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IEEE Sensors Letters Publication Information IEEE传感器通讯出版信息
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-15 DOI: 10.1109/LSENS.2025.3527772
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引用次数: 0
IEEE Sensors Letters Subject Categories for Article Numbering Information 用于物品编号信息的IEEE传感器字母主题分类
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-15 DOI: 10.1109/LSENS.2025.3527776
{"title":"IEEE Sensors Letters Subject Categories for Article Numbering Information","authors":"","doi":"10.1109/LSENS.2025.3527776","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3527776","url":null,"abstract":"","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 1","pages":"3-3"},"PeriodicalIF":2.2,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10842684","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993386","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
Electric Field-Induced Exosome Lysis and Quantification of TSG101-Derived Protein via Electrochemical Sensing
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-15 DOI: 10.1109/LSENS.2024.3522106
Nusrat Praween;Pammi Guru Krishna Thej;Palash Kumar Basu
{"title":"Electric Field-Induced Exosome Lysis and Quantification of TSG101-Derived Protein via Electrochemical Sensing","authors":"Nusrat Praween;Pammi Guru Krishna Thej;Palash Kumar Basu","doi":"10.1109/LSENS.2024.3522106","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3522106","url":null,"abstract":"Exosomes that contain TSG101 biomarkers are synthesized by both healthy and malignant cells and have the potential to accurately diagnose a wide range of diseases, including cancer. For exosomal protein quantification, exosomes must be isolated from serum and then used for protein extraction. Ultracentrifugation is the most common way to isolate. Although detergents are commonly employed to extract the encapsulated exosomal proteins, they may compromise their protein integrity. The present work involves two detailed studies: the lysing of exosomes immobilized on the Au screen printed electrode (SPE) and the development of a nonfaradaic electrochemical sensor by utilizing SPE to quantity TSG101 protein. To lyse exosomes attached to the SPE surface, we applied different amplitudes of square signals to the SPE to disrupt the exosomes and facilitate the release of their contents. The lysate solution was utilized for electrochemical impedance spectroscopy (EIS) by faradic and nonfaradic techniques. Results of both types of EIS were similar, showing that nonfaradaic sensing could be an effective alternative. Hence, we employed nonfaradaic EIS to quantify the TSG101 protein released by electric lysis and validated the result with ELISA. We achieved a linear response, specifically at concentrations ranging from 0.125 to 8 ng/mL, with a detection limit of 0.10 ng/mL for human serum. Cross-reactivity analysis demonstrated selectivity to TSG101 with minimal interaction with nonspecific biomolecules.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105621","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
An Automatic Feature Extraction Method for Gas Sensors Based on Color-Enhanced Phase Space
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-15 DOI: 10.1109/LSENS.2025.3529584
Guangfen Wei;Xuerong Wang;Aixiang He;Wei Zhang;Baichuan Wang
{"title":"An Automatic Feature Extraction Method for Gas Sensors Based on Color-Enhanced Phase Space","authors":"Guangfen Wei;Xuerong Wang;Aixiang He;Wei Zhang;Baichuan Wang","doi":"10.1109/LSENS.2025.3529584","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3529584","url":null,"abstract":"Aiming to improve the effectiveness and the identity of features extracted from gas sensor responses, a novel automatic feature extraction method is proposed and studied. A simple color-enhanced phase-space approach is proposed to convert the dynamic gas sensor signals into images, which emphasizes the internal features of phase space. A lightweight neural network, i.e., MobileNetV2, is adopted to automatically extract the features and classify the odors. The method has been embedded into a lab system to classify the freshness of yellow peaches, and the final freshness classification accuracy reaches 98.58%, which is more than 20% improvement of average classification accuracy than the traditional time domain or frequency domain feature extraction and recognition methods. Compared to the original phase space, more than 10% improvement in average classification accuracy has also been obtained.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706819","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
Phase-Based Approaches for Rapid Construction of Magnetic Fields in NV Magnetometry
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-14 DOI: 10.1109/LSENS.2025.3529780
Prabhat Anand;Ankit Khandelwal;Achanna Anil Kumar;M Girish Chandra;Pavan K Reddy;Anuj Bathla;Dasika Shishir;Kasturi Saha
{"title":"Phase-Based Approaches for Rapid Construction of Magnetic Fields in NV Magnetometry","authors":"Prabhat Anand;Ankit Khandelwal;Achanna Anil Kumar;M Girish Chandra;Pavan K Reddy;Anuj Bathla;Dasika Shishir;Kasturi Saha","doi":"10.1109/LSENS.2025.3529780","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3529780","url":null,"abstract":"With the second quantum revolution underway, quantum-enhanced sensors are moving from laboratory demonstrations to field deployments, providing enhanced and even new capabilities. Signal processing and operational software are becoming integral parts of these emerging sensing systems to reap the benefits of this progress. This letter looks into widefield nitrogen vacancy (NV) center-based magnetometry and focuses on estimating the magnetic field from the optically detected magnetic resonances (ODMR) signal, a crucial output for various applications. Mapping the shifts of ODMR signals to phase estimation, a computationally efficient approaches are proposed. Involving Fourier transform (FT) and filtering as preprocessing steps, the suggested approaches involve linear curve fit or complex frequency estimation based on well known super-resolution technique estimation of signal parameters via rotational invariant techniques (ESPRIT). The existing methods in the quantum sensing literature take different routes based on Lorentzian fitting for determining magnetic field maps. To showcase the functionality and effectiveness of the suggested techniques, relevant results, based on experimental data are provided, which shows a significant reduction in computational time with the proposed method over existing methods.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 3","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379544","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
Medical Sensor Data Security: A DNN Framework for SOP Prediction in Two-Way Relay NOMA Systems
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-14 DOI: 10.1109/LSENS.2025.3528978
Astitva Kamble;Harsh Dalwadi;Mahendra K. Shukla;Om Jee Pandey;Vishal Krishna Singh
{"title":"Medical Sensor Data Security: A DNN Framework for SOP Prediction in Two-Way Relay NOMA Systems","authors":"Astitva Kamble;Harsh Dalwadi;Mahendra K. Shukla;Om Jee Pandey;Vishal Krishna Singh","doi":"10.1109/LSENS.2025.3528978","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3528978","url":null,"abstract":"Securing medical sensor data are imperative due to the susceptibility of wireless transmissions to eavesdropping. In this letter, we focus on improving the security of two-way communication in medical networks by investigating deep neural networks (DNN) for two-way (TWR) relay nonorthogonal multiple access (NOMA) systems. Utilizing a decode-and-forward (DF) relay and considering both maximum ratio combining and selection combining at the eavesdropper, we derive analytical expressions for the secrecy outage probability (SOP), leveraging the exact SOP expression from (Shukla et al., 2020). Due to the system's complexity, deriving a closed-form SOP is challenging. To address this, we introduce a DNN framework for real-time SOP prediction, which not only validates the theoretical model but also significantly reduces offline execution time and computational complexity.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105533","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 Sensing in Low-Field (0.55 T) MRI Environment
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-13 DOI: 10.1109/LSENS.2025.3528305
Felix Muñoz;Krishna S. Nayak;Yasser Khan
{"title":"Wearable Sensing in Low-Field (0.55 T) MRI Environment","authors":"Felix Muñoz;Krishna S. Nayak;Yasser Khan","doi":"10.1109/LSENS.2025.3528305","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3528305","url":null,"abstract":"Wearable sensors in the magnetic resonance imaging (MRI) environment enable the use of wearable devices to monitor vital signs, such as heart rate, respiration rate, blood pressure, temperature, and biochemical markers, during an MRI scan. Here, we demonstrate the efficacy of Bluetooth Low Energy (BLE)-enabled optical photoplethysmogram (PPG) sensors at a low-field MRI strength of 0.55 T. We evaluate the noise in a wearable device caused by eddy currents from the rapidly switching MRI gradients, as well as the MRI noise and artifacts introduced by the BLE wearable into the MR receiver. Our results show that a custom-made BLE PPG sensor can operate effectively during 0.55 T MRI scanning, providing precise (within 20 ms) wireless monitoring of PPG with no observable effect on either the sensor signal or image quality. These results are encouraging for future wearable sensing in the MRI environment.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105622","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-Speed, Low-Power Bootstrapped Class-B Driver Amplifier for LCoS Applications
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-13 DOI: 10.1109/LSENS.2025.3528395
Yingqi Feng;Yuwei Jiang;Chenghe Yang;Hui Wang;Li Tian;Yongxin Zhu;Qiliang Li;Zunkai Huang
{"title":"High-Speed, Low-Power Bootstrapped Class-B Driver Amplifier for LCoS Applications","authors":"Yingqi Feng;Yuwei Jiang;Chenghe Yang;Hui Wang;Li Tian;Yongxin Zhu;Qiliang Li;Zunkai Huang","doi":"10.1109/LSENS.2025.3528395","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3528395","url":null,"abstract":"In this letter, we present a high-speed, low-power bootstrapped class-B driver amplifier for liquid crystal on silicon (LCoS) applications. The amplifier, incorporating a dynamically adjustable bootstrapping control circuit, doubles the voltage driving range compared to traditional circuits, significantly enhancing system flexibility and performance in high-resolution environments. The design drives a 120-pF capacitive load with a slew rate of 13.65 V/µs and a settling time of 0.685 µs, while consuming only 7-µA quiescent current from a 5-V supply. Fabricated using a 0.18 µm high-voltage complementary metal-oxide-semiconductor (HV CMOS) process, the driver can power multiple pixel columns. Measurement results confirm the circuit's effectiveness in supporting holographic projection and display for LCoS technologies.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105623","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
Electrochemical Sensor With Dynamic Self-Calibration for Acetaminophen Detection in Water
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-10 DOI: 10.1109/LSENS.2025.3528342
Bryan E. Alvarez-Serna;Daniel A. Arcos-Santiago;Jorge A. Uc-Martín;Roberto G. Ramírez-Chavarría
{"title":"Electrochemical Sensor With Dynamic Self-Calibration for Acetaminophen Detection in Water","authors":"Bryan E. Alvarez-Serna;Daniel A. Arcos-Santiago;Jorge A. Uc-Martín;Roberto G. Ramírez-Chavarría","doi":"10.1109/LSENS.2025.3528342","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3528342","url":null,"abstract":"In this letter, we introduce a self-calibrating electrochemical sensor for water acetaminophen (ACT) detection. The sensor is built upon a graphite pencil lead (GPL) electrode modified with a molecularly imprinted polymer (MIP) to ensure selectivity. Moreover, using a sparse identification scheme, the sensor is equipped with a dynamic calibration algorithm to increase the sensor accuracy in time-dependent measurements. The sensor performance was evaluated under static and dynamic conditions using ACT solutions prepared in tap water as the matrix. As a result, the sensor achieved a detection limit of 9.3 mg/L, proving to be a viable alternative for quantifying emerging concerns in water. Finally, we show how simple but robust sensor models could enhance the performance of online measurements.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105624","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
Room-Temperature-Operated Fe2O3/PANI-Based Flexible and Eco-Friendly Ammonia Sensor With Sub-ppm Detectability 室温工作Fe2O3/ pani基柔性环保亚ppm检测氨传感器
IF 2.2
IEEE Sensors Letters Pub Date : 2025-01-08 DOI: 10.1109/LSENS.2025.3527229
Ajay Beniwal;Rahul Gond;Xenofon Karagiorgis;Brajesh Rawat;Chong Li
{"title":"Room-Temperature-Operated Fe2O3/PANI-Based Flexible and Eco-Friendly Ammonia Sensor With Sub-ppm Detectability","authors":"Ajay Beniwal;Rahul Gond;Xenofon Karagiorgis;Brajesh Rawat;Chong Li","doi":"10.1109/LSENS.2025.3527229","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3527229","url":null,"abstract":"In this letter, a room temperature (RT) (∼27 °C) operated ferric oxide/polyaniline (Fe<sub>2</sub>O<sub>3</sub>/PANI) composite-based flexible ammonia sensor with substantial sensing performance is reported. Initially, interdigitated electrodes were screen printed (using graphene-carbon-based ink) on a bio-degradable paper substrate. Further, PANI nanofibers were electrospun on printed IDEs, followed by drop casting a layer of Fe<sub>2</sub>O<sub>3</sub>. X-ray diffraction and Fourier transform infrared spectroscopy studies were performed to confirm the composite formation, followed by scanning electron microscopy analysis to examine the sensing surface morphology. The ammonia sensing performance was examined within the range of 0.5 ppm (i.e., 500 ppb) to 50 ppm, with a 1.99% response achieved even at 0.5 ppm. The response/recovery times were noted as 950/250 s toward 0.5 ppm of ammonia. In addition, selectivity toward interference gases including carbon dioxide, nitrogen dioxide, carbon monoxide, and sulfur dioxide was also investigated. The proposed sensing mechanism of the composite material toward ammonia gas detection is also presented.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 2","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993287","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
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