IEEE Sensors Letters最新文献_第9页

Droplet Heating Using Liquid Dielectrophoresis: A Parametric Study 利用液体压电效应加热液滴：参数研究

IF 2.2

IEEE Sensors Letters Pub Date : 2024-08-07 DOI: 10.1109/LSENS.2024.3439720

Krishnadas Narayanan Nampoothiri;Aswathy M Narayanan;Challa Praneeth Kumar

{"title":"Droplet Heating Using Liquid Dielectrophoresis: A Parametric Study","authors":"Krishnadas Narayanan Nampoothiri;Aswathy M Narayanan;Challa Praneeth Kumar","doi":"10.1109/LSENS.2024.3439720","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3439720","url":null,"abstract":"Droplet manipulation using digital microfluidics is extensively being researched for various biological and chemical sensor applications. Among the various methods, liquid dielectrophoresis (L-DEP) offers precise droplet manipulation using high-frequency electric fields. L-DEP also aids in generating temperature inside the droplet. Even though droplet heating using L-DEP promises various potential capabilities in microfluidic sensor development, droplet actuation at high voltages [greater than 400 V peak voltage (V\u0000p\u0000)] remains a concern. In this manuscript, the parameters, such as dielectric material and dielectric thickness, which are responsible for droplet heating, are investigated numerically through simulations. By keeping the dielectric thickness constant, the relation between temperature rise and frequency for various V\u0000p\u0000 was simulated for seven different dielectrics, mainly Si\u00003\u0000N\u00004\u0000, ZnO, and alumina. A temperature rise of 100 °C was generated using V\u0000p\u0000 = 200 V at 200 kHz using Si\u00003\u0000N\u00004\u0000 as the dielectric, which proves the capability of using this technique at lower voltages. However, the complexity in fabrication hinders its usage in microfluidic applications. Thus, we investigated low dielectric strength materials, such as ZnO and alumina. We observed that despite the dielectric film being porous, due to synthesis, the effect of the porosity of these films in droplet heating is found to be minimal. Finally, the variation of temperature rise inside the droplet with varying dielectric film thickness for various kHz frequencies by keeping the V\u0000p\u0000 is studied. This study is crucial in developing droplet thermal sensors, which could replicate the functions of microheaters for various microfluidic applications.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041378","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

SO2 Gas Detection Using GLAD-Synthesized ZnO Nanowires 利用 GLAD 合成的氧化锌纳米线检测二氧化硫气体

IF 2.2

IEEE Sensors Letters Pub Date : 2024-08-07 DOI: 10.1109/LSENS.2024.3440044

K. Moatemsu Aier;Jay Chandra Dhar

引用次数: 0

Breast Cancer Detection Using Si-Doped MoS2 Channel-Based Thickness Engineered TFET Biosensor 利用基于硅掺杂 MoS2 沟道厚度设计的 TFET 生物传感器检测乳腺癌

IF 2.2

IEEE Sensors Letters Pub Date : 2024-08-06 DOI: 10.1109/LSENS.2024.3438872

Priya Kaushal;Gargi Khanna

{"title":"Breast Cancer Detection Using Si-Doped MoS2 Channel-Based Thickness Engineered TFET Biosensor","authors":"Priya Kaushal;Gargi Khanna","doi":"10.1109/LSENS.2024.3438872","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3438872","url":null,"abstract":"This letter investigates the electrical performance characteristics for breast cancer cell line detection by developing the Si-doped molybdenum disulfide thickness engineered tunnel field effect transistor biosensor. A complete study of the electrostatic field is presented, including the surface potential, electric field, transconductance (g\u0000m\u0000), threshold voltage (V\u0000th\u0000), \u0000<sc>on\u0000 current (I\u0000ON\u0000), and subthreshold swing. The sensitivity is analyzed in terms of drain current (I\u0000ds\u0000), g\u0000m\u0000, V\u0000th\u0000, I\u0000ON\u0000, I\u0000ON\u0000/I\u0000OFF\u0000 ratio, and g\u0000m\u0000. Further, this study investigates the impact of device geometry variations, specifically cavity thickness, and length on the sensitivity of drain current (\u0000<inline-formula><tex-math>$text{S}_{rm{I}_{rm{ds}}}$</tex-math></inline-formula>\u0000), transconductance (\u0000<inline-formula><tex-math>$text{S}_{rm{g}_{rm{m}}}$</tex-math></inline-formula>\u0000 ), threshold voltage (\u0000<inline-formula><tex-math>${text{S}}_{{{rm{V}}_{{rm{th}}}}}$</tex-math></inline-formula>\u0000), and \u0000<sc>on\u0000 current (\u0000<inline-formula><tex-math>${text{S}}_{{{rm{I}}_{{rm{ON}}}}}$</tex-math></inline-formula>\u0000). In addition, the impact of immobilized cell line occupancy on device performance has been examined. The presented biosensor is highly sensitive with increased cavity occupancy resulting in enhanced performance. As a result, array-based screening and diagnosis of breast cancer cells can be accomplished with the device, which is also economical and simpler to fabricate.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142084485","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

Design and Implementation of an IoT Acoustic-Controlled Pillow for Sleep Health Monitoring 设计和实现用于睡眠健康监测的物联网声控枕头

IF 2.2

IEEE Sensors Letters Pub Date : 2024-08-06 DOI: 10.1109/LSENS.2024.3439259

Jason K. Liao;Chun Yin Lai;Chetwyn Che Hin Chan;Steve W. Y. Mung

引用次数: 0

Thin Film Reconfigurable Intelligent Surface for Harmonic Beam Steering 用于谐波光束转向的薄膜可重构智能表面

IF 2.2

IEEE Sensors Letters Pub Date : 2024-08-05 DOI: 10.1109/LSENS.2024.3438458

Boxuan Xie;Aleksandr D. Kuznetsov;Lauri Mela;Jari Lietzén;Kalle Ruttik;Alp Karakoç;Riku Jäntti

引用次数: 0

Factor Graph Optimization Enhanced Pedestrian Dead Reckoning With Dual-Foot-Mounted IMUs 因子图优化增强了双脚安装 IMU 的行人惯性导航功能

IF 2.2

IEEE Sensors Letters Pub Date : 2024-08-02 DOI: 10.1109/LSENS.2024.3436929

Jie Dou;Fen Hu;Lei Dou

引用次数: 0

Optimizing Glucose Sensor Calibration With Lightweight Neural Networks: A Comparative Study 利用轻量级神经网络优化葡萄糖传感器校准：比较研究

IF 2.2

IEEE Sensors Letters Pub Date : 2024-08-02 DOI: 10.1109/LSENS.2024.3436630

Costanza Cenerini;Anna Sabatini;Luca Vollero;Danilo Pau

{"title":"Optimizing Glucose Sensor Calibration With Lightweight Neural Networks: A Comparative Study","authors":"Costanza Cenerini;Anna Sabatini;Luca Vollero;Danilo Pau","doi":"10.1109/LSENS.2024.3436630","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3436630","url":null,"abstract":"Diabetes presents a significant global health challenge, necessitating precise blood glucose monitoring for effective management. Continuous glucose monitoring (CGM) devices offer a minimally invasive approach, yet require accurate calibration models to improve reliability. This letter investigates various neural network architectures for predicting time errors in CGM sensor readings, aiming for high accuracy and minimal computational burden. Using simulated data, models were trained and evaluated, with Legendre memory unit and temporal convolutional network architectures emerging as promising candidates. With these architectures, it was possible to lower the sensor's reading error to, respectively, 24.22 and 25.34 mg/dL, decreasing the error by 40.6% and 37.9%. Furthermore, the letter explores the impact of sensor calibration frequency on prediction accuracy, revealing optimal performance with calibrations once every three or five days, obtaining an error in the reading of approximately 16 and 15 mg/dL. These findings underscore the potential for enhancing glucose monitoring systems and suggest avenues for future research in diabetes management.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013414","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

Label-Free EGFR Sensing by Using a Flexible IrOx Extended-Gate Field-Effect Transistor-Based Biosensor 利用基于柔性氧化铁扩展栅极场效应晶体管的生物传感器进行无标记表皮生长因子受体传感

IF 2.2

IEEE Sensors Letters Pub Date : 2024-07-31 DOI: 10.1109/LSENS.2024.3436106

Kanishk Singh;Chao-Hung Chen;Li-Chia Tai;Wei-Chen Huang;Tung-Ming Pan

{"title":"Label-Free EGFR Sensing by Using a Flexible IrOx Extended-Gate Field-Effect Transistor-Based Biosensor","authors":"Kanishk Singh;Chao-Hung Chen;Li-Chia Tai;Wei-Chen Huang;Tung-Ming Pan","doi":"10.1109/LSENS.2024.3436106","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3436106","url":null,"abstract":"In this research work, we present a flexible iridium oxide (IrO\u0000<italic>x\u0000) extended-gate field-effect transistor (EGFET) biosensor for label-free detection of the epidermal growth factor receptor (EGFR) biomarker. IrO\u0000<italic>x\u0000 was employed as the sensing membrane material due to its excellent electrochemical properties, high conductivity, stability, biocompatibility, and ability to facilitate redox reactions. The IrO\u0000<italic>x\u0000 film was deposited on a flexible polyimide (PI) substrate through a sol–gel process and characterized using atomic force microscopy and X-ray photoelectron spectroscopy. As a pH sensor, the IrO\u0000<italic>x\u0000 EGFET exhibited a super-Nernstian sensitivity of 68.54 mV/pH with high linearity, a low hysteresis of ∼ 6 mV, and a drift rate of 0.50 mV/h at pH 7 over 12 h. For EGFR detection, the IrO\u0000<italic>x\u0000 surface was functionalized with 3-aminopropyltriethoxysilane and glutaraldehyde to immobilize anti-EGFR antibodies. The EGFR sensor demonstrated a wide linear detection range from 1 to 1000 ng/mL with a sensitivity of 11.78 mV/log(ng/mL) and a linearity of 99.8%, making it suitable for clinical EGFR monitoring in cancer patients. The flexible IrO\u0000<italic>x\u0000 EGFET shows promise for reliable label-free detection of EGFR.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141973519","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

Monocular Visual-Inertial SLAM With IMU-Aided Hybrid Line Matching 利用 IMU 辅助混合线匹配的单目视觉惯性 SLAM

IF 2.2

IEEE Sensors Letters Pub Date : 2024-07-31 DOI: 10.1109/LSENS.2024.3435988

Gongpu Zha;Peiyu Guan;Zhiqiang Cao;Ting Sun;Shijie Yu

{"title":"Monocular Visual-Inertial SLAM With IMU-Aided Hybrid Line Matching","authors":"Gongpu Zha;Peiyu Guan;Zhiqiang Cao;Ting Sun;Shijie Yu","doi":"10.1109/LSENS.2024.3435988","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3435988","url":null,"abstract":"Multisensor fusion simultaneous localization and mapping (SLAM) has gained popularity in the SLAM community due to its low cost and high real-time performance. Common point-feature-based visual-inertial SLAM systems often struggle in environments with weak textures or motion blur. By incorporating line features, the accuracy and robustness of SLAM systems can be improved. However, challenges in line matching and increased processing time caused by line features have limited these improvements. To address the problem, we introduce a real-time monocular visual-inertial SLAM method with inertial measurement unit (IMU)-aided hybrid line matching, where the hybrid lines consist of elementary and recessive lines. Specifically, an IMU-aided hybrid line matching scheme is designed to determine the search space of line matching according to the IMU preintegration result. It scales down the search range effectively and thus improves the accuracy and speed of line matching. Also, an improved enhanced line segment drawing (iELSED) algorithm is utilized for efficient elementary line feature extraction, where the parameters of line features are adaptively adjusted with the number of extracted point features to avoid feature redundancy. In addition, we also extend the point-based loop-closure detection by introducing line features for higher accuracy of loop-closure detection. Experiment results demonstrate the effectiveness of the proposed method.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013200","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 Efficient Ensemble Framework for Human Gait Recognition Using CNN-LSTM With Extra Tree Classifier and Smartphone Sensors in Real-World Environment 在真实世界环境中使用带有额外树分类器的 CNN-LSTM 和智能手机传感器进行人体步态识别的高效集合框架

IF 2.2

IEEE Sensors Letters Pub Date : 2024-07-30 DOI: 10.1109/LSENS.2024.3435719

Nurul Amin Choudhury;Sakshi Singh;Badal Soni

{"title":"An Efficient Ensemble Framework for Human Gait Recognition Using CNN-LSTM With Extra Tree Classifier and Smartphone Sensors in Real-World Environment","authors":"Nurul Amin Choudhury;Sakshi Singh;Badal Soni","doi":"10.1109/LSENS.2024.3435719","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3435719","url":null,"abstract":"Gait recognition is a biometric technology that identifies individuals based on their unique way of walking. Most of the work on human gait recognition (HGR) systems has minimal user records and is performed in a closed simulated environment, which hampers the performance in a real-world scenario. This letter presents an efficient ensemble framework using a hybrid deep learning network (convolutional neural network-long short-term memory) with an extra tree classifier (ETC) for HGR in a real-world environment. The proposed model effectively extracts low-level spatial and temporal features from the sensor data for meaningful pattern generation and classifies them using multiple decision trees present in the ensemble ETC. A State-of-the-Art HGR dataset has also been developed for a diverse set of users in uncontrolled environments in real-world environments using built-in smartphone sensors. The proposed model achieved an average performance accuracy of 99.10% and optimal precision, recall, and F1-score, outperforming all the benchmark models with optimal performance margins in lower computational times.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966294","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