IEEE Sensors Journal最新文献_第8页

Transmission Map-Guided Joint Source-Channel Coding for Underwater Semantic Communication

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3542396

Simeng Cheng;Zhigang Jin;Lixiang Chang;Jiawei Liang;Haoyong Li;Yishan Su;Gen Li

{"title":"Transmission Map-Guided Joint Source-Channel Coding for Underwater Semantic Communication","authors":"Simeng Cheng;Zhigang Jin;Lixiang Chang;Jiawei Liang;Haoyong Li;Yishan Su;Gen Li","doi":"10.1109/JSEN.2025.3542396","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3542396","url":null,"abstract":"Joint source-channel coding (JSCC) for semantic communication (SemCom) has achieved significant progress. However, due to the degradation of underwater images, directly using JSCC for underwater SemCom leads to inadequate semantic extraction. To this end, this article proposes a transmission map-guided JSCC (TGJSCC) for underwater SemCom to better extract and transmit the semantic information of underwater degradation images, called TGJSCC. Specifically, we design the TGJSCC encoder to extract abundant semantic information of underwater degraded images. TGJSCC encoder first uses the transmission map generated by the underwater imaging model to help JSCC locate the focal regions in underwater degraded images, and then computes the global information in the latent space to obtain abundant semantic information. To transmit semantic information over the limited underwater channel, the semantic importance compression module (SICM) is proposed to compress semantic information while retaining useful information. Finally, the TGJSCC decoder is designed to reconstruct raw underwater degraded images from the semantic information transmitted by the underwater channel. The experimental results and analysis demonstrate that compared with the traditional separation source-channel coding (SSCC) methods and JSCC methods, the underwater SemCom based on TGJSCC not only extracts abundant semantic information of underwater degradation images, but also recovers the high-precision images.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"12198-12209"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748886","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}

引用次数: 0

A High-Performance Directional Strain Sensor Using Kirigami and Corrugated Structures for Real-Time Knee Joint Movement Detection

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3541672

Chiranjit Das;Guo-Hua Feng

{"title":"A High-Performance Directional Strain Sensor Using Kirigami and Corrugated Structures for Real-Time Knee Joint Movement Detection","authors":"Chiranjit Das;Guo-Hua Feng","doi":"10.1109/JSEN.2025.3541672","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3541672","url":null,"abstract":"This article presents the development and application of a flexible directional strain sensor designed using a combination of kirigami and corrugated structures to improve stretchability, sensitivity, and mechanical robustness. The sensor is embedded in a self-adhesive silicone elastomer, enabling reliable skin contact. It uses piezoelectric lead zirconate titanate (PZT) layers grown using a hydrothermal process, verified by X-ray diffraction (XRD) and polarization-electric field (P–E) curve analysis. We conducted extensive fundamental testing and assessed knee motion during squatting, standing, and knee bending cycles in lying-down status. The results showed that the sensor responded accurately to different stress levels, with accurate multidirectional and low cross-axis sensitivity. The reliability of the sensor was established in a 1000-cycle durability test. Notably, under the same bending angle of the leg, the larger signal was obtained for the motion from squatting to standing with increased knee joint loading compared to the leg outward folding motion in lying-down status. This innovative sensor has great potential for wearable health monitoring, motion tracking, and robotic systems, enabling reliable, real-time stress detection.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"10775-10783"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761362","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}

引用次数: 0

A Highly Sensitive Iontronic Pressure Sensor for High-Pressure Range Monitoring

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3541697

Shu Wan;Peng Wan;Shen Li;Junju Wang;Haizhou Huang;Ji Jin;Shunbo Li;Xuefeng He;Shi Su;Hengchang Bi;Yizhou Ye

{"title":"A Highly Sensitive Iontronic Pressure Sensor for High-Pressure Range Monitoring","authors":"Shu Wan;Peng Wan;Shen Li;Junju Wang;Haizhou Huang;Ji Jin;Shunbo Li;Xuefeng He;Shi Su;Hengchang Bi;Yizhou Ye","doi":"10.1109/JSEN.2025.3541697","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3541697","url":null,"abstract":"Flexible pressure sensors with high performance are in high demand for applications in electronic skin, human-machine interfaces, and health monitoring. A promising method to enhance the sensitivity of capacitive pressure sensors is the incorporation of ionic soft materials with microstructured designs in the functional layer. These structures enhance the capacitance signal by generating an electron double layer, thereby increasing sensor sensitivity. However, while microstructured ionic piezocapacitive sensors exhibit exceptional sensitivity in low-pressure regimes (<10>200 kPa) due to the stiffening of the microstructures. In addition, the complex fabrication processes and the need for specialized equipment to create these microstructures result in high costs and low production efficiency. Here, we present a simple and cost-effective method for integrating an ionic hydrogel and separator into a pressure sensor. By sandwiching a porous polytetrafluoroethylene (PTFE) membrane between two layers of polyacrylamide (PAAm) hydrogel containing NaCl, the sensor achieves remarkable sensitivity—up to 977.8 kPa−1—at high pressures (>200 kPa). Furthermore, the PAAm-NaCl hydrogel-based sensor demonstrates a fast response time of ~100 ms and exceptional mechanical stability, enduring 1000 compression-release cycles. This approach offers a straightforward strategy for the mass production of highly sensitive pressure sensors. We also highlight the potential of these devices to detect subtle mechanical stimuli under high baseline pressures, such as monitoring pressure distribution during postural changes when a person shifts the standing position.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"10766-10774"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761544","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}

引用次数: 0

SitPose: Real-Time Detection of Sitting Posture and Sedentary Behavior Using Ensemble Learning With Depth Sensor

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3541821

Hang Jin;Xin He;Lingyun Wang;Yujun Zhu;Weiwei Jiang;Xiaobo Zhou

{"title":"SitPose: Real-Time Detection of Sitting Posture and Sedentary Behavior Using Ensemble Learning With Depth Sensor","authors":"Hang Jin;Xin He;Lingyun Wang;Yujun Zhu;Weiwei Jiang;Xiaobo Zhou","doi":"10.1109/JSEN.2025.3541821","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3541821","url":null,"abstract":"Poor sitting posture can lead to various work-related musculoskeletal disorders (WMSDs). Office employees spend approximately 81.8% of their working time seated, and sedentary behavior can result in chronic diseases such as cervical spondylosis and cardiovascular diseases. To address these health concerns, we present SitPose, a sitting posture and sedentary detection system utilizing the latest Kinect depth camera. The system tracks 3-D coordinates of bone joint points in real-time and calculates the angle values of related joints. We established a dataset containing six different sitting postures and one standing posture, totaling 33409 data points, by recruiting 36 participants. We applied several state-of-the-art machine learning algorithms to the dataset and compared their performance in recognizing the sitting poses. Our results show that the ensemble learning model based on the soft voting mechanism achieves the highest <inline-formula> <tex-math>$F_{1}$ </tex-math></inline-formula> score of 98.1%. Finally, we deployed the SitPose system based on this ensemble model to encourage better sitting posture and to reduce sedentary habits.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"12444-12454"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748810","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}

引用次数: 0

Comparative Evaluation of Flexible and Rigid Dry Electrodes Versus Gel Electrodes for Reliable ECG Monitoring in Android Wearable Smart Garment

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3537016

Nacera Meziane;Merouane Bouzid;Dalila Meziane;Malika Kedir-Talha

{"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}

引用次数: 0

A NTRU-Based Data Deduplication Scheme for Underwater Acoustic Sensor Networks

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3542506

Ming Xu;Tongtong Guo

{"title":"A NTRU-Based Data Deduplication Scheme for Underwater Acoustic Sensor Networks","authors":"Ming Xu;Tongtong Guo","doi":"10.1109/JSEN.2025.3542506","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3542506","url":null,"abstract":"Data security and storage capacity have become more important as a result of the extensive use of underwater acoustic sensor networks (UWSNs) in fields including military applications, national defense, and marine resource research. To maintain data security while cutting costs associated with transmission and storage, we propose a number theory research unit (NTRU)-based data deduplication strategy for UWSNs, coined as NTRU-based data deduplication scheme for underwater acoustic sensor networks (NTDP). The NTDP scheme is novel in three aspects. First, a novel encryption scheme is proposed to ensure data security and privacy by utilizing primitive vectors, combined with NTRU multi-key fully homomorphic encryption and certificateless signatures in an underwater resource-constrained environment. Second, we propose a dynamic partitioning algorithm, which can identify repetitions within preprocessed data blocks so as to effectively achieve data deduplication. Third but not least, the NTDP scheme embeds a secure proof of ownership (PoW) protocol to ensure semantic security, enabling surface relay devices to claim data ownership without disclosing the actual data content, thus improving the level of data privacy protection. Extensive experimental results show that the NTDP scheme effectively enhances data transmission security and improves data storage efficiency in UWSNs.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"12210-12221"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748955","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}

引用次数: 0

Detection Model for Automatic Defect Quantification and Segmentation for Stepped Eddy Current Thermography

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3542091

Yuan Gao;Liang Zhang;Zheng Liang;Ting Zheng;Xiong Deng;Xin Chen

{"title":"Detection Model for Automatic Defect Quantification and Segmentation for Stepped Eddy Current Thermography","authors":"Yuan Gao;Liang Zhang;Zheng Liang;Ting Zheng;Xiong Deng;Xin Chen","doi":"10.1109/JSEN.2025.3542091","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3542091","url":null,"abstract":"The stepped eddy current thermography (SECT) nondestructive testing (NDT) technique is characterized by long heating time and nonuniform temperature rise. This causes it to remain challenging to quantify the geometrical features of defects on the inner wall of the tank roof and the outer wall of the tank bottom in oil and gas storage tanks. This article proposes a combined model for compressing and reconstructing thermal image sequences: the skewness model combined with the improved Gaussian adaptive background estimation algorithm (SM-IGABEA) for quantifying the defect morphology. The combined model is coupled with the first-order differential max-min method to quantify the width and height of defects accurately. The combined model combined with the first-order differential mean method can accurately segment defects. A mathematical model for predicting the residual depth (RD) of steel plates is developed to describe the relationship between the geometric characteristics of defects and the mean value of skewness. Finally, the generalization of SM-IGABEA is verified by elliptical defects. The results show that various combinatorial models and quantization methods are proposed for the defect measurement task. The measurement accuracy and stability of SM-IGABEA significantly outperform the mainstream compressive reconstruction algorithms.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"10784-10799"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761359","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}

引用次数: 0

Heart Murmur and Abnormal PCG Detection via Wavelet Scattering Transform and 1D-CNN

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3541320

Ahmed Patwa;Muhammad Mahboob Ur Rahman;Tareq Y. Al-Naffouri

{"title":"Heart Murmur and Abnormal PCG Detection via Wavelet Scattering Transform and 1D-CNN","authors":"Ahmed Patwa;Muhammad Mahboob Ur Rahman;Tareq Y. Al-Naffouri","doi":"10.1109/JSEN.2025.3541320","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3541320","url":null,"abstract":"Congenital heart disease (CHD) is the most common type of congenital anomaly, with an estimated prevalence of 8–12 per 1000 live births. CHD results in heart murmurs, which once listened to provide valuable information about mechanical activity of the heart and aid in diagnosis of CHD and other heart valve diseases (HVDs). This work does automatic and accurate heart murmur detection from phonocardiogram (PCG) recordings. Two publicly available PCG datasets from PhysioNet online database are utilized to train and test various custom neural networks (NNs). We first do preprocessing which includes the following key steps: denoising, segmentation, relabeling of noise-only segments, data normalization, and time-frequency analysis of the PCG segments using wavelet scattering transform (WST), mel-frequency cepstral coefficients (MFCCs), and short-time Fourier transform (STFT). We then conduct four experiments, first three (E1–E3) using first dataset, and fourth (E4) using second dataset. It turns out that our custom 1-D convolutional neural network (1D-CNN) with wavelet scattering outperforms all other models. Furthermore, the vanilla 1D-CNN model (with wavelet scattering) outperforms the related work in terms of weighted accuracy, precision, and specificity, for experiment E3. As for experiment E1, our model performs quite close to top-performing work in terms of weighted accuracy, outperforms related works in terms of precision and is on par with the related works in terms of <inline-formula> <tex-math>${F}1$ </tex-math></inline-formula>-score.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"12430-12443"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748796","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}

引用次数: 0

Synthetic Aperture Positioning Using Subaperture Interference

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3532670

Xing Liu;Hao Huan;Ran Tao

引用次数: 0

High-Sensitivity MEMS Ethanol Gas Sensors Based on Laser-Machined Glass Substrates and Electrospun p-NiO Doped n-V₂O₅ Nanofibers

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-02-24 DOI: 10.1109/JSEN.2025.3542249

Wei-Hsiang Liao;Zhen-Jie Huang;Yen-Liang Pan;Cheng-Liang Hsu

{"title":"High-Sensitivity MEMS Ethanol Gas Sensors Based on Laser-Machined Glass Substrates and Electrospun p-NiO Doped n-V₂O₅ Nanofibers","authors":"Wei-Hsiang Liao;Zhen-Jie Huang;Yen-Liang Pan;Cheng-Liang Hsu","doi":"10.1109/JSEN.2025.3542249","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3542249","url":null,"abstract":"Nickel-doped V2O5 nanofibers (NiO-V2O5 NFs) were synthesized using electrospinning and integrated onto glass substrates with microelectro mechanical systems (MEMSs) structures. By utilizing UV laser processing, a rapid fabrication of microheaters and interdigitated electrodes (IDEs) was achieved, significantly reducing production time to 1.2 s per MEMS component. Before integrating the material with the MEMS structure, the sensor demonstrated a gas response of 722.6% for 500 ppm ethanol gas at 350 °C, with a reaction time of 48 s, a recovery time of 49 s, and a detection limit of 300 ppb. After combining the NFs with the MEMS structure, the detection limit was improved to 100 ppb, and for 200 ppm ethanol gas at 350 °C, the reaction time and recovery time were 28 and 156 s, respectively. The MEMS structure, fabricated using UV laser machining on a Pt-coated glass substrate, enabled precise and efficient integration of sensing and heating elements. The sensor demonstrated excellent selectivity toward ethanol gas, with a response significantly higher than that for isopropanol and acetone, as well as superior sensitivity, repeatability, and stability across a range of operating temperatures. These findings highlight the potential of this approach for scalable, high-performance ethanol gas detection, and applications in optoelectronic devices.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"10594-10601"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748966","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}

引用次数: 0