The stretchable and curved electronics have recently attracted tremendous attention due to their unique advantages and broad application scenarios. Stretchable conductors are the most important units and determine the performance of the whole device. This article focuses on the development of a novel vertical serpentine conductor (VSC) with a high aspect ratio through MEMS-based fabrication technology for stretchable and curved electronics with superior performance. A comprehensive study of various designs for the vertical serpentine structure was conducted to provide a critical basis for subsequent structural design and fabrication. Next, a series of VSCs of different designs were manufactured for comparative experiments, which also confirmed the feasibility of constructing vertical serpentine structures via MEMS-based technology. After that, the mechanical properties of the VSC were investigated experimentally. The VSC with a radius of $30~mu $ m can be stretched up to 4000% while maintaining structural integrity and electrical performance. Excellent stability can also be obtained, where the electrical properties of VSC were strain insensitive during deformation. In addition, the superior durability of the VSC was verified after 20 000 cycles of stretching and releasing at 3000% applied strain, where the relative resistance only changed within 5%.
{"title":"Highly Stretchable Strain-Insensitive Vertical Serpentine Conductors for Flexible Electronics","authors":"Rui Jiao;Ruoqin Wang;Qian Xu;Shuo Mao;Xiaohan Wang;Mingliang Chen;Jiaqiang Huang;Zebin Chen;Longqian Zhu;Hongyu Yu","doi":"10.1109/JSEN.2025.3545952","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3545952","url":null,"abstract":"The stretchable and curved electronics have recently attracted tremendous attention due to their unique advantages and broad application scenarios. Stretchable conductors are the most important units and determine the performance of the whole device. This article focuses on the development of a novel vertical serpentine conductor (VSC) with a high aspect ratio through MEMS-based fabrication technology for stretchable and curved electronics with superior performance. A comprehensive study of various designs for the vertical serpentine structure was conducted to provide a critical basis for subsequent structural design and fabrication. Next, a series of VSCs of different designs were manufactured for comparative experiments, which also confirmed the feasibility of constructing vertical serpentine structures via MEMS-based technology. After that, the mechanical properties of the VSC were investigated experimentally. The VSC with a radius of <inline-formula> <tex-math>$30~mu $ </tex-math></inline-formula>m can be stretched up to 4000% while maintaining structural integrity and electrical performance. Excellent stability can also be obtained, where the electrical properties of VSC were strain insensitive during deformation. In addition, the superior durability of the VSC was verified after 20 000 cycles of stretching and releasing at 3000% applied strain, where the relative resistance only changed within 5%.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13810-13818"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-05DOI: 10.1109/JSEN.2024.3524872
Xin Sui;Bangwen Liao;Changqiang Wang;Zhengxu Shi
Presents corrections to the paper, (Corrections to “Improved XGBoost and GM UWB/MEME IMU Positioning Methods for Non-Line-of-Sight Environments”).
{"title":"Corrections to “Improved XGBoost and GM UWB/MEME IMU Positioning Methods for Non-Line-of-Sight Environments”","authors":"Xin Sui;Bangwen Liao;Changqiang Wang;Zhengxu Shi","doi":"10.1109/JSEN.2024.3524872","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3524872","url":null,"abstract":"Presents corrections to the paper, (Corrections to “Improved XGBoost and GM UWB/MEME IMU Positioning Methods for Non-Line-of-Sight Environments”).","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"9208-9208"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10912815","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-05DOI: 10.1109/JSEN.2025.3546277
Mohamad Eshghi;Abolfazl Bijari
This article presents an angular displacement sensor utilizing a double-ring resonator (DRR) and introduces an integrable and low-cost readout circuit to detect the transmission zero (TZ) position in the sensor’s frequency response. The proposed sensor comprises a DRR-based stator and an open-ended stub rotor. The interaction between the rotor and stator via ohmic contact causes a notable change in the effective electrical length of the stator, leading to a measurable shift in the position of the TZ. The theoretical analysis of the sensor is conducted using ABCD matrices, ensuring accurate modeling and characterization. A novel readout circuit is implemented by a frequency synthesizer and a power detector. The proposed circuit effectively detects notches or peaks in the frequency response of the device under test (DUT) by applying a precisely controlled sinusoidal signal and measuring the output power. This enables reliable detection over a wide frequency range of 35 MHz–4.4 GHz. The proposed readout circuit supports real-time measurements for resonant-based sensors in industrial applications, eliminating the need for expensive laboratory equipment. The experimental results show good agreement between the measurements from the readout circuit and those from a vector network analyzer (VNA), confirming the reliability and accuracy of the proposed method.
{"title":"Angular Displacement Sensor Based on Double-Ring Resonator With a Novel Readout Circuit","authors":"Mohamad Eshghi;Abolfazl Bijari","doi":"10.1109/JSEN.2025.3546277","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3546277","url":null,"abstract":"This article presents an angular displacement sensor utilizing a double-ring resonator (DRR) and introduces an integrable and low-cost readout circuit to detect the transmission zero (TZ) position in the sensor’s frequency response. The proposed sensor comprises a DRR-based stator and an open-ended stub rotor. The interaction between the rotor and stator via ohmic contact causes a notable change in the effective electrical length of the stator, leading to a measurable shift in the position of the TZ. The theoretical analysis of the sensor is conducted using ABCD matrices, ensuring accurate modeling and characterization. A novel readout circuit is implemented by a frequency synthesizer and a power detector. The proposed circuit effectively detects notches or peaks in the frequency response of the device under test (DUT) by applying a precisely controlled sinusoidal signal and measuring the output power. This enables reliable detection over a wide frequency range of 35 MHz–4.4 GHz. The proposed readout circuit supports real-time measurements for resonant-based sensors in industrial applications, eliminating the need for expensive laboratory equipment. The experimental results show good agreement between the measurements from the readout circuit and those from a vector network analyzer (VNA), confirming the reliability and accuracy of the proposed method.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13210-13218"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vital signs, such as respiratory rate (RR) and heart rate (HR), are essential indicators for assessing human health. Radar enables noncontact detection of RR and HR. However, chest displacement caused by heartbeats is much smaller than that caused by respiration. And the weak heartbeat signal is susceptible to being overwhelmed by respiratory harmonics and noise, making HR detection challenging. To address these issues, we propose a novel vital sign decomposition method. Phase difference and Hampel filter are used to suppress unknown noise, and discrete wavelet transform (DWT) is used to separate respiratory signal. To achieve more accurate estimation of heartbeat signal frequency, we introduce the singular value decomposition (SVD)-focal underdetermined system solver (FOCUSS)-recovery (SFR) method following successive variational mode decomposition (SVMD). This method possesses feature extraction and sparsity optimization capabilities, thereby improving spectral resolution and the estimation of heartbeat signal frequency. Experimental results demonstrate that the root mean square error (RMSE) between ECG sensor measurements and proposed method is below 1 beat per minute (bpm) for RR and below 2 bpm for HR.
{"title":"A Novel Approach to Accurate Respiratory Rate and Heart Rate Estimation via FMCW Radar","authors":"Denghao Li;Yukun Huang;Huaqing Li;Jingran Cheng;Wenwen Zhu;Haoming Feng","doi":"10.1109/JSEN.2025.3542776","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3542776","url":null,"abstract":"Vital signs, such as respiratory rate (RR) and heart rate (HR), are essential indicators for assessing human health. Radar enables noncontact detection of RR and HR. However, chest displacement caused by heartbeats is much smaller than that caused by respiration. And the weak heartbeat signal is susceptible to being overwhelmed by respiratory harmonics and noise, making HR detection challenging. To address these issues, we propose a novel vital sign decomposition method. Phase difference and Hampel filter are used to suppress unknown noise, and discrete wavelet transform (DWT) is used to separate respiratory signal. To achieve more accurate estimation of heartbeat signal frequency, we introduce the singular value decomposition (SVD)-focal underdetermined system solver (FOCUSS)-recovery (SFR) method following successive variational mode decomposition (SVMD). This method possesses feature extraction and sparsity optimization capabilities, thereby improving spectral resolution and the estimation of heartbeat signal frequency. Experimental results demonstrate that the root mean square error (RMSE) between ECG sensor measurements and proposed method is below 1 beat per minute (bpm) for RR and below 2 bpm for HR.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13937-13945"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-05DOI: 10.1109/JSEN.2025.3546235
Bojun Zhang
With the rapid development of the retail industry, enhancing customer experience and operational efficiency has become increasingly critical, where technological integration is key. This study introduces an innovative framework for human behavior recognition that combines graph neural network (GNN) and radio frequency identification (RFID) technology. By embedding RFID signals into the graph structure, we effectively capture the spatial dependencies hidden in the data. Furthermore, the spline convolution technique is utilized to address the spatial dependencies of the signals, achieving accurate and robust human behavior recognition. Facing challenges such as dynamic changes in data dimensions in the retail environment, over-smoothing issues in GNNs, and the effective fusion of multidimensional features, we adopted a graph-based modeling approach. We constructed an adjacency matrix with small-world characteristics using the TopK mechanism and Pearson correlation coefficients, and introduced inception structures and residual connections to increase network width, thereby mitigating over-smoothing phenomena. The introduction of bidirectional long short-term memory network (BiLSTM) readout methods further enhanced the model’s ability to process time series information. Experimental results demonstrate the framework’s excellent performance in human behavior recognition tasks, with high accuracy and strong robustness, proving not only theoretically feasible but also highly effective in practical applications. Through qualitative analysis, we have improved the interpretability of the framework, providing retailers with a powerful tool for gaining in-depth insights into customer behavior, which helps to optimize customer experience and enhance operational efficiency.
{"title":"Human Behavior Recognition in Retail Environments With Graph-Driven RFID Signal Embedding","authors":"Bojun Zhang","doi":"10.1109/JSEN.2025.3546235","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3546235","url":null,"abstract":"With the rapid development of the retail industry, enhancing customer experience and operational efficiency has become increasingly critical, where technological integration is key. This study introduces an innovative framework for human behavior recognition that combines graph neural network (GNN) and radio frequency identification (RFID) technology. By embedding RFID signals into the graph structure, we effectively capture the spatial dependencies hidden in the data. Furthermore, the spline convolution technique is utilized to address the spatial dependencies of the signals, achieving accurate and robust human behavior recognition. Facing challenges such as dynamic changes in data dimensions in the retail environment, over-smoothing issues in GNNs, and the effective fusion of multidimensional features, we adopted a graph-based modeling approach. We constructed an adjacency matrix with small-world characteristics using the TopK mechanism and Pearson correlation coefficients, and introduced inception structures and residual connections to increase network width, thereby mitigating over-smoothing phenomena. The introduction of bidirectional long short-term memory network (BiLSTM) readout methods further enhanced the model’s ability to process time series information. Experimental results demonstrate the framework’s excellent performance in human behavior recognition tasks, with high accuracy and strong robustness, proving not only theoretically feasible but also highly effective in practical applications. Through qualitative analysis, we have improved the interpretability of the framework, providing retailers with a powerful tool for gaining in-depth insights into customer behavior, which helps to optimize customer experience and enhance operational efficiency.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13828-13839"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-05DOI: 10.1109/JSEN.2025.3545378
Daniel Gusland;Sigmund Rolfsjord;Jörgen Ahlberg
Multiple targets in the same radar micro-Doppler spectrogram, such as an uncrewed aerial vehicle (UAV) surrounded by flocking birds, can confuse classification algorithms. Without knowing which of the targets to classify, the decision is ambiguous. We propose to inform the classifier which targets to classify by encoding the detected target position as a separate channel. This instructs the convolutional neural network to pay attention to the selected target without removing context. We, therefore, enable the model to classify individual objects in multitarget spectrograms, paving the way for higher classification performance in complex environments. Different representations of the detection-guiding matrix are tested, and the approach is compared to alternative approaches, such as centering and cropping, and we show that it is superior in cases with multiple targets. The efficacy of the approach is demonstrated on synthetic multitarget spectrograms using multiple datasets.
{"title":"Detection-Guided Attention for Selective Target Classification Using Radar Micro-Doppler Spectrograms","authors":"Daniel Gusland;Sigmund Rolfsjord;Jörgen Ahlberg","doi":"10.1109/JSEN.2025.3545378","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3545378","url":null,"abstract":"Multiple targets in the same radar micro-Doppler spectrogram, such as an uncrewed aerial vehicle (UAV) surrounded by flocking birds, can confuse classification algorithms. Without knowing which of the targets to classify, the decision is ambiguous. We propose to inform the classifier which targets to classify by encoding the detected target position as a separate channel. This instructs the convolutional neural network to pay attention to the selected target without removing context. We, therefore, enable the model to classify individual objects in multitarget spectrograms, paving the way for higher classification performance in complex environments. Different representations of the detection-guiding matrix are tested, and the approach is compared to alternative approaches, such as centering and cropping, and we show that it is superior in cases with multiple targets. The efficacy of the approach is demonstrated on synthetic multitarget spectrograms using multiple datasets.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"14370-14378"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10913973","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-05DOI: 10.1109/JSEN.2025.3542385
Yuyang Sun;Panagiotis Kosmas
In this study, we present a noninvasive glucose prediction system that integrates near-infrared (NIR) spectroscopy and millimeter-wave (mm-wave) sensing. We employ a mixed linear model (MixedLM) to analyze the association between mm-wave frequency ${S}_{{21}}$ parameters and blood glucose levels within a heterogeneous dataset. The MixedLM method considers intersubject variability and integrates multiple predictors, offering a more comprehensive analysis than traditional correlation analysis. In addition, we incorporate a domain generalization (DG) model, meta-forests, to effectively handle domain variance in the dataset, enhancing the model’s adaptability to individual differences. Our results demonstrate promising accuracy in glucose prediction for unseen subjects, with a mean absolute error (MAE) of 17.47 mg/dL, a root mean square error (RMSE) of 31.83 mg/dL, and a mean absolute percentage error (MAPE) of 10.88%, highlighting its potential for clinical application. This study marks a significant step toward developing accurate, personalized, and noninvasive glucose monitoring systems, contributing to improved diabetes management.
{"title":"Noninvasive Glucose Prediction System Enhanced by Mixed Linear Models and Meta-Forests for Domain Generalization","authors":"Yuyang Sun;Panagiotis Kosmas","doi":"10.1109/JSEN.2025.3542385","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3542385","url":null,"abstract":"In this study, we present a noninvasive glucose prediction system that integrates near-infrared (NIR) spectroscopy and millimeter-wave (mm-wave) sensing. We employ a mixed linear model (MixedLM) to analyze the association between mm-wave frequency <inline-formula> <tex-math>${S}_{{21}}$ </tex-math></inline-formula> parameters and blood glucose levels within a heterogeneous dataset. The MixedLM method considers intersubject variability and integrates multiple predictors, offering a more comprehensive analysis than traditional correlation analysis. In addition, we incorporate a domain generalization (DG) model, meta-forests, to effectively handle domain variance in the dataset, enhancing the model’s adaptability to individual differences. Our results demonstrate promising accuracy in glucose prediction for unseen subjects, with a mean absolute error (MAE) of 17.47 mg/dL, a root mean square error (RMSE) of 31.83 mg/dL, and a mean absolute percentage error (MAPE) of 10.88%, highlighting its potential for clinical application. This study marks a significant step toward developing accurate, personalized, and noninvasive glucose monitoring systems, contributing to improved diabetes management.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"14209-14219"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite metamaterial-based absorbers enabling flexibly manipulating electromagnetic waves, achieving highly anisotropic and tunable absorption still remains a challenge. The discovery of $alpha $ -phase molybdenum trioxide ($alpha $ -MoO3), a 2-D van der Waals material with strong crystal anisotropy, has aroused significant interest in developing exotic polarization-dependent optoelectronic devices. However, effectively leveraging its anisotropic properties for perfect absorption requires careful structural design and optimization. In this work, we theoretically propose an anisotropic metamaterial perfect absorber (MPA) consisting of a square array of $alpha $ -MoO3 nanostructures. The meta-atom composed of an $alpha $ -MoO3 ring intersected by a central cross deploying on a gold mirror is designed to realize narrowband perfect absorption for polarization along both [100] and [001] crystalline directions in the visible to the near-infrared region. Our analysis shows that the perfect absorption results from the interactions of the strongly localized electromagnetic field confinement induced by the $alpha $ -MoO3’s crystal anisotropy, the magnetic dipole mode, and the Rayleigh anomalies (RAs) of the meta-atoms. Investigation of varying geometric parameters of the MPA demonstrates that the narrow perfect absorption bands can be precisely tunable. Moreover, the MPA exhibits a high bulk sensitivity of 593.88 nm RIU$^{-{1}}$ and a figure of merit of 19.94 RIU$^{-{1}}$ , which indicates strong potential for bulk sensing applications. Surface sensing characterization reveals that the surface sensitivity of the MPA is different over different absorbate layer thickness ranges under both y- and x-polarized excitations, highlighting the complexity of designing efficient biosensing platforms. These findings not only point out the challenges and opportunities for developing $alpha $ -MoO3-based MPAs but also suggest great potential applications in integrated bulk sensing and biosensing technologies.
{"title":"Selectable Narrowband Anisotropic Perfect Absorbers Based on α-MoO₃ Metamaterials for Refractive Index Sensing","authors":"Weijia Han;Yilin Zuo;Wei Zhu;Guochao Wei;Kang Du;Bohan Zhang;Xiaoman Xiong;Tingting Wang;Cai Zhou;Yan Liu;Shengxiang Wang","doi":"10.1109/JSEN.2025.3546488","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3546488","url":null,"abstract":"Despite metamaterial-based absorbers enabling flexibly manipulating electromagnetic waves, achieving highly anisotropic and tunable absorption still remains a challenge. The discovery of <inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>-phase molybdenum trioxide (<inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>-MoO3), a 2-D van der Waals material with strong crystal anisotropy, has aroused significant interest in developing exotic polarization-dependent optoelectronic devices. However, effectively leveraging its anisotropic properties for perfect absorption requires careful structural design and optimization. In this work, we theoretically propose an anisotropic metamaterial perfect absorber (MPA) consisting of a square array of <inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>-MoO3 nanostructures. The meta-atom composed of an <inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>-MoO3 ring intersected by a central cross deploying on a gold mirror is designed to realize narrowband perfect absorption for polarization along both [100] and [001] crystalline directions in the visible to the near-infrared region. Our analysis shows that the perfect absorption results from the interactions of the strongly localized electromagnetic field confinement induced by the <inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>-MoO3’s crystal anisotropy, the magnetic dipole mode, and the Rayleigh anomalies (RAs) of the meta-atoms. Investigation of varying geometric parameters of the MPA demonstrates that the narrow perfect absorption bands can be precisely tunable. Moreover, the MPA exhibits a high bulk sensitivity of 593.88 nm RIU<inline-formula> <tex-math>$^{-{1}}$ </tex-math></inline-formula> and a figure of merit of 19.94 RIU<inline-formula> <tex-math>$^{-{1}}$ </tex-math></inline-formula>, which indicates strong potential for bulk sensing applications. Surface sensing characterization reveals that the surface sensitivity of the MPA is different over different absorbate layer thickness ranges under both y- and x-polarized excitations, highlighting the complexity of designing efficient biosensing platforms. These findings not only point out the challenges and opportunities for developing <inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>-MoO3-based MPAs but also suggest great potential applications in integrated bulk sensing and biosensing technologies.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13149-13159"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-05DOI: 10.1109/JSEN.2025.3537212
Michele Magno;Daniela de Venuto;Giuseppe Ferri;Seonyeong Heo
{"title":"Guest Editorial Special Issue on Energy-Efficient Embedded Intelligent Sensor Systems (S1)","authors":"Michele Magno;Daniela de Venuto;Giuseppe Ferri;Seonyeong Heo","doi":"10.1109/JSEN.2025.3537212","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3537212","url":null,"abstract":"","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"7733-7733"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10912814","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-05DOI: 10.1109/JSEN.2025.3546431
Mohammed A. Alsultan;S. López-Soriano;Joan Melià-Seguí
Continuous monitoring of body fluids is essential to maintain health and prevent critical issues such as dehydration, especially among those engaged in physical activities, living in harsh environments such as warm climates, or belonging to vulnerable populations. Traditional hydration monitoring solutions often involved complex measurements, required body-worn devices, or relied on batteries, making them impractical for widespread use among the general population. However, the development of low-cost, noninvasive hydration monitoring technology that can be integrated into textiles, together with the generalization of the digital product passport (DPP), could play a crucial role in democratizing and enhancing eHealth. Building upon previous studies, this work delves into the use of ultrahigh-frequency (UHF) radio frequency identification (RFID) antennas as hydration sensors on various fabrics and frequency bands. After dielectric characterization of different fabrics when mixed with synthetic euhydrated and dehydrated sweat, we developed and evaluated different prototypes compatible with different fabrics, achieving a read range four times larger compared with previous works. In a controlled laboratory environment, we achieved 100% accuracy classifying between euhydrated and dehydrated sweat in fabrics with liquid concentrations greater than 50%. Furthermore, the improved classification method ensures compatibility with both the Federal Communications Commission (FCC) and European Telecommunications Standards Institute (ETSI) bands.
{"title":"Multitextile and Multiband UHF RFID Antenna-Based Sensor for Noninvasive eHealth Hydration Monitoring","authors":"Mohammed A. Alsultan;S. López-Soriano;Joan Melià-Seguí","doi":"10.1109/JSEN.2025.3546431","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3546431","url":null,"abstract":"Continuous monitoring of body fluids is essential to maintain health and prevent critical issues such as dehydration, especially among those engaged in physical activities, living in harsh environments such as warm climates, or belonging to vulnerable populations. Traditional hydration monitoring solutions often involved complex measurements, required body-worn devices, or relied on batteries, making them impractical for widespread use among the general population. However, the development of low-cost, noninvasive hydration monitoring technology that can be integrated into textiles, together with the generalization of the digital product passport (DPP), could play a crucial role in democratizing and enhancing eHealth. Building upon previous studies, this work delves into the use of ultrahigh-frequency (UHF) radio frequency identification (RFID) antennas as hydration sensors on various fabrics and frequency bands. After dielectric characterization of different fabrics when mixed with synthetic euhydrated and dehydrated sweat, we developed and evaluated different prototypes compatible with different fabrics, achieving a read range four times larger compared with previous works. In a controlled laboratory environment, we achieved 100% accuracy classifying between euhydrated and dehydrated sweat in fabrics with liquid concentrations greater than 50%. Furthermore, the improved classification method ensures compatibility with both the Federal Communications Commission (FCC) and European Telecommunications Standards Institute (ETSI) bands.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 8","pages":"13974-13985"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10914505","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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