IEEE Sensors Letters最新文献_第2页

Collective Optimization of Synthesis and Printing for Improved Performance of ZnO Nanowires Based Large-Area Printed Sensors

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-28 DOI: 10.1109/LSENS.2025.3555528

Fengyuan Liu;Dhayalan Shakthivel;Adamos Christou;Leandro Lorenzelli;Ravinder Dahiya

{"title":"Collective Optimization of Synthesis and Printing for Improved Performance of ZnO Nanowires Based Large-Area Printed Sensors","authors":"Fengyuan Liu;Dhayalan Shakthivel;Adamos Christou;Leandro Lorenzelli;Ravinder Dahiya","doi":"10.1109/LSENS.2025.3555528","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3555528","url":null,"abstract":"ZnO nanowires (NWs) form an important building block for various types of sensors and field-effect transistors. However, owing to the known variability of ZnO structure morphologies, it is challenging to obtain ZnO NWs alone by using synthesis processes such as vapor phase transport. To address this challenge, we have performed a series of NW synthesis studies and discovered that it is difficult to eliminate ZnO nanoflakes during the growth stage. By optimizing the synthesis and printing method together, it is possible to reduce considerably the size and density of undesirable structures, such as printed flakes, to a level where they would not bridge the contacts of the device and thus not affect the device's performance. As proof of concept, the ZnO NWs-based UV photodetectors were realized using the contact printing method. The developed devices show the photo-to-dark current ratio of 104, a rise time of ∼3.1 s, and a decay time of 8.6 s. The removal of flakes contributes to the low level of dark current, which is critical to low power consumption. The presented results provide a promising route for ZnO NWs ensembles based large area sensing for applications such as electronic skin for humanoids, and more.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830518","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

Stator Interturn Fault Detection in BLDC Motors: A Signal-Processing-Based Method

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-27 DOI: 10.1109/LSENS.2025.3555389

Mohammad Amin Jarrahi;Ahmad Jafari;Vahid Abolghasemi;Jawad Faiz

引用次数: 0

High-Speed Volumetric Capture for Vibration Propagation in the Human Body

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-27 DOI: 10.1109/LSENS.2025.3555391

Toma Mori;Feiyue Wang;Kohei Shimasaki;Idaku Ishii

引用次数: 0

Bias Compensation for Kernel Least-Mean-Square Algorithms

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-24 DOI: 10.1109/LSENS.2025.3553594

Ying-Ren Chien;Jin-Ling Liu;En-Ting Lin;Guobing Qian

引用次数: 0

Ferroelectret-Based Insole for Vertical Ground Reaction Force Estimation Using a Convolutional Neural Network

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-21 DOI: 10.1109/LSENS.2025.3553491

Omid Mohseni;Janick Betz;Bastian Latsch;Julian Seiler;André Seyfarth;Mario Kupnik

{"title":"Ferroelectret-Based Insole for Vertical Ground Reaction Force Estimation Using a Convolutional Neural Network","authors":"Omid Mohseni;Janick Betz;Bastian Latsch;Julian Seiler;André Seyfarth;Mario Kupnik","doi":"10.1109/LSENS.2025.3553491","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3553491","url":null,"abstract":"Precise and portable ground reaction force (GRF) measurement is critical for advancing biomechanical gait analysis and enabling more effective control of robots and assistive devices. This study investigates vertical GRF estimation during walking using a soft, lightweight, and cost-effective 3D-printed ferroelectret insole. The insole design incorporates four monolithically 3D-printed piezoelectric sensors positioned under key foot contact areas, which generate nonlinear voltage in response to applied forces. A 1-D convolutional neural network (CNN), featuring two convolutional and two fully connected layers, was trained to predict vertical GRF across five different walking speeds (50–150% of normal walking speed). The CNN was validated using K-fold cross-validation, enhancing model generalization. Results showed an average root-mean-squared error of 9.24% and <inline-formula><tex-math>$R^{2}$</tex-math></inline-formula> values exceeding 0.99 across different speeds, demonstrating the potential of 3D-printed ferroelectret sensors for portable GRF measurement in gait analysis and robotics applications.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830544","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

Enhancing Surgical Laparoscopic Video Quality Assessment With Integrated Feature Fusion Accounting for Sensor and Transmission Distortions

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-20 DOI: 10.1109/LSENS.2025.3553292

Ajay Kumar Reddy Poreddy;Priyanka Kokil;Balasubramanyam Appina

{"title":"Enhancing Surgical Laparoscopic Video Quality Assessment With Integrated Feature Fusion Accounting for Sensor and Transmission Distortions","authors":"Ajay Kumar Reddy Poreddy;Priyanka Kokil;Balasubramanyam Appina","doi":"10.1109/LSENS.2025.3553292","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3553292","url":null,"abstract":"In this letter, an opinion-aware quality assessment (QA) model for surgical laparoscopic videos (LVs) considering sensor and transmission distortions is proposed based on statistical disparities between luminance and color components of the opponent color space (OCS). First, the luminance variations among the frames of distorted LVs are computed based on the energy of the Gabor subbands and weighted histogram features of the local binary pattern map. Second, the color degradations of each frame of LV are estimated based on the chromatic components of the OCS using moment statistics and the shape and spread parameters of the asymmetric generalized Gaussian distribution. These features are computed across two scales, concatenated, and pooled to obtain the overall quality representative feature set of the LVs. Finally, an AdaBoost back propagation neural network is utilized to map the extracted feature set to quality scores using labels as surgeons opinion scores. Extensive experiments demarcate that the proposed QA model for surgical LVs outperforms the existing video QA models with an overall linear correlation coefficient of 0.9800 and Spearman rank order correlation of 0.9247 on the LVQA dataset, respectively.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865357","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

Wearable RFID Sensor for Simultaneous Heartbeat and Respiration Monitoring

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-20 DOI: 10.1109/LSENS.2025.3548147

Runhao Zhang;Bo Zhang;Zhaozong Meng;Chenxi Li;Haichao Liu;Nan Gao

{"title":"Wearable RFID Sensor for Simultaneous Heartbeat and Respiration Monitoring","authors":"Runhao Zhang;Bo Zhang;Zhaozong Meng;Chenxi Li;Haichao Liu;Nan Gao","doi":"10.1109/LSENS.2025.3548147","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3548147","url":null,"abstract":"Novel sensing and communication techniques have created new opportunities for unobtrusive vital sign monitoring. Due to the features of wireless power and data transfer and non-line-of-sight interrogation of radio frequency identification (RFID), its innovative integration with different sensing elements has become a promising solution. Since the heartbeat and respiration signals are weak and their measurement is time-consuming, a lightweight and flexible solution for their unobtrusive wearable sensing remains a challenge. This investigation presents a novel capacitive pressure sensor (CPS)-augmented RFID solution for simultaneous and wearable sensing of heartbeat and respiration. The main contributions include: first, proposal of an innovative RFID-based vital sign monitoring scheme, which integrates a CPS for heartbeat sensing and employs RFID phase signals for respiration sensing; second, design and fabrication of a polydimethylsiloxane (PDMS)-based flexible and porous slotted CPS for continuous heartbeat sensing; and third, development of respiration signal reconstruction algorithm using the weak and noisy RFID phase integrating phase disambiguation, denoising, baseline removal, and peak detection. Experimental studies are conducted to verify the feasibility and effectiveness of the presented techniques.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667611","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

Performance Evaluation for a Muddy Water Contamination on Autonomous Sensors

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-20 DOI: 10.1109/LSENS.2025.3553101

Sungho Shin;Namkyun Kim;Wancheol Gim;Hun-Jae Kim;Joon Woo Lee;Hyuntaeck Lim

{"title":"Performance Evaluation for a Muddy Water Contamination on Autonomous Sensors","authors":"Sungho Shin;Namkyun Kim;Wancheol Gim;Hun-Jae Kim;Joon Woo Lee;Hyuntaeck Lim","doi":"10.1109/LSENS.2025.3553101","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3553101","url":null,"abstract":"Autonomous driving systems depend heavily on advanced recognition sensors, such as light detection and ranging, radar, cameras, and ultrasonic sensors, to navigate dynamic environments safely and effectively. However, these sensors are vulnerable to environmental contamination, particularly from muddy water, which can significantly degrade their optical performance. This letter presents a standardized method for evaluating the impact of muddy water contamination on recognition sensor cover with a focus on assessing transmittance reduction. An automated injection system was employed to apply varying levels of contamination to polycarbonate windows, and transmittance was estimated based on a pulsed laser module. The proposed method demonstrated that practical applicability was achieved by comparison with real-world contamination during test driving and laboratory findings. This research will provide a reliable, standardized approach to quantify the effects of various contaminations on sensor performance, also contributing to the development of more robust autonomous driving technologies capable of operating in harsh environmental conditions.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769410","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

High Responsivity in Near-Infrared Phototransistor With Oriented Polymer Semiconductors

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-19 DOI: 10.1109/LSENS.2025.3549783

Manish Pandey;Shubham Sharma;Shyam S. Pandey;Masakazu Nakamura

{"title":"High Responsivity in Near-Infrared Phototransistor With Oriented Polymer Semiconductors","authors":"Manish Pandey;Shubham Sharma;Shyam S. Pandey;Masakazu Nakamura","doi":"10.1109/LSENS.2025.3549783","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3549783","url":null,"abstract":"Near-infrared organic phototransistors (OPTs) in bottom-gated top-contact structures are being reported using an oriented p-type diketopyrrolopyrrole-based semiconducting polymer (SCP) (DPPT-TT). Here, highly oriented DPPT-TT floating films were prepared on a liquid substrate using the unidirectional floating-film transfer method (UFTM) and then utilized as the active layer. This innovative approach exhibits a dual-orientation advantage: They align polymer chains unidirectionally, enhancing charge transport along the backbone while simultaneously promoting an edge-on molecular arrangement relative to the substrate. This combination, coupled with highly uniform thin films, facilitates efficient charge transport pathways, contributing significantly to the fabrication of high-performance OPTs. Our DPPT-TT-based OPT exhibited a high field-effect mobility of 1.5 cm2·V−1·s−1 and photoresponsivity (R) > 105 A·W−1 at an intensity of 45 <italic>μW·cm−2 under 810 nm light illumination. This exceptional performance is attributed to faster carrier transport and efficient charge collection in the oriented DPPT-TT films enabled by the UFTM.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769379","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

IEEE Sensors Letters Publication Information

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-19 DOI: 10.1109/LSENS.2025.3549957

引用次数: 0