IEEE Sensors Letters最新文献

{"title":"Tunable BTEX Gas Detection At Room Temperature via Composition Engineered MoSe$_{2}$–WSe$_{2}$ Nanocomposites","authors":"Priyakshi Kalita;Abhik Chanda;Orison Waikhom;Biplob Mondal","doi":"10.1109/LSENS.2025.3595417","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3595417","url":null,"abstract":"The detection of hazardous volatile organic compounds, particularly benzene, toluene, ethylbenzene, and xylene (BTEX), is crucial due to their carcinogenic nature and contribution to environmental pollution. Conventional gas sensors often suffer from high operating temperatures, poor sensitivity and selectivity, and slow response times. To address these limitations, composition-tunable MoSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>–WSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula> heterostructures were synthesized via a facile liquid-phase exfoliation (LPE) technique for room-temperature BTEX sensing applications. A comparative investigation was conducted between two distinct compositional ratios: MoSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>:WSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula> = 3:1 (n-type dominant) and 1:3 (p-type dominant), to elucidate the role of composition on electrical and sensing behavior. The structural, morphological, and optical properties of the synthesized composites were comprehensively characterized using Raman spectroscopy, FESEM, EDX, XRD, and UV–Vis spectroscopy. The 3:1 sample exhibited dominant MoSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula> Raman features with an estimated bandgap of 1.78 eV, whereas the 1:3 sample showed dominant WSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula> features with a bandgap of 1.47 eV. Elemental analysis further validated the targeted Mo:W atomic ratios, closely matching the intended 3:1 and 1:3 compositions. Electrical measurements demonstrated a maximum sensor response of 25.74% toward benzene, with a rapid response time of 30 s at a gas concentration of 50 ppm for MoSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>–WSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula> composite (1:3). This study provides the first detailed report on composition-dependent BTEX sensing performance of MoSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>–WSe<inline-formula><tex-math>$_{2}$</tex-math></inline-formula> heterostructures synthesized via LPE. The findings highlight the critical influence of n-/p-type dominance tuning for achieving gas-specific selectivity, offering promising pathways for the development of next-generation, room-temperature, 2D-material-based gas sensors with tailored sensitivity profiles.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887535","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}

{"title":"Vessel-SAM2: Adapting Segment Anything 2 for Patch-Free Retinal Vessel Segmentation in Ultra-High Resolution Fundus Images","authors":"Zihuang Wu;Xinyu Xiong","doi":"10.1109/LSENS.2025.3595139","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3595139","url":null,"abstract":"Accurate automatic segmentation of blood vessels in ophthalmic images is crucial for the early diagnosis of many diseases. These images are typically high-resolution and contain intricate details of fine terminal vessels. However, most existing deep learning methods operate on lower resolutions, which limits their segmentation accuracy. Learning directly from high-resolution images faces significant challenges, as the computational overhead required by existing complex segmentation decoders can be impractical. To address these challenges, we propose Vessel-SAM2, a retinal vessel segmentation network based on Segment Anything 2 (SAM2), capable of performing end-to-end segmentation at an ultra-high resolution of 2048 × 2048 without the need for cumbersome patching. Vessel-SAM2 fine-tunes the pretrained Hiera of SAM2 using adapters in a parameter-efficient manner, while its decoder incorporates an efficient attention aggregation mechanism. Extensive experiments demonstrate the superior performance of Vessel-SAM2.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926865","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}

{"title":"Near-Surface Explosion Localization in a Built Environment Using Ground-Coupled Airwaves","authors":"Samba Gaye;Wagdy Mahmoud;Max Denis","doi":"10.1109/LSENS.2025.3594490","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3594490","url":null,"abstract":"The preservation of target signatures over long distances can be effectively achieved using low-frequency seismic and acoustic sensing. Seismic sensing minimizes clutter caused by the multipath environment often experienced by acoustic waves in urban areas. While subsurface features, such as basements, sewers, and building foundations, may clutter the environment, they do not create multipath conditions for seismic waves, which primarily propagate through solid ground. This results in less pronounced scattering and reflections compared to airborne acoustic waves from above-ground structures [1]. Furthermore, seismic waves have longer wavelengths relative to many subsurface features, making them less sensitive to small-scale clutter, unlike acoustic waves, which are more easily scattered by similar-sized objects [2], [3]. This study investigates seismic signatures from an airborne near-surface detonation of an explosive charge in a complex environment using an array of seismic sensors. We aim to accurately estimate the explosion's location amid various clutter signatures. We recorded both seismic waves and ground-coupled airwaves, with the seismic waves arriving earlier. By employing filtering and least square estimation techniques, we located the explosion source with an average error of ±25 m and determined the average velocity of the ground-coupled airwaves to be 342 m/s. These findings highlight the effectiveness of seismic sensing in locating airborne explosion sources within urban environments. Future work could optimize sensor placement and explore advanced signal processing methods or integrate data from multiple sensor types to further improve precision.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896791","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}

{"title":"A 266-nW, 4.9-μVrms Noise, Wideband Neural Recording Amplifier With Folding-Current-Reuse Operational Transconductance Amplifier","authors":"Minjae Kim;Jeongho Choi;Joongyu Kim;Sung-Yun Park","doi":"10.1109/LSENS.2025.3594060","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3594060","url":null,"abstract":"This letter presents a nano-watt, low-noise, ac-coupled wideband neural recording amplifier. The nano-watt power consumption has been achieved with 1) doubling of the transconductance by using folding current transistors in a folded-cascode operational transconductance amplifier (OTA) as input transistors [folding-current-reuse (FCR) technique], that also nulls their contribution to output noise and 2) dual supplies where the high and low voltages are assigned for low and high current consuming branches, respectively. Also, the proposed FCR technique indirectly contributes to low power consumption by forming low impedance nodes, which is a difference from a conventional current-reuse OTA in a two-stage amplifier that requires Miller compensation. The amplifier with the FCR technique has been fabricated in a 180 nm standard 1P6M complementary metal-oxide-semiconductor (CMOS) process. The fabricated chip has been experimentally verified both in benchtop and in vitro using a commercial silicon microelectrode. The amplifier consumes extremely low power of 266 nW from 0.4 and 0.6 V supplies, with the input referred noise of 4.9 μV_rms in a wide bandwidth from 0.09 Hz to 7.56 kHz and exhibits 1% total harmonic distortion with an 2.4 mV_pp input and an 40 dB closed-loop gain.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852980","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}

{"title":"Tracking Muscle Stiffness During Gripping With Wearable Ultrasound Shear-Wave Elastometry","authors":"Shane Steinberg;Yuu Ono;Sreeraman Rajan","doi":"10.1109/LSENS.2025.3594215","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3594215","url":null,"abstract":"This letter presents a wearable ultrasound shear-wave elastometry (wUS-SWEM) device and demonstrates its capability to track time- and depth-resolved muscle stiffness, using grip force as a reference for muscle activation.Shear waves were generated by a miniature actuator and detected using two unfocused ultrasound transducers integrated into a compact, wearable form factor. The device was applied to monitor the forearm flexor muscles during a cyclic grip–relax task, yielding spatiotemporal shear modulus patterns aligned with task timing. In the superficial flexors region, shear modulus exhibited a strong linear correlation with grip force (<inline-formula><tex-math>$text{r} = 0.82text{--}0.86$</tex-math></inline-formula>, <inline-formula><tex-math>$text{p}&lt; 0.001$</tex-math></inline-formula>), supporting its use as a noninvasive predictor of muscle force. These results demonstrate the feasibility of shear modulus tracking during functional activity of the upper arm using wUS-SWEM and highlight its potential for neuromuscular assessment and human–machine interfacing.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144928878","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}

{"title":"Automatic Characterization of Droplet Flow Regimes in Microfluidic T-Junctions Using Capacitive Sensing","authors":"Andreas Tröls;Nico Rathmayr;Marco Da Silva","doi":"10.1109/LSENS.2025.3594446","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3594446","url":null,"abstract":"This letter presents the automatic characterization of droplet flow regimes in a microfluidic T-junction using capacitive sensing. Key properties of the generated droplets, such as velocity and length, are extracted via three embedded electrode pairs and used to classify the prevailing flow regime. The resulting flow type depends on the junction geometry, absolute velocities, and their ratio, and is visualized in a so-called capillary plot that fully describes the junction's operational behavior. Accurate prediction, detection, and classification of flow regimes in a given junction opens new possibilities for precise and flexible droplet generation, particularly in lab-on-a-chip applications.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11106253","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144867582","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}

{"title":"Detection of Weak Muscle Fatigue Using Bioimpedance Spectroscopy Based on Current Concentration","authors":"Masaya Ishida;Masashi Taniguchi;Zimin Wang;Tetsuya Hirono;Toru Hamasaki;Takashi Katsuno;Noriaki Ichihashi","doi":"10.1109/LSENS.2025.3593853","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3593853","url":null,"abstract":"Low-load muscle exercises are a safer alternative to high-load exercises and effectively promote health across various age groups. However, low-load exercises induce minimal physiological changes, making it difficult to detect muscle fatigue. In this study, we aimed to increase the electrical conductivity of target muscles owing to exercise hyperemia during exercises and detect the weak muscle fatigue signals as following approaches. First, the spacing between current electrodes on the human thigh was determined through electromagnetic simulations to clarify the high current concentration in muscle. Next, fatigue detection sensitivities during low-load knee extension exercise with and without current concentration were evaluated. The evaluation parameter was bioelectrical impedance (BI), which was recorded before exercise and after each set of exercise. In the narrow-space electrodes with high-current concentration, extracellular water resistance (<italic>R</i>_ECW) derived from the BI decreased significantly with exercise. In contrast, in the wide-space electrodes with uniform current, <italic>R</i>_ECW showed no significant change. These findings suggest that localized BI electrode enhances fatigue detection sensitivity and provides a reliable approach to assessing the effects of low-load exercise.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11105089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831821","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}

{"title":"Parking–Occupancy Detection Through Adaptive Multisensor Camera-CNN Fusion","authors":"Vincent Lassen;Maximilian Lübke;Norman Franchi","doi":"10.1109/LSENS.2025.3593908","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3593908","url":null,"abstract":"A robust multicamera sensor system for parking–occupancy detection is introduced, combining convolutional neural networks with an adaptive fusion mechanism that leverages angular diversity. The proposed pipeline integrates viewpoint-specific bounding-box components and a distortion–reduction module that compensates for perspective-induced deformations. Under different azimuth angles and illumination conditions, including overcast, sunny, and nighttime scenarios, the fusion approach consistently outperformed single-camera systems. Notably, fusing cameras at 0<inline-formula><tex-math>$^circ$</tex-math></inline-formula> and 90<inline-formula><tex-math>$^circ$</tex-math></inline-formula> yielded an intersection-over-union (IoU) of 0.898 without correction, while the distortion–reduction module improved IoU from 0.734 to 0.856 in geometrically challenging cases. The method also maintained robust performance in low-light environments, where individual camera views degraded. Designed for scalability and minimal calibration effort, the architecture supports geometry-consistent localization across multiple sensor perspectives. These results demonstrate that combining angular fusion with correction-aware processing offers substantial gains in precision and robustness. The system is particularly suited for real-world deployment in smart parking applications under complex environmental conditions.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831829","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}

{"title":"Automated Vision-Based Detection of Impairment Through Divided Attention Psychophysical Tests","authors":"Saboora M. Roshan;Edward J. Park","doi":"10.1109/LSENS.2025.3594392","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3594392","url":null,"abstract":"Divided attention psychophysical tests are one of the main tests from standardized field sobriety tests (SFSTs) that drug recognition expert (DRE) officers employ to detect impaired drivers and to investigate the type of consumed drugs. Two well-known divided attention psychophysical tests are One Leg Stand (OLS) and Walk and Turn (WAT), which are commonly used by officers to make a decision on the status of the drivers. As this decision might be considered by courts for further investigation, the purpose of this letter is to design an automated impairment system to remove the subjectivity of SFSTs by helping officers make accurate determinations of sobriety and to serve as evidence for proving the correctness of the officers’ decisions in the courts. In this letter, a vision-based system is introduced and implemented to automatically detect impaired subjects using various feature engineering and machine learning algorithms, which were performed on the OLS and WAT videos obtained from 34 volunteer participants. Based on the results, the Random Forest classifier showed the best performance for impairment classification, achieving results comparable to those of DRE officers. Furthermore, the OLS-right features are the most relevant compared to the WAT features for the final classification.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144843038","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}

{"title":"Investigations on the Effect of Halide Dopants on the Piezo Response of ZnO-Based Flexible Energy Harvesters","authors":"Nisarg Hirens Purabiarao;Sidhi Ramer;Anshu Sahu;Vipul Singh;Iyamperumal Anand Palani","doi":"10.1109/LSENS.2025.3588875","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3588875","url":null,"abstract":"In this letter, we present a unique method to improve the output performance of ZnO-based flexible piezoenergy harvesters (FPEHs). Halide dopants (Cl, Br) are infused into ZnO nanorods (NRs) to increase lattice distortion along the <italic>c</i>-axis. This facilitates charge separation, which improves the output performance of halide-doped ZnO FPEHs. This technique confirmed that the size and concentration of the dopants have a significant impact on lattice distortion along the <italic>c</i>-axis in halogen-doped ZnO NRs. By doping the halide elements, the lattice distortion along the ZnO <italic>c</i>-axis could be tuned from a contractive to an elastic state. This modulation was driven by the variation in ionic size and doping concentration of halide elements, which yielded an enhancement in the performance of ZnO FPEHs. The pristine ZnO NRs exhibited an output voltage of 2.24 V and a current of 272.68 nA, yielding a maximum power of 610.8 nW. In contrast, ZnO:Cl NRs demonstrated a piezoelectric voltage of 3.41 V and a piezoelectric current density of 323.43 nA/cm², reaching a peak power output of 1.1 µW. ZnO:Br NRs exhibited an even higher piezoelectric voltage of 4.55 V and a current of 367.79 nA, achieving a maximum power of 1.67 µW. Further enhancement in piezoelectric performance was observed when the NaBr doping concentration was increased to 20 mM, resulting in a piezovoltage of 4.84 V, a piezoelectric current of 447.63 nA, and a peak power of 2.17 µW. This approach of inducing the lattice distortion via halide dopants could be applied to design piezoelectric devices with improved efficiency at a low cost.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 10","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036718","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}