IEEE Sensors Letters最新文献_第7页

Eye Movement Detection Based on SM-SSA and Quantum CNN from EMG of EOM Signals 基于SM-SSA和量子CNN的眼动检测

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-12 DOI: 10.1109/LSENS.2025.3550346

Kiran Kumar Makam;Vivek Kumar Singh;Ram Bilas Pachori

引用次数: 0

Real-Time Detection of D-Glucose Molecules in Exhaled Aerosols Using a Biochemical Sensor for Breathalyzer Applications 呼气气溶胶中d -葡萄糖分子的实时检测使用生化传感器呼气分析仪应用

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-12 DOI: 10.1109/LSENS.2025.3546084

Pardis Sadeghi;Nader Lobandi;Rania Alshawabkeh;Amie Rui;William Sun;Juntong Chen;Bin Luo;Rui Huang;Nian X. Sun

引用次数: 0

PA-YOLO: Small Target Detection Algorithm With Enhanced Information Representation for UAV Aerial Photography 基于增强信息表示的无人机航拍小目标检测算法PA-YOLO

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-11 DOI: 10.1109/LSENS.2025.3550406

Ming Zeng;Siyu He;Qingli Zeng;Yibo Niu;Renmin Zhang

引用次数: 0

Machine Learning Assisted Characterization of Hidden Metallic Objects 机器学习辅助表征隐藏金属物体

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-10 DOI: 10.1109/LSENS.2025.3549923

Marko Šimić;Davorin Ambruš;Vedran Bilas

引用次数: 0

Highly Reliable Impedimetric Sensor Based on Silver Nanoparticle-Functionalized Composites of Graphene Oxide and Ionic Liquid for the Detection of Trace Levels of the Pesticide Malathion 基于纳米银功能化氧化石墨烯与离子液体复合材料的高可靠阻抗传感器检测农药中痕量马拉硫磷

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-10 DOI: 10.1109/LSENS.2025.3549518

Tianqi Lu;Saddam Weheabby;Anurag Adiraju;Zongyan Li;Yang Li;Ammar Al-Hamry;Igor A. Pasti;Olfa Kanoun

{"title":"Highly Reliable Impedimetric Sensor Based on Silver Nanoparticle-Functionalized Composites of Graphene Oxide and Ionic Liquid for the Detection of Trace Levels of the Pesticide Malathion","authors":"Tianqi Lu;Saddam Weheabby;Anurag Adiraju;Zongyan Li;Yang Li;Ammar Al-Hamry;Igor A. Pasti;Olfa Kanoun","doi":"10.1109/LSENS.2025.3549518","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3549518","url":null,"abstract":"Malathion (MLT), a widely used organophosphate pesticide for global pest control, presents substantial risks to both human health and ecosystems. Therefore, the development of a rapid and efficient detection method is critical to mitigate its harmful effects. This study proposes a novel thin-film impedimetric sensor designed for the reliable detection of MLT pesticide residues based on laser-induced graphene electrodes coated with a sensing composite material comprising graphene oxide, 1-butyl-3-methylimidazolium hexafluorophosphate, and silver nanoparticles. Mechanical and electrochemical stabilities are enhanced by the integration of polyvinyl chloride (PVC) and 2-nitrophenyl octyl ether (o-NPOE) into framework materials. The sensor exhibited excellent sensitivity toward MLT in the concentration range of 1 – 200 nm. The charge transfer resistance R<sub>ct</sub> increases by 304.08% at a concentration of 200 nm. The sensor shows minimal interference and good reproducibility and repeatability. A change in R<sub>ct</sub> of 15.61% over 30 days confirms good stability. Using framework materials enhances the long-term stability by 11.45 times compared to sensors without them. The synergistic effects of the three sensitive materials and the structural support from PVC and o-NPOE enable outstanding detection capabilities. The novel sensor has a high potential for pesticide residue detection in the environment, providing a reliable and efficient tool for preserving ecosystems, supporting sustainable agriculture, and ensuring compliance with environmental regulations.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tampon-Based Sensors for Monitoring Intravaginal pH Levels 基于卫生棉条的阴道内pH值监测传感器

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-07 DOI: 10.1109/LSENS.2025.3549185

Goran M. Stojanović;Saima Qureshi;Hima Zafar;Dušica Dimitrijević;Ivana Tomić

{"title":"Tampon-Based Sensors for Monitoring Intravaginal pH Levels","authors":"Goran M. Stojanović;Saima Qureshi;Hima Zafar;Dušica Dimitrijević;Ivana Tomić","doi":"10.1109/LSENS.2025.3549185","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3549185","url":null,"abstract":"The proposed work is a proof-of-concept study aimed at developing a sensor capable of measuring and monitoring vaginal pH. The objective of this research is to examine the design concepts and operational principles of a vaginal sensor that utilizes soft, biodegradable textile materials. Traditional methods of assessing vaginal pH levels, such as evaluating vaginal fluids or discharge from the vaginal walls, are difficult to perform consistently over long periods and are often prone to errors. Our sensor demonstrates a simple fabrication technique of pH value monitoring based on the capacitive principle by embroidering the sensors onto a tampon, which is comfortable and biocompatible. Silver conductive threads, known for their antibacterial properties, are used. Two different geometries of embroidered electrodes are proposed for the pH sensors, enabling the monitoring of vaginal pH. A device that tracks changes in pH value aids in early detection, notifies users of potential health changes, supports women's self-management of wellness, and helps prevent conditions, such as vaginitis or sexually transmitted infections associated with pH levels above 4.7.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10916920","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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 Novel Machine Learning and Sensor-Driven System for Nondestructive Detection of Jaggery Adulteration 用于无损检测掺假琼脂的新型机器学习和传感器驱动系统

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-07 DOI: 10.1109/LSENS.2025.3548887

Vinayak Bairagi;Vaishali H. Kamble;Sharad T Jadhav;Mrinal R Bachute

{"title":"A Novel Machine Learning and Sensor-Driven System for Nondestructive Detection of Jaggery Adulteration","authors":"Vinayak Bairagi;Vaishali H. Kamble;Sharad T Jadhav;Mrinal R Bachute","doi":"10.1109/LSENS.2025.3548887","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3548887","url":null,"abstract":"Food adulteration is a major challenge on a global scale impacting 10% of the food supply and leading to financial losses up to $30–40 billion annually. A developing country, such as India, is also not an exception to this widespread concerning issue and has significant adulteration cases reported across various categories, including Jaggery, which is its major product sharing 55% of the total world Jaggery production. While the literature reports a few methods for detecting various food adulterations, jaggery—the most popular food in India—has received meagre attention. Moreover, the reported methods have limited success and need further experimentation on a variety of diverse datasets before they are practically deployable. This research presents a classical, novel color-based method for detecting the adulteration in the jaggery. A color sensor is used to detect the color of melted jaggery samples, and an Arduino Uno is used to further analyze the color for reliable detection of adulteration. This research exploits the direct relationship between the captured pixel intensities of the jaggery and its purity to develop a linear regression model. The developed product is validated using samples having varying percentages of adulterations (10%–70%) caused due to single and multiple adulterants (sugar and food color) in jaggery. The machine learning-based novel approach developed in this research gives promising results with an accuracy of 94.67% and a precision as 92.6%. The developed method for identifying tampered jaggery is user-friendly, affordable, portable, and nondestructive and the experimental results confirm its superiority.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Microstrip Line Loaded With Series Gap and Dumbbell Defect-Ground-Structure (DB-DGS) Resonator for Highly Sensitive Sensing Based on Resonance/Antiresonance: Application to Humidity Measurements 基于共振/反共振的高灵敏度传感用串联缺口和哑铃缺陷-地结构（DB-DGS）谐振器微带线：在湿度测量中的应用

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-05 DOI: 10.1109/LSENS.2025.3567134

Nazmia Kurniawati;Paris Vélez;Pau Casacuberta;Lijuan Su;Xavier Canalias;Ferran Martín

{"title":"Microstrip Line Loaded With Series Gap and Dumbbell Defect-Ground-Structure (DB-DGS) Resonator for Highly Sensitive Sensing Based on Resonance/Antiresonance: Application to Humidity Measurements","authors":"Nazmia Kurniawati;Paris Vélez;Pau Casacuberta;Lijuan Su;Xavier Canalias;Ferran Martín","doi":"10.1109/LSENS.2025.3567134","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3567134","url":null,"abstract":"A new planar structure for the implementation of highly sensitive single-frequency microwave sensors is proposed. The key aspect to obtain high sensitivity is to generate closely spaced resonance and antiresonance frequencies, achieved by means of a microstrip line with a series gap etched on top of a transversely oriented dumbbell defect-ground-structure (DB-DGS) resonator, the sensitive element. By this means, both the magnitude and the phase of the transmission coefficient exhibit a high phase slope between such frequencies. The result is a high sensitivity of either the magnitude or the phase of the transmission coefficient at the operating frequency with the dielectric constant of the environment surrounding the DB-DGS resonator. Advantages of the proposed device are size and simplicity, and isolation between the analyte (or material under test) and the line strip. Two sensors with different DB-DGS geometries are reported to validate the proposed approach. Using the phase as the main output variable, the maximum sensitivity in one of the prototypes is found to be 88.7° per unit of dielectric constant variation. This sensor has been applied to relative humidity (RH) measurements by using a functional film of polyvinyl alcohol deposited on top of the sensing DB-DGS resonator. The average sensitivity in this case is 0.33°/% (note that RH is given in %).","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 6","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10988649","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wearable Multisensory Glove for Shape, Size, and Stiffness Recognition Based on Off-the-Shelf Components 基于现成部件的形状、尺寸和刚度识别的可穿戴多感官手套

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-05 DOI: 10.1109/LSENS.2025.3548264

Mohamad Yaacoub;Ali Ibrahim;Fatima Khansa;Leila Hammadi;Christian Gianoglio

引用次数: 0

FPGA-Based Real-Time Road Object Detection System Using mmWave Radar 基于fpga的毫米波雷达实时道路目标检测系统

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-03 DOI: 10.1109/LSENS.2025.3547008

Anand Mohan;Hemant Kumar Meena;Mohd Wajid;Abhishek Srivastava

{"title":"FPGA-Based Real-Time Road Object Detection System Using mmWave Radar","authors":"Anand Mohan;Hemant Kumar Meena;Mohd Wajid;Abhishek Srivastava","doi":"10.1109/LSENS.2025.3547008","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3547008","url":null,"abstract":"This letter presents the development of a real-time object detection system using frequency modulated continuous wave millimeter-wave (mmWave) radar signals and the python productivity for zynq ultrascale + mpsocs (PYNQ-ZU) field-programmable gate array (FPGA) board, which is widely used in advanced driving assistance system and robotic applications. A hardware FPGA platform serves as a valid embedded architecture for the purpose of validating object detection and recognition applications. We used our experiment's point cloud images to apply different machine learning models to detect these objects. Using a top-view (TV) filter to convert 3-D point cloud images into 2-D representations made object detection more accurate. Following the use of filtration techniques, we extracted features from the filtered 2-D image using the visual geometry group (VGG) 16 model. We then assessed four machine learning models for object detection and found that the support vector machine (SVM) model and logistic regression (LR) had better results, obtaining an accuracy of 97%. Our proposed work uses mmWave radar, TV filter, VGG 16 Model, and LR to highly increase object detection accuracy over existing methods.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0