IEEE Sensors Journal最新文献

{"title":"ClO2 Bubble-Propelled Micromotors for Combined Antibiotic Adsorption and Water Disinfection","authors":"Lian Weng;Bangyu Liu;Gaocheng Zhan;Jiawei Cong;Gongwei Hu;Yiman Liu;Min Liu","doi":"10.1109/JSEN.2026.3724629","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3724629","url":null,"abstract":"Pharmaceutical and personal care products (PPCPs) are increasingly detected in aquatic systems owing to their persistence, mobility, and ecological risks, whereas conventional treatment processes are not tailored to these emerging contaminants. Here, we report chlorine-dioxide bubble-propelled micromotors (ClO₂-BPMs) for enhanced antibiotic removal from water. The micromotors consist of a conical magnetic polydimethylsiloxane (PDMS) hydrogel tube loaded with ClO₂ effervescent powder and coated with a chitin-bamboo fiber (Ct–Ba) adsorption layer. During operation, gas generation drives autonomous propulsion and enhances local interfacial transport, while the Ct–Ba layer captures pollutants through multiple interfacial interactions. Relative to quiescent conditions, bubble propulsion markedly accelerates early-stage antibiotic uptake, yielding substantially improved tetracycline (TC) and oxytetracycline (OTC) removal within a short treatment window. Beyond these model antibiotics, the platform shows broad efficacy toward representative pollutants and maintains strong performance in representative real-water matrices. Importantly, the micromotors can be rapidly retrieved after treatment through magnetic actuation, reducing residual solids and supporting practical deployment. In addition, the release of chlorine dioxide during operation provides an intrinsic disinfection capability that may further broaden the applicability of this platform in water treatment.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"31553-31561"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149175983","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":"Brillouin Frequency Shift Demodulation Algorithm for Concrete Microcracks Identification Based on Frequency Domain Sliding Window Accumulation","authors":"Xiaohu Li;Tao Wang;Yanchun Gu;Xiaoning Dong;Xinyu Han;Ruixin Wang;Jianzhong Zhang;Mingjiang Zhang","doi":"10.1109/JSEN.2026.3731094","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3731094","url":null,"abstract":"When Brillouin distributed sensing systems are applied to concrete crack monitoring, weak Brillouin gain spectra (BGS) changes caused by microcracks are easily submerged by various factors, such as concrete deformation, residual stress, and system noise, leading to low detection accuracy and poor real-time performance. Existing demodulation algorithms struggle to distinguish the slight changes in the BGS caused by microcracks. To address this limitation, we propose a novel demodulation algorithm integrating baseline differential preprocessing with frequency domain sliding window accumulation. The baseline differencing eliminates global systematic interferences and highlights crack-induced spectral changes, while the frequency domain sliding window accumulation suppresses both coherent fading noise and random noise based on their zero-mean statistical characteristics. Experimental results show that the proposed algorithm improves the signal-to-noise ratio (SNR) by approximately 10 dB, reduces the Brillouin frequency shift (BFS) uncertainty from ±4 to ±1 MHz, and reduces the required data acquisition averages from 5000 to 500. To verify algorithm performance, we cast C30 concrete beams and conducted bending tests. Results show the algorithm can accurately identify millimeter-level cracks. With simple structure and high computational efficiency, this algorithm provides a practical solution for high-precision real-time crack monitoring of bridges, tunnels, and other infrastructure.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30533-30539"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176004","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":"Experimental Study on AFBGA Sensor for Stress–Vibration Safety Monitoring of Bolt Supporting Roadway","authors":"Jianjun Dong;Hongwei Liu;Bing Zhu","doi":"10.1109/JSEN.2026.3726542","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3726542","url":null,"abstract":"With increasing mining depth and extraction intensity in coal mines, rock burst disasters occur frequently. However, as a key supporting component in coal mine roadways, rock bolts exhibit complex dynamic response signals, making it difficult to directly extract useful information. This study proposes a Butterworth filtering decoupling method based on dynamic spectrum identification and adaptive parameter optimization, and introduces zero-phase filtering to suppress phase distortion, achieving synchronous high-precision decoupling of stress–vibration coupled signals under impact loading. By constructing an apodized fiber Bragg grating array (AFBGA)-based dynamic monitoring experimental system for rock bolts, composite dynamic response signals under impact loading were acquired. A decoupling algorithm was then applied to separate the composite signals, and the accuracy and precision of the algorithm were comprehensively evaluated. The results show that, under different working conditions, the minimum coefficient of determination (R²) value of the linear fit between the decoupled stress signal and the composite signal is greater than 0.9, while the mean absolute error (MAE) and root-mean-square error (RMSE) between the stress and vibration signals remain at generally low levels, verifying the high accuracy of the decoupling algorithm. In addition, for vibration signals under different working conditions, the <inline-formula> <tex-math>$pm 2sigma $ </tex-math></inline-formula> values from 100 repeated experiments are all less than ±0.045 Hz, indicating that the measurement accuracy of the dominant vibration frequency reaches ±0.045 Hz. This study provides a new technical approach for decoupling composite signals of rock bolts under impact loading, which is of great significance for achieving coal mine safety monitoring and early warning.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30600-30610"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176006","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 Unfolding and Gated Fusion for Aeromagnetic Compensation","authors":"Boyao Zhang;Sixu Wen;Linliang Miao;Hailin Qiu;Zihao Chen;Jun Ouyang;Xiaofei Yang","doi":"10.1109/JSEN.2026.3727450","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3727450","url":null,"abstract":"Measurements from airborne magnetic sensors are susceptible to platform magnetic interference and therefore require effective aeromagnetic compensation to improve measurement accuracy. Compensation methods based on the Tolles–Lawson (T-L) model are physically interpretable, but their fixed linear-coefficient assumption limits their adaptability to complex and time-varying platform interference. Neural-network compensation methods can improve the modeling of nonlinear interference from sensor observations, but their compensation process usually lacks explicit T-L physical-structure constraints, which limits result interpretability; when the training and test flight conditions differ, the compensation performance of these methods is more likely to be affected. This article proposes a dual-branch collaborative model for aeromagnetic compensation of airborne magnetic sensor measurements. The model consists of a deep unfolding physical branch and a data-driven neural branch. The deep unfolding physical branch uses the T-L physical structure as its backbone, incorporates temporal constraints and learnable state updates into the compensation process, and combines physical priors with adaptive modeling capability; the data-driven neural branch provides nonlinear representation information complementary to the physical branch. The two branches are adaptively fused through a gating network to perform aeromagnetic compensation. Experimental results show that the proposed method can improve compensation performance while maintaining good stability and physical interpretability, providing an effective approach for combining physical models with neural networks in airborne magnetic sensor measurement compensation.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30858-30869"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176072","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":"Multisensor Electronic Platform for High-Resolution HIV-Antigen Detection","authors":"Arianna Adelaide Maurina;Francesco Damin;Laura Sola;Chiara Capelli;Elena Criscuolo;Nicola Clementi;Marcella Chiari;Cainã de Oliveira Figares;Evans Atta Asamoah;Francesco Zanetto;Giorgio Ferrari;Marco Sampietro","doi":"10.1109/JSEN.2026.3727431","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3727431","url":null,"abstract":"The growing demand for rapid, accurate, and decentralized diagnostics has accelerated the development of point-of-care (PoC) biosensors for early disease detection. In this work, we demonstrate the detection of the HIV-specific capsid antigen p24 protein by a compact, fully electronic, and reconfigurable bioelectronic platform based on impedance sensing. The platform integrates a multichannel array of gold interdigitated electrodes (IDEs) that can be independently functionalized to enable multiplexing, redundancy, and statistical validation. A differential readout architecture, combining transimpedance amplification with FPGA-based digital lock-in detection, ensures the highest stability over temperature and salinity fluctuations and effective rejection of common-mode errors. Experimental validation demonstrated sensitive detection of HIV p24 across multiple concentrations, with a limit of detection (LOD) of 8.5 pg/mL. Measurements on virus isolate samples further confirmed the robustness and reliability of the platform. These results establish the system as a versatile and scalable option for next-generation PoC diagnostics, with particular strengths in stable, multichannel, and adaptable antigen detection: thanks to the copolymer coating of the chips, reconfiguration requires only the substitution of the spotted probes, enabling applications that range from highly specific biorecognition elements to broader capture molecules.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"31331-31340"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176110","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":"Specific and Optimized PVC Membrane-Based Ion-Selective Field-Effect Transistors for Determination of Nitrate","authors":"Yuhao Ma;Siyu Ye;Haoran Cheng;Qijin Cheng","doi":"10.1109/JSEN.2026.3732296","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3732296","url":null,"abstract":"Nitrate (NO<inline-formula> <tex-math>${}_{{3}}^{-}$ </tex-math></inline-formula>) monitoring is essential for precision agriculture and environmental protection, yet solid-state ion sensors often suffer from sub-Nernstian sensitivity due to unoptimized polymeric membrane formulations. In this work, we present a systematic ratio-optimization strategy for the nitrate-selective polyvinyl chloride (PVC) membrane to enhance the interfacial potential coupling efficiency of Ta₂O₅-gate ion-sensitive field-effect transistors (ISFETs). By precisely tuning the stoichiometric mass ratios of the PVC matrix, o-NPOE plasticizer, and TDDAN ionophore, the thermodynamic energy barrier for ion extraction was minimized. The optimized sensor (Formula B: 13.5 wt% TDDAN, 41.0 wt% PVC, and 45.5 wt% o-NPOE) achieves a near-Nernstian sensitivity of 59.0 mV/decade with excellent linearity (R<inline-formula> <tex-math>${}^{{2}} =0.999$ </tex-math></inline-formula>) over a wide concentration range from <inline-formula> <tex-math>$10^{-{4}}$ </tex-math></inline-formula> to <inline-formula> <tex-math>$10^{-{1}}$ </tex-math></inline-formula> M, and a detection limit of <inline-formula> <tex-math>${3}.{7}{,}{,}times {,}{,}{10} ^{-{6}}$ </tex-math></inline-formula> M. The sensor exhibits robust selectivity against common interfering anions with logarithmic selectivity coefficients ranging from −2.7 to −4.7, consistent with the classical Hofmeister series. Long-term stability tests revealed a low potential drift of 0.166 mV/h over 8 h, representing an 88.3% improvement over untreated devices. The underlying mechanism of the sensitivity enhancement is discussed in terms of the plasticizer-to-PVC ratio and its influence on ion mobility and interfacial adhesion. Real sample validation using tap water, lake water, and soil extract confirmed satisfactory accuracy with recovery rates of 93.2%–120.5%. This work provides a reliable reference for the design of high-performance solid-state ion sensors and demonstrates their potential for scalable deployment in Internet of Things (IoT)-enabled environmental monitoring networks.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30043-30050"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176111","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":"Clinical Diagnostic Efficacy of a Point-of-Care Testing Device for Noncommunicable Diseases","authors":"Ankit Chowdhury;Sahil Jagnani;Nilanjana Medhi;Saurabh Dubey;Shweta Tiwari;Snigdha Saikia;Suchita Markan;Rajesh Sagar;Pankaj Upadhyay;Madhumita Das;Dipankar Bandyopadhyay","doi":"10.1109/JSEN.2026.3724249","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3724249","url":null,"abstract":"Noncommunicable diseases (NCDs) pose a serious threat to the world population. In this direction, point-of-care testing (POCT) devices can expedite the delivery of rapid and timely results, offering a clinically significant advantage in patient management even in low-resource settings. To address these issues, this study has been performed to make a comparison between a portable blood testing analyzer device named “Mobilab” as a POCT device with a fully automated clinical laboratory analyzer (Siemens Dimension EXL 200) to evaluate the device performance. Mobilab is a portable, Internet of Things (IoT)-enabled, battery-operated, and smartphone-app-operated device that provides digital patient data in real time at an affordable cost. The present study evaluated the efficacy of Mobilab by analyzing five biochemical parameters, viz., cholesterol (CHOL), triglycerides (TGL), low-density low-lipoprotein-cholesterol (LDL-C), creatinine (CRE), and uric acid (UA), as crucial parameters that are indicative of normal functionality in healthy individuals. Validation of Mobilab was performed by comparing results from 50 to 52 human serum samples and assessing analytical sensitivity, linearity, precision, and performance matrices. In terms of statistical analysis, all tested parameters showed consistency and accuracy, indicating reliable and consistent performance by Mobilab. As a POCT device, Mobilab delivers digital, rapid, and direct results from a patient’s blood sample, eliminating the need for manual result analysis. Utilizing Mobilab to monitor health parameters could promote a healthy lifestyle with cost-effectiveness and time efficiency, potentially preventing the development of critical health conditions in resource-constrained areas (RCAs) of both developed and developing countries.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"31541-31552"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176116","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":"Thin-Film Devices on Flexible and Unobtrusive Cellulose for Sustainable Temperature Sensing","authors":"Hafiza Faiqa Maqsood;Ahmed Rasheed;Soufiane Krik;Fahimeh Masoumi;Franco Cacialli;Paolo Lugli;Luisa Petti;Dianne C. Corsino;Riccardo Zamboni;Niko Münzenrieder;Giuseppe Cantarella","doi":"10.1109/JSEN.2026.3723956","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3723956","url":null,"abstract":"Despite remarkable progress in flexible electronics, the reliance on nonbiodegradable polymers and energy-intensive fabrication processes continues to impede their environmental compatibility and long-term viability. To address this stark sustainability concern, recent research efforts have pivoted toward the exploration of eco-friendly materials with low carbon footprint. In pursuit of this objective, we demonstrate the fabrication of thin-film resistance temperature detectors (RTDs) and thin-film thermistor sensors on a triacetyl cellulose (TAC) film. These devices are characterized in a temperature range from <inline-formula> <tex-math>$25,^{circ }$ </tex-math></inline-formula>C to <inline-formula> <tex-math>$75,^{circ }$ </tex-math></inline-formula>C, demonstrating average sensitivity of 0.21%/°C<inline-formula> <tex-math>${}^{-{1}}$ </tex-math></inline-formula> for the Cu-based RTDs, 0.065%/°C<inline-formula> <tex-math>${}^{-{1}}$ </tex-math></inline-formula> for Mo-based RTDs, and −0.26%/°C<inline-formula> <tex-math>${}^{-{1}}$ </tex-math></inline-formula> for Mo/indium gallium zinc oxide (IGZO) based thermistors. The performance of all devices is further evaluated under cyclic thermal stress and varying humidity conditions. Furthermore, device performance is demonstrated under applied mechanical strain, retaining reliable functionality down to 8 mm bending radii. Finally, Mo-based RTDs and thermistor sensors revealed transient behavior in deionized water after 26 and 30 h, respectively. The finding highlights the potential of a cellulose-based TAC substrate for integration with thin-film devices, enabling reusability and environmental sustainability for green electronic applications while contributing to the minimization of electronic waste.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30117-30125"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11674386","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176188","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}

{"title":"Underwater Crack Detection and Segmentation via Transformer-Based Style Transfer With Global–Local Feature Fusion","authors":"Tao Liu;Qin Cheng;Lingji Xu;Jianming Miao","doi":"10.1109/JSEN.2026.3725742","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3725742","url":null,"abstract":"Deep-learning-enabled autonomous underwater vehicles (AUVs) have shown strong potential for autonomous underwater structural inspection, yet reliable crack detection and segmentation remain constrained by scarce underwater crack data and degraded imaging conditions. This article presents a crack-aware framework that combines structure-preserving style transfer for underwater crack image synthesis with DBE-YOLO for underwater crack detection and segmentation. In the style transfer stage, terrestrial crack images are translated into underwater-style samples using a Transformer-based model, where a quality-aware consistency loss is designed to suppress patchwise style artifacts and color distortion while preserving crack structures. In the perception stage, we propose DBE-YOLO, a YOLOv7-based detector-segmenter tailored to underwater crack geometry. DBE-YOLO incorporates deformable convolution v2 (DCNv2), bilevel routing attention (BRA), and Explicit Visual Center (EVC) to align adaptive sampling, contextual reasoning, and global–local feature fusion with the elongated morphology, weak visual contrast, and background interference of underwater cracks. Focal-EIoU and binary cross-entropy (BCE)-Dice losses are further adopted to improve bounding-box localization and mask delineation, respectively. A dedicated underwater crack dataset containing both synthesized and real underwater crack images is constructed for training and evaluation. Experiments on unseen real underwater crack images show that DBE-YOLO improves detection mean average precision (mAP) from 82.0% to 87.1% over the YOLOv7 baseline, while the BCE-Dice loss improves average precision (AP)-mask from 86.8% to 88.1% for segmentation. These results demonstrate the effectiveness of the proposed framework for underwater crack detection and segmentation under challenging underwater conditions.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30362-30375"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176191","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":"A Multimodal Tactile Sensor for Material Recognition, Force Measurement, and Slip Detection in Robotic Gripper","authors":"Zixian Zhu;Chenhao Zhang;Xiaofei Bu;Long Li;Quan Zhang;Yingzhong Tian;Yangqiao Lin;Tao Jin","doi":"10.1109/JSEN.2026.3727996","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3727996","url":null,"abstract":"This article presents a compact multimodal tactile sensor integrating triboelectric, bending, and pressure-sensing elements for robotic automation manipulation. Four triboelectric electrode pairs with different friction materials are used for surface-material recognition, while a bending sensor embedded in a centrally located silicone protrusion responds to tangential deformation associated with object slip. A pressure sensor beneath a rigid support structure measures the normal gripping force. Finite-element analysis was used to optimize the geometry of the central protrusion and the support-pillar height to improve the sensitivity and stability of slip detection. Experimental results show that the pressure-sensing unit provides a response range of 0–100 N, whereas the bending-sensing unit responds to tangential displacements of 0–4 mm. The triboelectric-sensing unit achieves classification of six materials via a 1-D convolutional neural network, with a test accuracy of 99.17%. In a robotic-grasping experiment, the sensor recognized the surface materials of three cups and detected slip induced by a progressively increasing payload. The detected slip signal automatically triggered an increase in gripping force and prevented further downward motion of the cup. These results demonstrate the feasibility of integrating material recognition, force measurement, and slip detection into a single tactile sensing device for adaptive robotic grasping.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"31355-31364"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176227","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}