles that must be overcome and discuss some interesting future research directions.展开更多
Background:Physical activity(PA)is important for cancer survivors.Trials of remotely delivered interventions are needed to assist in reaching under-served non-metropolitan cancer survivors.The objective of this study ...Background:Physical activity(PA)is important for cancer survivors.Trials of remotely delivered interventions are needed to assist in reaching under-served non-metropolitan cancer survivors.The objective of this study was to ascertain whether wearable technology,coupled with health coaching was effective in increasing PA in breast and colorectal cancer survivors living in regional and remote areas in Australia.Methods:Cancer survivors from 5 states were randomized to intervention and control arms.Intervention participants were given a Fitbit Charge 2TMand received up to 6 telephone health coaching sessions.Control participants received PA print materials.Accelerometer assessments at baseline and 12 weeks measured moderate-to-vigorous PA(MVPA),light PA,and sedentary behavior.Results:Eighty-seven participants were recruited(age=63±11 years;74(85%)female).There was a significant net improvement in MVPA of 49.8 min/week,favoring the intervention group(95%confidence interval(95%CI):13.6-86.1,p=0.007).There was also a net increase in MVPA bouts of 39.5 min/week(95%CI:11.9-67.1,p=0.005),favoring the intervention group.Both groups improved light PA and sedentary behavior,but there were no between-group differences.Conclusion:This’s the first study to demonstrate that,when compared to standard practice(i.e.,PA education),a wearable technology intervention coupled with distance-based health coaching,improves MVPA in non-metropolitan cancer survivors.The results display promise for the use of scalable interventions using smart wearable technology in conjunction with phone-based health coaching to foster increased PA in geographically disadvantaged cancer survivors.展开更多
Wearable technology has revolutionized personalized healthcare and human–machine interfaces[1,2].While conventional devices,such as watches,rings,and chest straps,demonstrate utility in localized physiological monito...Wearable technology has revolutionized personalized healthcare and human–machine interfaces[1,2].While conventional devices,such as watches,rings,and chest straps,demonstrate utility in localized physiological monitoring,they exhibit inherent limitations in mechanical compliance and ergonomic adaptability.These systems fundamentally lack the capability to capture the body’s spatially distributed,multimodal biosignals(biopotential,optical,thermal,and mechanical)with precision due to their single-node measurement paradigm.展开更多
Cardiovascular diseases remain a leading global cause of mortality,underscoring the urgent need for intelligent diagnostic tools to enhance early detection,prediction,diagnosis,prevention,treatment,and recovery.This d...Cardiovascular diseases remain a leading global cause of mortality,underscoring the urgent need for intelligent diagnostic tools to enhance early detection,prediction,diagnosis,prevention,treatment,and recovery.This demand has spurred the advancement of wearable and flexible technologies,revolutionizing continuous,noninvasive,and remote heart sound(HS)monitoring—a vital avenue for assessing heart activity.The conventional stethoscope,used to listen to HSs,has limitations in terms of its physical structure,as it is inflexible and bulky,which restricts its prospective applications.Recently,mechanoacoustic sensors have made remarkable advancements,evolving from primitive forms to soft,flexible,and wearable designs.This article provides an in-depth review of the latest scientific and technological advancements by addressing various topics,including different types of sensors,sensing materials,design principles,denoising techniques,and clinical applications of flexible and wearable HS sensors.This transformative potential lies in the capacity for ongoing,remote,and personalized monitoring,promising enhanced patient outcomes,amplified remote monitoring capabilities,and timely diagnoses.Last,the article highlights current challenges and prospects for the future,suggesting techniques to advance HS sensing technologies for exciting real‐time applications.展开更多
The conductive polymer poly-3,4-ethylenedioxythiophene(PEDOT),recognized for its superior electrical conductivity and biocompatibility,has become an attractive material for developing wearable technologies and bioelec...The conductive polymer poly-3,4-ethylenedioxythiophene(PEDOT),recognized for its superior electrical conductivity and biocompatibility,has become an attractive material for developing wearable technologies and bioelectronics.Nevertheless,the complexities associated with PEDOT's patterning synthesis on diverse substrates persist despite recent technological progress.In this study,we introduce a novel deep eutectic solvent(DES)-induced vapor phase polymerization technique,facilitating nonrestrictive patterning polymerization of PEDOT across diverse substrates.By controlling the quantity of DES adsorbed per unit area on the substrates,PEDOT can be effectively patternized on cellulose,wood,plastic,glass,and even hydrogels.The resultant patterned PEDOT exhibits numerous benefits,such as an impressive electronic conductivity of 282 S·m-1,a high specific surface area of 5.29 m^(2)·g-1,and an extensive electrochemical stability range from-1.4 to 2.4 V in a phosphate-buffered saline.To underscore the practicality and diverse applications of this DES-induced approach,we present multiple examples emphasizing its integration into self-supporting flexible electrodes,neuroelectrode interfaces,and precision circuit repair methodologies.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
With the development of ordnance technology,the survival and safety of individual combatants in hightech warfare are under serious threat,and the Personal Protective Equipment(PPE),as an important guarantee to reduce ...With the development of ordnance technology,the survival and safety of individual combatants in hightech warfare are under serious threat,and the Personal Protective Equipment(PPE),as an important guarantee to reduce casualties and maintain military combat effectiveness,is widely developed.This paper systematically reviewed various PPE based on individual combat through literature research and comprehensive discussion,and introduced in detail the latest application progress of PPE in terms of material and technology from three aspects:individual integrated protection system,traditional protection equipment,and intelligent protection equipment,respectively,and discussed in depth the functional improvement and optimization status brought by advanced technology for PPE,focusing on the achievements of individual equipment technology application.Finally,the problems and technical bottlenecks in the development of PPE were analyzed and summarized,and the development trend of PPE were pointed out.The results of the review will provide a forward-looking reference for the current development of individual PPE,and are important guidance for the design and technological innovation of advanced equipment based on the future technological battlefield.展开更多
Wearable technology,which can continuously and remotely monitor physiological and behavioral parameters by incorporated into clothing or worn as an accessory,introduces a new era for ubiquitous health care.With big da...Wearable technology,which can continuously and remotely monitor physiological and behavioral parameters by incorporated into clothing or worn as an accessory,introduces a new era for ubiquitous health care.With big data technology,wearable data can be analyzed to help long-term cardiovascular care.This review summarizes the recent developments of wearable technology related to cardiovascular care,highlighting the most common wearable devices and their accuracy.We also examined the application of these devices in cardiovascular healthcare,such as the early detection of arrhythmias,measuring blood pressure,and detecting prevalent diabetes.We provide an overview of the challenges that hinder the widespread application of wearable devices,such as inadequate device accuracy,data redundancy,concerns associated with data security,and lack of meaningful criteria,and offer potential solutions.Finally,the future research direction for cardiovascular care using wearable devices is discussed.展开更多
Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of patients.WBASN under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can commun...Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of patients.WBASN under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can communicate with each other without human involvement.These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs.The BSNs generate critical data as it is related to patient’s health.The data traffic can be classified as Sensitive Data(SD)and Non-sensitive Data(ND)packets based on the value of vital signs.These data packets have different priority to deliver.The ND packets may tolerate some delay or packet loss whereas,the SD packets required to be delivered on time with minimized packet loss otherwise it can be life threating to the patients.In this research,we propose a Traffic Priority-aware Medical Data Dissemination(TPMD2)scheme forWBASN to deliver the data packets according to their priority based on the sensitivity of the data.The assessment of the proposed scheme is carried out in various experiments.The simulation results of the TPMD2 scheme indicate a significant improvement in packets delivery,transmission delay and energy efficiency in comparison with the existing schemes.展开更多
基金supported by the National Natural Science Foundation of China(No.81974355 and No.82172525)the National Intelligence Medical Clinical Research Center(No.2020021105012440)the Hubei Province Technology Innovation Major Special Project(No.2018AAA067).
文摘Chronic diseases are a growing concern worldwide,with nearly 25% of adults suffering from one or more chronic health conditions,thus placing a heavy burden on individuals,families,and healthcare systems.With the advent of the“Smart Healthcare”era,a series of cutting-edge technologies has brought new experiences to the management of chronic diseases.Among them,smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state.However,how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management,in terms of quality of life,patient outcomes,and privacy protection,is an urgent issue that needs to be addressed.Artificial intelligence(AI)can provide intelligent suggestions by analyzing a patient’s physiological data from wearable devices for the diagnosis and treatment of diseases.In addition,blockchain can improve healthcare services by authorizing decentralized data sharing,protecting the privacy of users,providing data empowerment,and ensuring the reliability of data management.Integrating AI,blockchain,and wearable technology could optimize the existing chronic disease management models,with a shift from a hospital-centered model to a patient-centered one.In this paper,we conceptually demonstrate a patient-centric technical framework based on AI,blockchain,and wearable technology and further explore the application of these integrated technologies in chronic disease management.Finally,the shortcomings of this new paradigm and future research directions are also discussed.
文摘The field of gastroenterology has recently seen a surge in wearable technology to monitor physical activity,sleep quality,pain,and even gut activity.The past decade has seen the emergence of wearable devices including Fitbit,Apple Watch,AbStats,and ingestible sensors.In this review,we discuss current and future devices designed to measure sweat biomarkers,steps taken,sleep efficiency,gastric electrical activity,stomach pH,and intestinal contents.We also summarize several clinical studies to better understand wearable devices so that we may assess their potential benefit in improving healthcare while also weighing the challenges that must be addressed.
文摘Wearable technology in the management of chronic diseases has emerged as a significant and growing concern in healthcare.These technologies,including smartwatches,fitness trackers,and other sensor-based devices,offer continuous monitoring and real-time data collection for individuals with chronic conditions.The data collected can include vital signs,activity levels,sleep patterns,and more,providing valuable insights into a patient's health.This trend is particularly relevant in the context of chronic diseases,such as diabetes,cardiovascular conditions,and respiratory disorders,where continuous monitoring is crucial for effective management.Wearable devices empower patients to actively participate in their healthcare by facilitating self-monitoring and promoting healthy behaviors.Healthcare providers can also leverage the data generated by these devices to make informed decisions,personalize treatment plans,and intervene proactively.However,challenges exist,such as data security and privacy concerns,the accuracy of the collected information,and the need for effective integration into existing healthcare systems.Despite these challenges,the increasing adoption of wearable technology in chronic disease management reflects a promising avenue for improving patient outcomes and reducing healthcare costs through preventive and personalized care.
基金funded in part by the German Research Foundation(Grant reference:496846758).
文摘The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activity, sedentary habits, sleep patterns) within the 24-h cycle of daily life. Wearables are applied in research, clinical practice, and as lifestyle devices;most obvious, they promise to be a key element for increasing human physical activity, one of the biggest health challenges nowadays.
基金funded by the Health Research Board in Ireland(Grant ID:HRB ILP-PHR-2024-005)Research Ireland(Grant ID:12/RC/2289_P2).
文摘Introduction:Consumer wearables increasingly provide users with Composite Health Scores(CHS)–integrated biometric indices that claim to quantify readiness,recovery,stress,or overall well-being.Despite their growing adoption,the validity,transparency,and physiological relevance of these scores remain unclear.This study systematically evaluates CHS fromleading wearablemanufacturers to assess their underlying methodologies,contributors,and scientific basis.Content:Information was synthesised from publicly available company documentation,including technical white papers,user manuals,app interfaces,and research literature where available.We identified 14 CHS across 10 major wearable manufacturers,including Fitbit(Daily Readiness),Garmin(Body Battery^(TM)and Training Readiness),Oura(Readiness and Resilience),WHOOP(Strain,Recovery,and Stress Monitor),Polar(Nightly Recharge^(TM)),Samsung(Energy Score),Suunto(Body Resources),Ultrahuman(Dynamic Recovery),Coros(Daily Stress),and Withings(Health Improvement Score).The most frequently incorporated biometric contributors in this catalogue of CHS were heart rate variability(86%),resting heart rate(79%),physical activity(71%),and sleep duration(71%).However,significant discrepancies were identified in data collection timeframes,metric weighting,and proprietary scoring methodologies.None of the manufacturers disclosed their exact algorithmic formulas,and few provided empirical validation or peer-reviewed evidence supporting the accuracy or clinical relevance of their scores.Summary and outlook:While the concept of CHS represent a promising innovation in digital health,their scientific validity,transparency,and clinical applicability remain uncertain.Future research should focus on establishing standardized sensor fusion frameworks,improving algorithmic transparency,and evaluating CHS across diverse populations.Greater collaboration between industry,researchers,and clinicians is essential to ensure these indices serve as meaningful health metrics rather than opaque consumer tools.
基金by National Natural Science Foundation of China(No.62306083)the Postdoctoral Science Foundation of Heilongjiang Province of China(LBH-Z22175)the Ministry of Industry and Information Technology。
文摘Adolescent idiopathic scoliosis(AIS)is a dynamic progression during growth,which requires long-term collaborations and efforts from clinicians,patients and their families.It would be beneficial to have a precise intervention based on cross-scale understandings of the etiology,real-time sensing and actuating to enable early detection,screening and personalized treatment.We argue that merging computational intelligence and wearable technologies can bridge the gap between the current trajectory of the techniques applied to AIS and this vision.Wearable technologies such as inertial measurement units(IMUs)and surface electromyography(sEMG)have shown great potential in monitoring spinal curvature and muscle activity in real-time.For instance,IMUs can track the kinematics of the spine during daily activities,while sEMG can detect asymmetric muscle activation patterns that may contribute to scoliosis progression.Computational intelligence,particularly deep learning algorithms,can process these multi-modal data streams to identify early signs of scoliosis and adapt treatment strategies dynamically.By using their combination,we can find potential solutions for a better understanding of the disease,a more effective and intelligent way for treatment and rehabilitation.
基金funded by a grant from Qiangnao Keji(BrainCo)Ltd.
文摘Objective:Behavioral interventions have been shown to ameliorate the electroencephalogram(EEG)dynamics underlying the behavioral symptoms of autism spectrum disorder(ASD),while studies have also demonstrated that mirror neuron mu rhythm-based EEG neurofeedback training improves the behavioral functioning of individuals with ASD.This study aimed to test the effects of a wearable mu rhythm neurofeedback training system based on machine learning algorithms for children with autism.Methods:A randomized,placebo-controlled study was carried out on 60 participants aged 3 to 6 years who were diagnosed with autism,at two center-based intervention sites.The neurofeedback group received active mu rhythm neurofeedback training,while the control group received a sham neurofeedback training.Other behavioral intervention programs were similar between the two groups.Results:After 60 sessions of treatment,both groups showed significant improvements in several domains including language,social and problem behavior.The neurofeedback group showed significantly greater improvements in expressive language(P=0.013)and cognitive awareness(including joint attention,P=0.003)than did the placebo-controlled group.Conclusion:Artificial intelligence-powered wearable EEG neurofeedback,as a type of brain-computer interface application,is a promising assistive technology that can provide targeted intervention for the core brain mechanisms underlying ASD symptoms.
文摘Walkability is an essential aspect of urban transportation systems. Properly designed walking paths can enhance transportation safety, encourage pedestrian activity, and improve community quality of life. This, in turn, can help achieve sustainable development goals in urban areas. This pilot study uses wearable technology data to present a new method for measuring pedestrian stress in urban environments and the results were presented as an interactive geographic information system map to support risk-informed decision-making. The approach involves analyzing data from wearable devices using heart rate variability (RMSSD and slope analysis) to identify high-stress locations. This data-driven approach can help urban planners and safety experts identify and address pedestrian stressors, ultimately creating safer, more walkable cities. The study addresses a significant challenge in pedestrian safety by providing insights into factors and locations that trigger stress in pedestrians. During the pilot study, high-stress pedestrian experiences were identified due to issues like pedestrian-scooter interaction on pedestrian paths, pedestrian behavior around high foot traffic areas, and poor visibility at pedestrian crossings due to inadequate lighting.
文摘The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.
文摘The integration of digital technologies into oral health care is transforming the field, driving advancements in diagnostic precision, patient engagement, and access to care. This review evaluates the impact of mobile health (mHealth) applications, tele-dentistry, artificial intelligence (AI), wearable devices, and advanced imaging systems on modern dentistry. Synthesizing findings from 125 studies published between 2010 and 2024, the paper identifies key achievements, including improved patient compliance, enhanced diagnostic capabilities, and expanded access to care in underserved areas. Tele-dentistry has been pivotal in bridging geographical gaps, particularly during the COVID-19 pandemic, while AI tools have revolutionized diagnostics and personalized treatment planning. Wearable devices and mHealth applications have empowered patients with real-time feedback, fostering sustained adherence to oral hygiene practices. The review also highlights the potential of digital tools to reduce healthcare disparities and operational costs, paving the way for more equitable and efficient dental care. By outlining critical advancements and future directions, this paper underscores the transformative potential of digital health technologies in dentistry. It advocates for further research on data security, interoperability, and innovative applications of AI to maximize the benefits of these tools, ultimately shaping a more accessible and patient-focused oral health ecosystem.
文摘As the population across the globe continues to dramatically increase,the prevalence of cognitive impairment and dementia will inevitably increase as well,placing increasing burden on families and health care systems.Technological advancements over the past decade provide potential benefit in not only relieving caregiver burden of caring for a loved one with dementia,but also enables individuals with dementia to age in place.Technological devices have served to improve functioning,tracking and mobility.Similarly,smartphones,tablets and the ubiquitous world wide web have facilitated the dissemination of health information to previously hard to reach populations largely through use of various social media platforms.In this review,we discuss the current and future uses of technology via devices and social media to promote healthy aging in individuals with dementia,and also limitations and challenges to consider in the future.
文摘Wearable technologies have the potential to become a valuable influence on human daily life where they may enable observing the world in new ways,including,for example,using augmented reality(AR)applications.Wearable technology uses electronic devices that may be carried as accessories,clothes,or even embedded in the user's body.Although the potential benefits of smart wearables are numerous,their extensive and continual usage creates several privacy concerns and tricky information security challenges.In this paper,we present a comprehensive survey of recent privacy-preserving big data analytics applications based on wearable sensors.We highlight the fundamental features of security and privacy for wearable device applications.Then,we examine the utilization of deep learning algorithms with cryptography and determine their usability for wearable sensors.We also present a case study on privacy-preserving machine learning techniques.Herein,we theoretically and empirically evaluate the privacy-preserving deep learning framework's performance.We explain the implementation details of a case study of a secure prediction service using the convolutional neural network(CNN)model and the Cheon-Kim-Kim-Song(CHKS)homomorphic encryption algorithm.Finally,we explore the obstacles and gaps in the deployment of practical real-world applications.Following a comprehensive overview,we identify the most important obstacles that must be overcome and discuss some interesting future research directions.
基金sponsored by a grant from the Tonkin son Colorectal Cancer Research Fund(#57838)the Ministry of Education,Culture and Sports of Spain for the financing of the Jose Castillejo scholarship(CAS19/00043)to MLR。
文摘Background:Physical activity(PA)is important for cancer survivors.Trials of remotely delivered interventions are needed to assist in reaching under-served non-metropolitan cancer survivors.The objective of this study was to ascertain whether wearable technology,coupled with health coaching was effective in increasing PA in breast and colorectal cancer survivors living in regional and remote areas in Australia.Methods:Cancer survivors from 5 states were randomized to intervention and control arms.Intervention participants were given a Fitbit Charge 2TMand received up to 6 telephone health coaching sessions.Control participants received PA print materials.Accelerometer assessments at baseline and 12 weeks measured moderate-to-vigorous PA(MVPA),light PA,and sedentary behavior.Results:Eighty-seven participants were recruited(age=63±11 years;74(85%)female).There was a significant net improvement in MVPA of 49.8 min/week,favoring the intervention group(95%confidence interval(95%CI):13.6-86.1,p=0.007).There was also a net increase in MVPA bouts of 39.5 min/week(95%CI:11.9-67.1,p=0.005),favoring the intervention group.Both groups improved light PA and sedentary behavior,but there were no between-group differences.Conclusion:This’s the first study to demonstrate that,when compared to standard practice(i.e.,PA education),a wearable technology intervention coupled with distance-based health coaching,improves MVPA in non-metropolitan cancer survivors.The results display promise for the use of scalable interventions using smart wearable technology in conjunction with phone-based health coaching to foster increased PA in geographically disadvantaged cancer survivors.
基金supported by the National Natural Science Foundation of China(52125201)China Postdoctoral Science Foundation(2024M751716)+1 种基金the Postdoctoral Fellowship Program of CPSF(GZB20230328)the Shuimu Tsinghua Scholar Program.
文摘Wearable technology has revolutionized personalized healthcare and human–machine interfaces[1,2].While conventional devices,such as watches,rings,and chest straps,demonstrate utility in localized physiological monitoring,they exhibit inherent limitations in mechanical compliance and ergonomic adaptability.These systems fundamentally lack the capability to capture the body’s spatially distributed,multimodal biosignals(biopotential,optical,thermal,and mechanical)with precision due to their single-node measurement paradigm.
基金supported by the City University of Hong Kong and funded by the Research Grants Council(RGC)partly supported by the InnoHK Project on Project 1.2-Novel Drug Delivery Systems to Achieve Precision Medicine for Acute CVD Patients(a closed-loop CVD control system)at the Hong Kong Center for Cerebrocardiovascular Health Engineering(COCHE).City University of Hong Kong(9610430,7006082,9678292,7020073,9609332,9609333),funded by the Research Grants Council(RGC)+2 种基金Innovation and Technology Commission(ITC)(9667220)-Research Talent Hub(RTH)1-5University Grant Committee(UGC)Innovation and Technology Fund(ITF).
文摘Cardiovascular diseases remain a leading global cause of mortality,underscoring the urgent need for intelligent diagnostic tools to enhance early detection,prediction,diagnosis,prevention,treatment,and recovery.This demand has spurred the advancement of wearable and flexible technologies,revolutionizing continuous,noninvasive,and remote heart sound(HS)monitoring—a vital avenue for assessing heart activity.The conventional stethoscope,used to listen to HSs,has limitations in terms of its physical structure,as it is inflexible and bulky,which restricts its prospective applications.Recently,mechanoacoustic sensors have made remarkable advancements,evolving from primitive forms to soft,flexible,and wearable designs.This article provides an in-depth review of the latest scientific and technological advancements by addressing various topics,including different types of sensors,sensing materials,design principles,denoising techniques,and clinical applications of flexible and wearable HS sensors.This transformative potential lies in the capacity for ongoing,remote,and personalized monitoring,promising enhanced patient outcomes,amplified remote monitoring capabilities,and timely diagnoses.Last,the article highlights current challenges and prospects for the future,suggesting techniques to advance HS sensing technologies for exciting real‐time applications.
基金supported by the National Science Fund for Distinguished Young Scholars(no.31925028)the National Natural Science Foundation of China(nos.32171720 and 32371823).
文摘The conductive polymer poly-3,4-ethylenedioxythiophene(PEDOT),recognized for its superior electrical conductivity and biocompatibility,has become an attractive material for developing wearable technologies and bioelectronics.Nevertheless,the complexities associated with PEDOT's patterning synthesis on diverse substrates persist despite recent technological progress.In this study,we introduce a novel deep eutectic solvent(DES)-induced vapor phase polymerization technique,facilitating nonrestrictive patterning polymerization of PEDOT across diverse substrates.By controlling the quantity of DES adsorbed per unit area on the substrates,PEDOT can be effectively patternized on cellulose,wood,plastic,glass,and even hydrogels.The resultant patterned PEDOT exhibits numerous benefits,such as an impressive electronic conductivity of 282 S·m-1,a high specific surface area of 5.29 m^(2)·g-1,and an extensive electrochemical stability range from-1.4 to 2.4 V in a phosphate-buffered saline.To underscore the practicality and diverse applications of this DES-induced approach,we present multiple examples emphasizing its integration into self-supporting flexible electrodes,neuroelectrode interfaces,and precision circuit repair methodologies.
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 National Outstanding Youth Science Fund Project of National Natural Science Foundation of China(Projects No.52202012)the National Natural Science Foundation of China(Projects No.51834007)。
文摘With the development of ordnance technology,the survival and safety of individual combatants in hightech warfare are under serious threat,and the Personal Protective Equipment(PPE),as an important guarantee to reduce casualties and maintain military combat effectiveness,is widely developed.This paper systematically reviewed various PPE based on individual combat through literature research and comprehensive discussion,and introduced in detail the latest application progress of PPE in terms of material and technology from three aspects:individual integrated protection system,traditional protection equipment,and intelligent protection equipment,respectively,and discussed in depth the functional improvement and optimization status brought by advanced technology for PPE,focusing on the achievements of individual equipment technology application.Finally,the problems and technical bottlenecks in the development of PPE were analyzed and summarized,and the development trend of PPE were pointed out.The results of the review will provide a forward-looking reference for the current development of individual PPE,and are important guidance for the design and technological innovation of advanced equipment based on the future technological battlefield.
基金National Natural Science Foundation of China(No.U1913210)in part by the Strategic Priority CAS Project(XDB38040200)in part by the Basic Research Project of Shenzhen(JCYJ20210324101206017)
文摘Wearable technology,which can continuously and remotely monitor physiological and behavioral parameters by incorporated into clothing or worn as an accessory,introduces a new era for ubiquitous health care.With big data technology,wearable data can be analyzed to help long-term cardiovascular care.This review summarizes the recent developments of wearable technology related to cardiovascular care,highlighting the most common wearable devices and their accuracy.We also examined the application of these devices in cardiovascular healthcare,such as the early detection of arrhythmias,measuring blood pressure,and detecting prevalent diabetes.We provide an overview of the challenges that hinder the widespread application of wearable devices,such as inadequate device accuracy,data redundancy,concerns associated with data security,and lack of meaningful criteria,and offer potential solutions.Finally,the future research direction for cardiovascular care using wearable devices is discussed.
基金This work was supported in part by Universiti TeknologiMalaysia(UTM)in the project under Institutional grant vote 08G49 and FRGS vote 5F349.
文摘Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of patients.WBASN under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can communicate with each other without human involvement.These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs.The BSNs generate critical data as it is related to patient’s health.The data traffic can be classified as Sensitive Data(SD)and Non-sensitive Data(ND)packets based on the value of vital signs.These data packets have different priority to deliver.The ND packets may tolerate some delay or packet loss whereas,the SD packets required to be delivered on time with minimized packet loss otherwise it can be life threating to the patients.In this research,we propose a Traffic Priority-aware Medical Data Dissemination(TPMD2)scheme forWBASN to deliver the data packets according to their priority based on the sensitivity of the data.The assessment of the proposed scheme is carried out in various experiments.The simulation results of the TPMD2 scheme indicate a significant improvement in packets delivery,transmission delay and energy efficiency in comparison with the existing schemes.
