IEEE Sensors Letters最新文献_第8页

IDMatchHAR: Semi-Supervised Learning for Sensor-Based Human Activity Recognition Using Pretraining 使用预训练的基于传感器的人类活动识别的半监督学习

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-03 DOI: 10.1109/LSENS.2025.3546985

Koki Takenaka;Shunsuke Sakai;Tatsuhito Hasegawa

{"title":"IDMatchHAR: Semi-Supervised Learning for Sensor-Based Human Activity Recognition Using Pretraining","authors":"Koki Takenaka;Shunsuke Sakai;Tatsuhito Hasegawa","doi":"10.1109/LSENS.2025.3546985","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3546985","url":null,"abstract":"In sensor-based human activity recognition (HAR), the annotation cost for sensor data is higher compared to data, such as images. One can use semisupervised learning (semi-SL) to reduce annotation costs. This method lever-ages unlabeled datasets by assigning pseudolabels. How- ever, these methods have the issue of confirmation bias, where performance degrades due to incorrect pseudolabels. Some approaches have attempted to solve this problem by performing multistage pretraining with labeled and unlabeled data, but these methods require significant computational resources. We propose a framework called IDMatchHAR, which performs semi-SL with a single-stage pretraining process on small-scale datasets. We use instance discrimination (ID) during pretraining to learn robust feature representations applied to the subsequent semi-SL task. We verify the effectiveness of the proposed framework using various convolutional neural networks (CNNs), such as VGG and residual network (ResNet), as well as Transformers, on HASC, WISDM, and Pamap2. Our proposed framework significantly reduces the computational cost of pretraining while demonstrating performance comparable to or exceeding that of existing semi-SL 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":"143645167","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

Modal Analysis of Structures Using a Millimeter-Wave Sensor 基于毫米波传感器的结构模态分析

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-02 DOI: 10.1109/LSENS.2025.3566456

Yudai Matsue;Jun Kuroda;Yuu Kashima;Satoshi Kawaji;Satoshi Yamada;Tomonori Nagayama;Jun Iyama

{"title":"Modal Analysis of Structures Using a Millimeter-Wave Sensor","authors":"Yudai Matsue;Jun Kuroda;Yuu Kashima;Satoshi Kawaji;Satoshi Yamada;Tomonori Nagayama;Jun Iyama","doi":"10.1109/LSENS.2025.3566456","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3566456","url":null,"abstract":"Millimeter-wave (mmWave) sensors are being actively researched and developed for sensing vibrations in construction, infrastructure, and machinery. Moreover, vibration modal analysis, including mode shape identification, is used to detect structural deterioration. This study examines the feasibility of vibration modal analysis using mmWave sensors. The laser Doppler vibrometer (LDV) and camera-based methods are often used as a noncontact vibration sensor for vibration modal analysis. Compared to these methods, mmWave sensors are less expensive and easier to miniaturize; however, they have a low spatial resolution. This study experimentally verifies the potential to use mmWave sensors for modal analysis, including mode shape identification, under the condition that the reflection response can be narrowed down to a single point by considering the surface reflectivity of the object. An aluminum alloy plate was excited sinusoidally at specific frequencies. A mmWave sensor and an LDV, as a reference, were used to measure the vibrations of the specimen at multiple points by changing their positions. The root mean square error for all points was at most 2.2 µm against a maximum displacement of 67.5 µm, confirming that vibration modes were measured accurately using mmWave sensors under appropriate conditions.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 6","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949226","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

Highly Efficient Room Temperature DMA and TMA Sensor Based on MoS2–ZnO Hybrid Channel FET Device 基于MoS2-ZnO混合通道场效应管器件的高效室温DMA和TMA传感器

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-01 DOI: 10.1109/LSENS.2025.3565135

Ranita Halder;Anjali Patel;Bikramdeb Chakraborty;Indrajit Sil;Partha Bhattacharyya

{"title":"Highly Efficient Room Temperature DMA and TMA Sensor Based on MoS2–ZnO Hybrid Channel FET Device","authors":"Ranita Halder;Anjali Patel;Bikramdeb Chakraborty;Indrajit Sil;Partha Bhattacharyya","doi":"10.1109/LSENS.2025.3565135","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3565135","url":null,"abstract":"In this letter, a back-gated field effect transistor (FET) sensor with MoS2–ZnO hybrid channel is reported for efficient detection of dimethylamine (DMA) and trimethylamine (TMA) vapors, the two primary amines that are primary bio-indicators for many applications, such as quality monitoring of freshness of fish, biomarker for couple of diseases, such as nonalcoholic fatty liver disease (NAFLD), renal disorder, etc. Compared to the state of the art, the developed sensor offered three distinct advantages: i) this is the first report of DMA, TMA detection with FET device employing MoS2–ZnO hybrid channel offering fast response and recovery; ii) the ability to detect the target species at room temperature owing to very high free surface energy associated with the hybrid channel region; iii) improved lowest detection level (0.5 ppm for DMA and 1 ppm for TMA) due to excessively high surface to volume ratio. The underlying mechanistic framework for such superior performance was primarily attributed to the judicious choice of the channel material coupled with device architecture. Formation of the p-n junction (p-MoS2 and n-ZnO) in the channel region and the associated charge separation assisted field generation therein leads to easy dissociation of target vapor species (low operating temperature and improved lowest detection level), while the majority carrier-driven fast charge transport in the channel region causes fast response and recovery in such FET device.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 6","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073258","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

Study of Low-Area PV Modules Under Indoor Natural Daylight for Autonomous Sensors 自主传感器室内自然光下低面积光伏组件的研究

IF 2.2

IEEE Sensors Letters Pub Date : 2025-03-01 DOI: 10.1109/LSENS.2025.3566120

Ferran Reverter

引用次数: 0

A Charge Balanced Stimulators With a Twin Compensation Loop for Evoked Neural Potential Sensing 一种用于诱发神经电位感应的双补偿回路电荷平衡刺激器

IF 2.2

IEEE Sensors Letters Pub Date : 2025-02-28 DOI: 10.1109/LSENS.2025.3546239

Longbin Zhu;Wenjie Wang;Risheng Su;Zhijun Zhou;Keping Wang

{"title":"A Charge Balanced Stimulators With a Twin Compensation Loop for Evoked Neural Potential Sensing","authors":"Longbin Zhu;Wenjie Wang;Risheng Su;Zhijun Zhou;Keping Wang","doi":"10.1109/LSENS.2025.3546239","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3546239","url":null,"abstract":"Neurological functional electrical stimulation (NFES) provides a well-controlled and high degree of reconfigurability amount for producing the desired stimulation effect. For evaluating the effect of stimulation, the evoked potentials can be sensed. However, in practice, the unbalanced charge accumulation leads to residual charges and toxic electrochemical reactions at the electrode-tissue sensing interface, which causes electrode corrosion and tissue damage. This letter presents a twin compensation loop (TCL) charge-balancing (CB) topology for the NFES. The TCL-CB consists of two compensation loops, including a positive compensation loop (PCL) and a negative compensation loop (NCL). The PCL and NCL continuously detect and compensate for the accumulated negative and positive charges at the output of the Wilson current mirror (WSC), respectively. The circuits are targeted at integrated circuit (IC) realization, designed and fabricated in a 0.18-<italic>μm complementary metal oxide semiconductor (CMOS) technology. The power consumption of the WSC with TCL-CB is circa 79.2 μW and occupies a die area of 0.047 mm2 (0.265 μm × 0.18 μm). Benefiting from TCL-CB, the charge mismatch at the output of WSC is reduced to less than 1%.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645302","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

Optimal Load Type for Passive Magnetic Energy Harvesters 无源磁能采集器的最佳负载类型

IF 2.2

IEEE Sensors Letters Pub Date : 2025-02-27 DOI: 10.1109/LSENS.2025.3546246

Alon Kuperman

引用次数: 0

Strain Measurement Validation of a Spherical Pressure Hull for Human Occupied Vehicle Using Rosette Strain Gauge 玫瑰花应变计用于载人车辆球形耐压壳体应变测量的验证

IF 2.2

IEEE Sensors Letters Pub Date : 2025-02-27 DOI: 10.1109/LSENS.2025.3546218

R. Ramesh;S. B. Pranesh;V. Bala Naga Jyothi;T. Sasikala;A. Vadivelan

{"title":"Strain Measurement Validation of a Spherical Pressure Hull for Human Occupied Vehicle Using Rosette Strain Gauge","authors":"R. Ramesh;S. B. Pranesh;V. Bala Naga Jyothi;T. Sasikala;A. Vadivelan","doi":"10.1109/LSENS.2025.3546218","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3546218","url":null,"abstract":"The deep-water human-occupied vehicle (HOV) MATSYA 6000 is being developed by the National Institute of Ocean Technology, Ministry of Earth Sciences, Government of India, to carry three humans up to a depth of 6000 m for deep ocean scientific exploration and research. As this underwater vehicle is man-rated, the safety and reliability of the spherical pressure hull are significant as the structure is subjected to extremely high pressures at higher depths. A spherical pressure hull of 2.1 m diameter is designed and manufactured indigenously to carry three humans up to a depth of 500 m. In this letter, triaxial strain measurements are carried out using the Rosette strain gauge at different welded locations inside the spherical pressure hull. The proposed methodology shall be used for human-rated subsea applications, which give insight and compliance in designing the human-rated systems with finite element analysis studies. The spherical pressure hull has been tested three times in the open sea at 606 m depth for a 60-min period in the Bay of Bengal. The results obtained from analysis and measurements observed from the external pressure test at open sea are comparable, and the error is less than ∼9%.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818040","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

Localization of RFID Tags Through Real-Time Angle-of-Arrival Estimation 基于实时到达角估计的RFID标签定位

IF 2.2

IEEE Sensors Letters Pub Date : 2025-02-26 DOI: 10.1109/LSENS.2025.3546092

Antonello Florio;Gianfranco Avitabile;Giuseppe Coviello

引用次数: 0

A Lightweight Causal Sound Separation Model for Real-Time Hearing Aid Applications 用于实时助听器应用的轻量级因果音分离模型

IF 2.2

IEEE Sensors Letters Pub Date : 2025-02-26 DOI: 10.1109/LSENS.2025.3546132

Harsh Mishra;Mahendra K. Shukla;Priyanshu;Som Dengre;Yashveer Singh;Om Jee Pandey

引用次数: 0

Smoothing Objective Function for 3-D Electrical Resistivity Inversion by CNNs Regularizer cnn正则化器三维电阻率反演的平滑目标函数

IF 2.2

IEEE Sensors Letters Pub Date : 2025-02-24 DOI: 10.1109/LSENS.2025.3544577

Peng Jiang;Shengjie Qiao;Yonghao Pang;Yongheng Zhang;Zhengyu Liu

{"title":"Smoothing Objective Function for 3-D Electrical Resistivity Inversion by CNNs Regularizer","authors":"Peng Jiang;Shengjie Qiao;Yonghao Pang;Yongheng Zhang;Zhengyu Liu","doi":"10.1109/LSENS.2025.3544577","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3544577","url":null,"abstract":"In tunnel geological forecasting, the electrical resistivity inversion method is extensively employed due to its high sensitivity to water-bearing bodies. Traditional inversion methods, such as least squares, simplify nonlinear problems into linear ones. However, they often converge to local minima, making it challenging to identify the global optimal solution, and their inversion results are highly dependent on the choice of the initial model. To address these challenges, we propose integrating convolutional neural networks (CNNs) into the conventional iterative inversion framework. Instead of directly optimizing the initial resistivity model, our approach focuses on updating the network parameters, with the resistivity model subsequently generated by the CNN. This enables the CNN structure to regularize the resistivity model, resulting in a smoother objective function. Consequently, our method exhibits greater robustness to variations in the initial model, leading to improved inversion results. Our numerical simulations and practical applications in engineering projects demonstrate that, compared to traditional inversion methods, the proposed approach is less sensitive to the initial model and achieves superior inversion outcomes, thereby validating our hypothesis.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 4","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611907","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