{"title":"Retraction Notice: A Proposed MIMO Antenna Prototype for Frequency Identification","authors":"Amin H. Al Ka’bi","doi":"10.1109/JSEN.2025.3546793","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3546793","url":null,"abstract":"Frequency Identification in Cognitive Radio (CR) networks is the key step to find the unused frequencies, so CR networks use less bandwidth and energy. The MIMO antenna system which is proposed for spectrum sensing in CR systems is a small super-wideband (SWB) design, which includes three band-notched diversity antennas. There are four identical semi-elliptical monopole antennas, directed perpendicularly with feed lines gently widened CWG type, which constitute a MIMO antenna. Every SWB characteristic has an antenna that has the cross-slot carved through its bottom just like a radiator. The antenna radiator is composed of two linked slits that replicate the image of the split ring resonator and also have a backward-S shaped slit to ensure that there is no negative impact on SWB. The antenna has a bandwidth ratio of 36:1mm and 0.2-43mm waves. In addition, 18dB of isolation and an envelope correlation coefficient of less than 0.01 have been implemented in a resonant frequency band for the MIMO antenna that has orthogonally placed antenna elements. On a frequency of 3.5GHz, 5.5GHz, and 8.5GHz, the gain level drops leading to a maximum gain of 4 dBi for the antenna. The proposed antenna has higher bandwidth ratio and hence incorporates easily into an existing RF equipment. In this manner, this SWB, MIMO antenna demonstrates superiority over those mentioned in the literature with a multi-notched band. In the same manner, we obtain three small super-wideband (SWB), which have not been filtered, so, the design and implementation of the antenna is feasible.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 6","pages":"10512-10512"},"PeriodicalIF":4.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10916580","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628713","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}
Xiong Cheng;Zhixiang Zhai;Pengfei Zhang;Yiqi Zhou;Rui Wang;Wenhua Gu;Xiaodong Huang;Daying Sun
{"title":"Corrections to “Generating Multiple Distinct Feasible Solutions for MEMS Accelerometers Using Deep Learning”","authors":"Xiong Cheng;Zhixiang Zhai;Pengfei Zhang;Yiqi Zhou;Rui Wang;Wenhua Gu;Xiaodong Huang;Daying Sun","doi":"10.1109/JSEN.2025.3528277","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3528277","url":null,"abstract":"Presents corrections to the paper, Corrections to “Generating Multiple Distinct Feasible Solutions for MEMS Accelerometers Using Deep Learning”.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"9209-9209"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10912817","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553462","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":"Corrections to “Improved XGBoost and GM UWB/MEME IMU Positioning Methods for Non-Line-of-Sight Environments”","authors":"Xin Sui;Bangwen Liao;Changqiang Wang;Zhengxu Shi","doi":"10.1109/JSEN.2024.3524872","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3524872","url":null,"abstract":"Presents corrections to the paper, (Corrections to “Improved XGBoost and GM UWB/MEME IMU Positioning Methods for Non-Line-of-Sight Environments”).","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"9208-9208"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10912815","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553191","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}
Michele Magno;Daniela de Venuto;Giuseppe Ferri;Seonyeong Heo
{"title":"Guest Editorial Special Issue on Energy-Efficient Embedded Intelligent Sensor Systems (S1)","authors":"Michele Magno;Daniela de Venuto;Giuseppe Ferri;Seonyeong Heo","doi":"10.1109/JSEN.2025.3537212","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3537212","url":null,"abstract":"","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"7733-7733"},"PeriodicalIF":4.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10912814","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553311","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":"Comparative Evaluation of Flexible and Rigid Dry Electrodes Versus Gel Electrodes for Reliable ECG Monitoring in Android Wearable Smart Garment","authors":"Nacera Meziane;Merouane Bouzid;Dalila Meziane;Malika Kedir-Talha","doi":"10.1109/JSEN.2025.3537016","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3537016","url":null,"abstract":"Conventional silver/silver chloride (Ag/AgCl) gel electrodes are widely used in clinical settings due to their excellent signal quality. Long-term use can, however, lead to skin irritation. Reusable dry electrodes offer a promising alternative for wearable electrocardiogram (ECG) devices, potentially reducing hospitalization time and healthcare costs, especially for elderly individuals with sensitive skin. In order to address this need, we developed a smart garment integrated with novel dry electrodes for wireless ECG recording. The acquired ECG signals are transmitted via Bluetooth to a developed Android Smartphone application, “ECG Surveillance.” The application displays the heart rate (HR) alongside the ECG signal. An alert notification is triggered if the HR falls outside the normal range of [60, 90] beats per minute (bpm). The entire system is battery-powered, rechargeable, and designed for extended use. We experimentally validated the system on a male subject, comparing the performance of gel and dry electrodes during the specific movements outlined in our experimental protocol. Additionally, we developed an algorithm to assess the performance of each electrode type based on HR, sensitivity, and signal-to-artifact ratio (SAR). A novel artifact removal technique was also proposed.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 6","pages":"9747-9758"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621648","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":"An Enhanced Microwave Differential Microfluidic Sensing System for Detecting Small Variation of Dielectric Properties","authors":"Xinyue Song;Guy A. E. Vandenbosch;Sen Yan","doi":"10.1109/JSEN.2025.3536466","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3536466","url":null,"abstract":"This article proposes a microwave sensor based on differential structure to detect small changes in the dielectric properties of biological microfluids. By examining the underlying operating principles of the differential sensing system, the key factors influencing sensor performance are identified. The proposed design enhances sensitivity by optimizing both the sensing branches and the overall configuration. Two coupled eighth-mode (EM) substrate-integrated waveguide (SIW) resonators with concentrated electric field tips are employed in the sensing branches, which exhibit rapid phase variation as the sample under test (SUT) changes, thereby improving the sensitivity of the original differential zero point. Furthermore, the introduction of an additional zero point caused by self-resonance achieves double increase in sensor sensitivity within a narrow frequency band. The sensor operates in the frequency range of 4.7–5.7 GHz, and its performance has been validated using ethanol-water solution with varying concentrations to simulate the subtle changes in biofluids under physiological conditions. The proposed structure offers a potential solution to the sensitivity challenges posed by subtle changes of high dielectric permittivity samples in biosensing.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 6","pages":"9608-9617"},"PeriodicalIF":4.3,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621853","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":"TPL-SLAM: Real-Time Monocular Thermal–Inertial SLAM With Point–Line Tracked by Optical Flow","authors":"Luguang Lai;Linyang Li;Yuxuan Zhou;Letian Zhang;Dongqing Zhao","doi":"10.1109/JSEN.2025.3537164","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3537164","url":null,"abstract":"Visual simultaneous localization and mapping (SLAM) systems perform poorly or even fail to work under extreme conditions such as insufficient light, smoke, and fog, and the infrared camera has stronger anti-interference ability in these challenging scenes. However, the high noise and poor imaging quality of infrared camera severely affect the performance of infrared SLAM. Considering the imaging characteristics of the infrared camera and the weak-texture features of subterranean structured scenes, a point-line combined thermal–inertial SLAM system (TPL-SLAM) is proposed. To improve the computational efficiency of point-line combined SLAM, a superior ELSED algorithm is employed to extract line features. Meanwhile, a 3 degrees-of-freedom (DOF) line feature optical flow tracking algorithm is proposed to track line features between continuous frames. Then, the back-end module optimizes inertial measurement unit (IMU), point, and line feature factors in real-time based on a sliding window and jointly performs loop detection with the point and line features on keyframes. Extensive experiments were conducted on real-world datasets to validate the effectiveness of TPL-SLAM. The results showed that TPL-SLAM outperformed the current advanced monocular visual-inertial system (VINS). Besides, parallel loop detection with point-line features can effectively reduce the risk of false loops. The computational efficiency of the proposed line feature extraction and tracking module is superior to those of PL-VINS and EPLF-VINS and can meet the requirements of real-time operation. The data and code for line feature processing are accessible at <uri>https://github.com/Fireflyatcode/TPL_SLAM</uri>.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 6","pages":"10015-10029"},"PeriodicalIF":4.3,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891346","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621661","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":"Monitoring Model Based on Data-Driven Optimization Stochastic Configuration Network and Its Applications","authors":"Aijun Yan;Kaicheng Hu;Dianhui Wang","doi":"10.1109/JSEN.2025.3538942","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3538942","url":null,"abstract":"Accurately monitoring key parameters of the production process is one of the prerequisites for ensuring efficient and stable production. However, some key parameters are difficult to measure online in real-time, and their change mechanisms are poorly understood. This article proposes a data-driven optimization stochastic configuration network (DO-SCN) soft sensor modeling method to build high-performance monitoring models. The DO-SCN is incrementally constructed within a newly designed configuration-evaluation-learning-modification framework. The parameters and connection ways of the model are determined via parallel construction and an adaptive supervisory evaluation mechanism. A parameter modification strategy is proposed to reduce the redundancy of the hidden layer nodes. The performance of the DO-SCN model is evaluated on six benchmark regression datasets and a furnace temperature dataset derived from municipal solid waste incineration (MSWI) power plant. The experimental results show that the DO-SCN model has advantages in model accuracy and structural compactness, achieving the lowest RMSE and MAPE values of 3.486 and 5.811 on the MSWI dataset, respectively. It has good potential for application in production process monitoring modeling tasks.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 6","pages":"10087-10096"},"PeriodicalIF":4.3,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621788","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}