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{"title":"A Multilayer Interdigitated Spiral Structure to Achieve Inductive Force and Capacitive Proximity Dual-Sensing","authors":"Fuchi Shih;Mei-Feng Lai;Weileun Fang","doi":"10.1109/JSEN.2025.3583062","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3583062","url":null,"abstract":"This study presents a tactile sensor featuring interdigitated spiral structure. Using different electrical routings, the interdigitated spiral structure achieves both inductive force and capacitive proximity dual-sensing capabilities on the same chip. The sensing device is implemented using the Taiwan Semiconductor Manufacturing Company (TSMC) 0.18-<inline-formula> <tex-math>$mu $ </tex-math></inline-formula> m 1P6M standard complementary metal-oxide–semiconductor (CMOS) process, along with in-house post-CMOS processes. Key features of the tactile sensor include: 1) force sensing mode (two-end signal input): acting as a magnetic coil to provide magnetic flux and 2) proximity sensing mode (single-end signal input): acting as interdigitated electrodes to generate fringe electric field. Leveraging the advantages of the CMOS platform, this study presents a multilayer interdigitated spiral structure to enhance the performance of the sensors. Measurements indicate that the device has a sensitivity of 5.1 nH/N under a 0–1-N load with one magnetic-coil sensing unit in the inductive force sensing mode, and a sensitivity of 0.54 fF/mm over a 0–3-mm distance range with a single-layer interdigitated electrode in the capacitive proximity sensing mode. Moreover, increasing the magnetic-coil sensing units from one to eight results in a nearly 64-fold enhancement in the sensitivity of force sensing. The proximity sensing can also be improved by increasing the stacked layers in interdigitated electrodes; however, this may result in a relatively unstable sensing signal, leading to larger error bars, which is a concern for applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28164-28173"},"PeriodicalIF":4.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758353","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}

{"title":"Efficient Computation of Laser Self-Mixing Sensor Signal Under Variable Optical Feedback","authors":"Syed Muhammad Muslim;Olivier D. Bernal;Usman Zabit","doi":"10.1109/JSEN.2025.3581469","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581469","url":null,"abstract":"Optical feedback-based laser self-mixing interferometry (SMI) has been used with success for a variety of sensing and measurement applications. Mathematical models exist that describe SMI signals with high accuracy, both for constant optical feedback conditions or for the more realistic variable optical feedback (VOF) conditions. However, the current VOF-based SMI model is computationally very intensive, which makes it difficult to use such a model in resource-limited hardware/environment for real-time embedded applications. In this article, three variants of the VOF-based SMI model are presented that are computationally much simpler, having a time of execution four, ten, and 23 times faster than the previous VOF model. Modeling of experimentally acquired speckle-affected laser sensor signals is also successfully achieved.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28299-28307"},"PeriodicalIF":4.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758354","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}

{"title":"Deep Learning Based Inverse Design of Nanoscale Optical Bandpass Filter for Sub-THz 6G Network","authors":"P. Agilandeswari;G. Thavasi Raja;R. Rajasekar","doi":"10.1109/TNANO.2025.3584854","DOIUrl":"https://doi.org/10.1109/TNANO.2025.3584854","url":null,"abstract":"In this paper, the novel deep learning-based nano scale optical filter is designed with narrow bandwidth for 6G network and Dense Wavelength Division Multiplexing (DWDM) systems. The hybrid Long Short-Term Memory Neural Network (LSTM-NN)-transformer based deep learning algorithm is implemented to accurately predict the structural parameter of the optical bandpass filter. The inverse design approach-based hybrid deep learning model is designed to improve the performance of the optical bandpass filter. The photonic filter performance parameters are numerically analyzed by Finite Difference Time Domain (FDTD) method. The proposed hybrid model is designed with very low mean square error of 5.4207 × 10⁻⁸ and less computation time of 834.81 seconds. The presented photonics platform is designed with narrow bandwidth of 1.12 THz and footprint is very compact as about 134 μm². Therefore, the proposed optical filter is highly suitable for photonic integrated circuits and lightwave communication systems.","PeriodicalId":449,"journal":{"name":"IEEE Transactions on Nanotechnology","volume":"24 ","pages":"347-355"},"PeriodicalIF":2.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing 3-D Sound Event Localization and Detection With Distance Estimation Using Reverberation and Spatial Coherence Features","authors":"Jun-Wei Yeow;Ee-Leng Tan;Jisheng Bai;Santi Peksi;Woon-Seng Gan","doi":"10.1109/JSEN.2025.3583033","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3583033","url":null,"abstract":"Sound event localization, detection, and distance estimation [3-D sound event localization and detection (SELD)] is pivotal for applications such as acoustic monitoring, surveillance, and robotic navigation. Despite significant advances in SELD, achieving accurate sound distance estimation (SDE) remains challenging due to complex real-world reverberation and the limited efficacy of existing methods. To address these challenges, we propose the coherence and direct-path dominance (CDPD) feature, specifically designed to overcome current limitations in SDE accuracy. By explicitly integrating complementary spatial coherence and reverberation cues into conventional SELD features, the CDPD feature captures robust distance-related information even under challenging reverberant conditions. The experimental results on the Sony-TAu Realistic Spatial Soundscapes 2023 (STARSS23) dataset demonstrate that incorporating the CDPD feature significantly enhances overall 3-D SELD performance, reducing the class-dependent relative distance error by up to 6.07% and improving the location-dependent F-score by up to 8.90%. Comparative analyses on the Detection and Classification of Acoustic Scenes and Events (DCASE) Challenge 2024 Task 3 validation set further confirm that our approach attains competitive performance while requiring fewer training resources. These findings highlight the potential of leveraging CDPD cues to advance 3-D SELD in real-world reverberant environments.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29221-29237"},"PeriodicalIF":4.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750858","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}

{"title":"SFFR-Transformer: Spatial and Frequency Feature Recalibration Transformer for Incomplete Multimodal Medical Image Segmentation","authors":"Jia Lin;Xinlong Liu;Like Li;Kesheng Zhang;Xiaopeng Sha;Ting Feng;Xiang Li","doi":"10.1109/JSEN.2025.3582902","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582902","url":null,"abstract":"Multimodal magnetic resonance imaging (MRI) is vital for the precise segmentation of brain tumors. However, missing or incomplete multimodal data is a frequent challenge in clinical practice, significantly affecting segmentation performance. Current advanced methods primarily focus on fusing multimodal images in the spatial domain, often neglecting the interplay between different modalities in the frequency domain. In this work, we propose a novel framework named spatial and frequency feature recalibration Transformer (SFFR-Transformer), which utilizes a frequency and spatial hybrid multihead attention (FSHMA) Transformer. This approach facilitates the complementary fusion of spatial- and frequency-domain information, enhancing the reconstruction of missing modalities. Moreover, most existing methods map fused modalities directly to all segmentation targets. Inspired by the correlation between single modalities and specific subtargets, we introduce a modality-subtarget matching module (MSTM). This module decouples the fusion modalities from the segmentation targets, enabling more accurate mapping between single modalities and their corresponding subtargets. Comprehensive experiments on the publicly available BraTS2018 and BraTS2020 datasets demonstrate that our framework surpasses state-of-the-art methods, particularly in scenarios involving missing modalities.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29201-29212"},"PeriodicalIF":4.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751107","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}

{"title":"Design and Performance of a Dielectrically Modulated Electron–Hole Bilayer Tunneling FET Biosensor: Effects of Nanogap Cavity on Sensitivity and Voltage Requirements","authors":"Mahdi Vadizadeh","doi":"10.1109/JSEN.2025.3582331","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582331","url":null,"abstract":"This study investigates a biosensor utilizing a dielectrically modulated electronhole bilayer tunneling field-effect transistor (DMEHBTFET) for high-sensitivity applications through numerical device simulation. The research examines three configurations to assess the influence of nanogap cavity placement on biosensor performance concerning bias supply voltage: standard DM-EHBTFET, overlapped DM-EHBTFET, and nonoverlapped DM-EHBTFET. In the standard configuration, the nanogap cavities span both gates. The overlapped design positions them within the overlapping regions of both gates, whereas the nonoverlapped configuration locates the cavities in the nonoverlapping areas of both gates. Simulation results reveal that the standard and overlapped biosensors require minimum bias voltages of <inline-formula> <tex-math>$V_{text {DD}} = 5.5$ </tex-math></inline-formula> V and <inline-formula> <tex-math>$V_{text {DD}} = 4.5$ </tex-math></inline-formula> V, respectively, for detection, while the nonoverlapped biosensor necessitates only 1 V. The nanogap cavity design in the nonoverlapped DMEHBTFET isolates specific regions of both gates, with a length of LOV, from the channel by a 2-nm HfO2 insulator, thereby enhancing electrostatic coupling. This nonoverlapped device consumes 82% less bias voltage than the standard version, rendering it suitable for low-voltage applications. The drain current sensitivity of the nonoverlapped biosensor for a biomolecule with <inline-formula> <tex-math>${K} = 12$ </tex-math></inline-formula> was 431 and 1208 times greater than that of the overlapped and standard biosensors, respectively. For K = 12, the nonoverlapped biosensor exhibits a drain current sensitivity of 3e9, an<sc>on</small>/<sc>off</small> current ratio sensitivity of 2.3e9, a cutoff frequency sensitivity of 2.8e8, and a transconductance sensitivity of 5.45e8. The performance of the nonoverlapped biosensor is evaluated in terms of steric hindrance, and it surpasses recent DM-TFET biosensors, establishing it as a promising candidate for high-sensitivity applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29576-29583"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758203","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}

{"title":"Integrated Wireless Distributed Strain Sensing Using Flexible Electronics for Structural Health Monitoring","authors":"Ant Lakatos;Morgan Riley;Allyssa Bateman;Timothy L. Phero;Matthew Zuzelski;Brian J. Jaques;Zhangxian Deng;Benjamin C. Johnson","doi":"10.1109/JSEN.2025.3582514","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582514","url":null,"abstract":"Real-time, distributed monitoring of the structural integrity of active space habitats is a critical function for manned-space missions, requiring systems that are redundant, compact, robust, and easily reproducible. Toward this goal, we developed resistive and capacitive strain gauges (CSGs) using commercial flexible printed circuit (FPC) technology that are directly integrated with readout electronics for distributed and wireless structural health monitoring. In our prototype system, we distributed 16 gauges that are interconnected on a structural Kevlar strap. Using a single flat flexible cable (FFC) cable between each device, the gauges are daisy-chained to a control hub, where strain information is wirelessly relayed from the hub to a base station via Bluetooth. The developed capacitive and resistive gauges were tested for dynamic strain while attached to Kevlar straps that have a maximum loading of 26.7 kN. We measured gauge factors (GFs) of 1.70 and 1.55 for capacitive and resistive gauges, respectively. The readout system has a volume of 0.1976 cm3 and is capable of interconnecting up to 16 gauges per hub, and multiple hubs can be connected to a base station for large-area strain monitoring.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29597-29604"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758277","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}

{"title":"High-Sensitivity Micro-Liquid-Level Sensor Based on Balloon-Like Core-Offset Structure","authors":"Zhiliang Huang;Zebin Chen;Kaiqi Wang;Xiaoyun Tang;Yaxun Zhang;Zhihai Liu;Yu Zhang;Libo Yuan","doi":"10.1109/JSEN.2025.3582250","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582250","url":null,"abstract":"Based on Mach-Zehnder interference (MZI) principle, we propose a balloon-like optical fiber micro-liquid-level sensor and verify its performance through experiments. The sensor can accurately measure the liquid level of different liquids. The structure of the sensor is to bend into a balloon-like after the single-mode optical fiber core-offset fusion. The core-offset fusion stimulates the cladding mode. The cladding mode and the core mode interfere with each other to form MZI. The liquid surface tension is used to change the bending radius of the sensor structure, so as to realize the measurement of the liquid level. The liquid-level sensitivity of the proposed sensor is 7300 pm/mm, corresponding to a liquid-level resolution of about <inline-formula> <tex-math>$2.74~boldsymbol {mu }$ </tex-math></inline-formula>m. In addition, the temperature sensitivity of the sensor is 91 pm/°C, and the temperature cross crosstalk sensitivity is 0.012 mm/°C. The sensor has significant advantages of good repeatability, high sensitivity, high linearity, and low cost. So, the sensor has broad application prospects in the fields of aerospace, energy and power, and biomedicine and scientific research.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28435-28441"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758413","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}

{"title":"Adaptive Sequence Hybrid Filter-Based Geomagnetic Navigation Method for Autonomous Vehicles","authors":"Qinghua Luo;Mutong Yu;Xiaozhen Yan;Boyuan Liu;Jiayi Sun","doi":"10.1109/JSEN.2025.3582552","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582552","url":null,"abstract":"Geomagnetic navigation is a geomagnetic field-based localization and navigation method that has been widely adopted across various domains. The current algorithms are capable of acquiring absolute positioning data, thereby correcting the cumulative errors inherent in odometry and inertial navigation systems (INSs). However, the positioning accuracy of the current algorithms is significantly affected by noise and trajectory shape of odometry, while its substantial computational load results in limited real-time performance. To address these limitations, this article proposes a geomagnetic navigation method based on an adaptive sequence hybrid filter (ASHF). First, to reduce the impact of measurement errors, we incorporate three additional geomagnetic components into the positioning process to improve its accuracy. Second, we propose a matching method based on a hybrid filter to rectify trajectory shape error. Finally, to address the low real-time performance of sequence matching, we perform feature selection to eliminate heavily disturbed components and reduce subsequent computational load. In addition, an adaptive resampling strategy based on Kullback-Leibler distance is employed to further improve positioning speed. Experimental results demonstrate that compared to odometry, the proposed algorithm reduces the positioning error from 11.766 to 2.353 m, while achieving an average positioning time of 0.044 s.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28238-28251"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758293","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}

{"title":"SEGL-SLAM: A Visual SLAM With Segformer Segmentation and Line Features Enhancement in Dynamic Environments","authors":"Yanyang Chen;Xilong Zhang;Xiaotao Huang;Honjie He;Sang Feng","doi":"10.1109/JSEN.2025.3582241","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582241","url":null,"abstract":"Visual simultaneous localization and mapping (VSLAM) is a crucial technology for autonomous navigation in robotics and remains a prominent area of research. The presence of dynamic objects significantly impacts the localization accuracy of visual SLAM systems, particularly traditional systems that rely on the assumption of a static environment. These systems often struggle to estimate positions accurately when dynamic objects are present in the scene. To address this issue, we propose a dynamic RGB-D SLAM system called SEGL-SLAM, built upon ORB-SLAM3. Our approach integrates a semantic segmentation network to identify objects in dynamic environments, thus extracting semantic information for enhanced localization. We then apply the epipolar constraint method to accurately identify and remove dynamic object features, reducing their interference with both localization and mapping. After removing dynamic feature points, we extract line features from each frame using the LSD algorithm, compensates for the reduced number of features, preventing trajectory estimation errors or map interruptions that could result from the scarcity of feature points. Using both static features and semantic labels, SEGL-SLAM generates dense semantic maps. We evaluate the proposed algorithm on the TUM RGB-D dataset and in real-world dynamic environments. Experimental results demonstrate that our method effectively mitigates the impact of dynamic objects in complex scenarios, exhibiting superior robustness and improved localization accuracy.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28144-28155"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758124","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}