IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144478

Jixing Ye, Gian-Franco Dalla Betta

{"title":"Influence of Surface Isolation Layers on High-Voltage Tolerance of Small-Pitch 3D Pixel Sensors.","authors":"Jixing Ye, Gian-Franco Dalla Betta","doi":"10.3390/s25144478","DOIUrl":"10.3390/s25144478","url":null,"abstract":"In recent years, 3D pixel sensors have been a topic of increasing interest within the High Energy Physics community. Due to their inherent radiation hardness, demonstrated up to a fluence of 3×1016 1 MeV equivalent neutrons per square centimeter, 3D pixel sensors have been used to equip the innermost tracking layers of the ATLAS and CMS detector upgrades at the High-Luminosity Large Hadron Collider. Additionally, the next generation of vertex detectors calls for precise measurement of charged particle timing at the pixel level. Owing to their fast response times, 3D sensors present themselves as a viable technology for these challenging applications. Nevertheless, both radiation hardness and fast timing require 3D sensors to be operated with high bias voltages on the order of ∼150 V and beyond. Special attention should therefore be devoted to avoiding problems that could cause premature electrical breakdown, which could limit sensor performance. In this paper, TCAD simulations are used to gain deep insight into the impact of surface isolation layers (i.e., p-stop and p-spray) used by different vendors on the high-voltage tolerance of small-pitch 3D sensors. Results relevant to different geometrical configurations and irradiation scenarios are presented. The advantages and disadvantages of the available technologies are discussed, offering guidance for design optimization. Experimentalmeasurements from existing samples based on both isolation techniques show good agreement with simulated breakdown voltages, thereby validating the simulation approach.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12298425/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144744683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

Measuring Blink-Related Brainwaves Using Low-Density Electroencephalography with Textile Electrodes for Real-World Applications. 测量眨眼相关的脑电波使用低密度脑电图与纺织品电极的实际应用。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144486

Emily Acampora, Sujoy Ghosh Hajra, Careesa Chang Liu

{"title":"Measuring Blink-Related Brainwaves Using Low-Density Electroencephalography with Textile Electrodes for Real-World Applications.","authors":"Emily Acampora, Sujoy Ghosh Hajra, Careesa Chang Liu","doi":"10.3390/s25144486","DOIUrl":"10.3390/s25144486","url":null,"abstract":"Background: Electroencephalography (EEG) systems based on textile electrodes are increasingly being developed to address the need for more wearable sensor systems for brain function monitoring. Blink-related oscillations (BROs) are a new measure of brain function that corresponds to brainwave responses occurring after spontaneous blinking, and indexes neural processes as the brain evaluates new visual information appearing after eye re-opening. Prior studies have reported BRO utility as both a clinical and non-clinical biomarker of cognition, but no study has demonstrated BRO measurement using textile-based EEG devices that facilitate user comfort for real-world applications. Methods: We investigated BRO measurement using a four-channel EEG system with textile electrodes by extracting BRO responses using existing, publicly available EEG data (n = 9). We compared BRO effects derived from textile-based electrodes with those from standard dry Ag/Ag-Cl electrodes collected at the same locations (i.e., Fp1, Fp2, F7, F8) and using the same EEG amplifier. Results: Results showed that BRO effects measured using textile electrodes exhibited similar features in both time and frequency domains compared to dry Ag/Ag-Cl electrodes. Data from both technologies also showed similar performance in artifact removal and signal capture. Conclusions: These findings provide the first demonstration of successful BRO signal capture using four-channel EEG with textile electrodes, providing compelling evidence toward the development of a comfortable and user-friendly EEG technology that uses the simple activity of blinking for objective brain function assessment in a variety of settings.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12299738/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144744794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

Measuring the Operating Condition of Induction Motor Using High-Sensitivity Magnetic Sensor. 用高灵敏度磁传感器测量感应电动机的工作状态。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144471

Akane Kobayashi, Kenji Nakamura, Takahito Ono

引用次数: 0

Extraction of Clinically Relevant Temporal Gait Parameters from IMU Sensors Mimicking the Use of Smartphones. 从模拟智能手机使用的IMU传感器提取临床相关的时间步态参数。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144470

Aske G Larsen, Line Ø Sadolin, Trine R Thomsen, Anderson S Oliveira

{"title":"Extraction of Clinically Relevant Temporal Gait Parameters from IMU Sensors Mimicking the Use of Smartphones.","authors":"Aske G Larsen, Line Ø Sadolin, Trine R Thomsen, Anderson S Oliveira","doi":"10.3390/s25144470","DOIUrl":"10.3390/s25144470","url":null,"abstract":"As populations age and workforces decline, the need for accessible health assessment methods grows. The merging of accessible and affordable sensors such as inertial measurement units (IMUs) and advanced machine learning techniques now enables gait assessment beyond traditional laboratory settings. A total of 52 participants walked at three speeds while carrying a smartphone-sized IMU in natural positions (hand, trouser pocket, or jacket pocket). A previously trained Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM)-based machine learning model predicted gait events, which were then used to calculate stride time, stance time, swing time, and double support time. Stride time predictions were highly accurate (<5% error), while stance and swing times exhibited moderate variability and double support time showed the highest errors (>20%). Despite these variations, moderate-to-strong correlations between the predicted and experimental spatiotemporal gait parameters suggest the feasibility of IMU-based gait tracking in real-world settings. These associations preserved inter-subject patterns that are relevant for detecting gait disorders. Our study demonstrated the feasibility of extracting clinically relevant gait parameters using IMU data mimicking smartphone use, especially parameters with longer durations such as stride time. Robustness across sensor locations and walking speeds supports deep learning on single-IMU data as a viable tool for remote gait monitoring.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12299727/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144744749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

MSWF: A Multi-Modal Remote Sensing Image Matching Method Based on a Side Window Filter with Global Position, Orientation, and Scale Guidance. 基于全局位置、方向和尺度引导的侧窗滤波器的多模态遥感图像匹配方法。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144472

Jiaqing Ye, Guorong Yu, Haizhou Bao

{"title":"MSWF: A Multi-Modal Remote Sensing Image Matching Method Based on a Side Window Filter with Global Position, Orientation, and Scale Guidance.","authors":"Jiaqing Ye, Guorong Yu, Haizhou Bao","doi":"10.3390/s25144472","DOIUrl":"10.3390/s25144472","url":null,"abstract":"Multi-modal remote sensing image (MRSI) matching suffers from severe nonlinear radiometric distortions and geometric deformations, and conventional feature-based techniques are generally ineffective. This study proposes a novel and robust MRSI matching method using the side window filter (MSWF). First, a novel side window scale space is constructed based on the side window filter (SWF), which can preserve shared image contours and facilitate the extraction of feature points within this newly defined scale space. Second, noise thresholds in phase congruency (PC) computation are adaptively refined with the Weibull distribution; weighted phase features are then exploited to determine the principal orientation of each point, from which a maximum index map (MIM) descriptor is constructed. Third, coarse position, orientation, and scale information obtained through global matching are employed to estimate image-pair geometry, after which descriptors are recalculated for precise correspondence search. MSWF is benchmarked against eight state-of-the-art multi-modal methods-six hand-crafted (PSO-SIFT, LGHD, RIFT, RIFT2, HAPCG, COFSM) and two learning-based (CMM-Net, RedFeat) methods-on three public datasets. Experiments demonstrate that MSWF consistently achieves the highest number of correct matches (NCM) and the highest rate of correct matches (RCM) while delivering the lowest root mean square error (RMSE), confirming its superiority for challenging MRSI registration tasks.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12300616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144744778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

Post-Quantum Linkable Hash-Based Ring Signature Scheme for Off-Chain Payments in IoT. 物联网下链支付的后量子可链接哈希环签名方案。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144484

Linlin He, Xiayi Zhou, Dongqin Cai, Xiao Hu, Shuanggen Liu

{"title":"Post-Quantum Linkable Hash-Based Ring Signature Scheme for Off-Chain Payments in IoT.","authors":"Linlin He, Xiayi Zhou, Dongqin Cai, Xiao Hu, Shuanggen Liu","doi":"10.3390/s25144484","DOIUrl":"10.3390/s25144484","url":null,"abstract":"Off-chain payments in the Internet of Things (IoT) enhance the efficiency and scalability of blockchain transactions. However, existing privacy mechanisms face challenges, such as the disclosure of payment channels and transaction traceability. Additionally, the rise of quantum computing threatens traditional public key cryptography, making the development of post-quantum secure methods for privacy protection essential. This paper proposes a post-quantum ring signature scheme based on hash functions that can be applied to off-chain payments, enhancing both anonymity and linkability. The scheme is designed to resist quantum attacks through the use of hash-based signatures and to prevent double spending via its linkable properties. Furthermore, the paper introduces an improved Hash Time-Locked Contract (HTLC) that incorporates a Signature of Knowledge (SOK) to conceal the payment path and strengthen privacy protection. Security analysis and experimental evaluations demonstrate that the system strikes a favorable balance between privacy, computational efficiency, and security. Notably, the efficiency benefits of basic signature verification are particularly evident, offering new insights into privacy protection for post-quantum secure blockchain.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12298650/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144744813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

Review of Acoustic Emission Detection Technology for Valve Internal Leakage: Mechanisms, Methods, Challenges, and Application Prospects. 阀内泄漏声发射检测技术综述：机理、方法、挑战及应用前景。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144487

Dongjie Zheng, Xing Wang, Lingling Yang, Yunqi Li, Hui Xia, Haochuan Zhang, Xiaomei Xiang

{"title":"Review of Acoustic Emission Detection Technology for Valve Internal Leakage: Mechanisms, Methods, Challenges, and Application Prospects.","authors":"Dongjie Zheng, Xing Wang, Lingling Yang, Yunqi Li, Hui Xia, Haochuan Zhang, Xiaomei Xiang","doi":"10.3390/s25144487","DOIUrl":"10.3390/s25144487","url":null,"abstract":"Internal leakage within the valve body constitutes a severe potential safety hazard in industrial fluid control systems, attributable to its high concealment and the resultant difficulty in detection via conventional methodologies. Acoustic emission (AE) technology, functioning as an efficient non-destructive testing approach, is capable of capturing the transient stress waves induced by leakage, thereby furnishing an effective means for the real-time monitoring and quantitative assessment of internal leakage within the valve body. This paper conducts a systematic review of the theoretical foundations, signal-processing methodologies, and the latest research advancements related to the technology for detecting internal leakage in the valve body based on acoustic emission. Firstly, grounded in Lechlier's acoustic analogy theory, the generation mechanism of acoustic emission signals arising from valve body leakage is elucidated. Secondly, a detailed analysis is conducted on diverse signal processing techniques and their corresponding optimization strategies, encompassing parameter analysis, time-frequency analysis, nonlinear dynamics methods, and intelligent algorithms. Moreover, this paper recapitulates the current challenges encountered by this technology and delineates future research orientations, such as the fusion of multi-modal sensors, the deployment of lightweight deep learning models, and integration with the Internet of Things. This study provides a systematic reference for the engineering application and theoretical development of the acoustic emission-based technology for detecting internal leakage in valves.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12300226/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144744835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

Advanced Multi-Scale CNN-BiLSTM for Robust Photovoltaic Fault Detection. 基于改进多尺度CNN-BiLSTM的光伏故障鲁棒检测。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144474

Xiaojuan Zhang, Bo Jing, Xiaoxuan Jiao, Ruixu Yao

{"title":"Advanced Multi-Scale CNN-BiLSTM for Robust Photovoltaic Fault Detection.","authors":"Xiaojuan Zhang, Bo Jing, Xiaoxuan Jiao, Ruixu Yao","doi":"10.3390/s25144474","DOIUrl":"10.3390/s25144474","url":null,"abstract":"The increasing deployment of photovoltaic (PV) systems necessitates robust fault detection mechanisms to ensure operational reliability and safety. Conventional approaches, however, struggle in complex industrial environments characterized by high noise, data incompleteness, and class imbalance. This study proposes an innovative Advanced CNN-BiLSTM architecture integrating multi-scale feature extraction with hierarchical attention to enhance PV fault detection. The proposed framework employs four parallel CNN branches with kernel sizes of 3, 7, 15, and 31 to capture temporal patterns across various time scales. These features are then integrated by an adaptive feature fusion network that utilizes multi-head attention. A two-layer bidirectional LSTM with temporal attention mechanism processes the fused features for final classification. Comprehensive evaluation on the GPVS-Faults dataset using a progressive difficulty validation framework demonstrates exceptional performance improvements. Under extreme industrial conditions, the proposed method achieves 83.25% accuracy, representing a substantial 119.48% relative improvement over baseline CNN-BiLSTM (37.93%). Ablation studies reveal that the multi-scale CNN contributes 28.0% of the total performance improvement, while adaptive feature fusion accounts for 22.0%. Furthermore, the proposed method demonstrates superior robustness under severe noise (σ = 0.20), high levels of missing data (15%), and significant outlier contamination (8%). These characteristics make the architecture highly suitable for real-world industrial deployment and establish a new paradigm for temporal feature fusion in renewable energy fault detection.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12300933/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144744579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

A 1000 fps High-Dynamic-Range Global Shutter CMOS Image Sensor with Full Thermometer Code Current-Steering Ramp. 一个1000帧/秒的高动态范围全局快门CMOS图像传感器与完整的温度计代码电流转向斜坡。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144483

Liqiang Han, Ganlin Cheng, Xu Zhang, Gengyun Wang, Weijun Pan, Yao Yao, Guihai Yu, Ruimeng Zhang, Shuaichen Mu, Songbo Wu, Hongbo Bu, Liqun Dai, Ben Fan, Dan Wang, Wei Fan, Ruiming Chen

引用次数: 0

Cyber-Physical System Interface for Implantable Esophageal Prosthesis. 植入式食管假体的信息物理系统接口。

IF 3.5 3区综合性期刊

Sensors Pub Date : 2025-07-18 DOI: 10.3390/s25144469

Ana Magdalena Anghel, Teodora Mîndra

引用次数: 0

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