Ahmed Rasheed;Sundus Riaz;Pietro Ibba;Giulia Elli;Angelo Zanella;Luisa Petti;Paolo Lugli
{"title":"Natural Cellulose-Based Flexible Bioimpedance Electrodes for AgriFood Applications","authors":"Ahmed Rasheed;Sundus Riaz;Pietro Ibba;Giulia Elli;Angelo Zanella;Luisa Petti;Paolo Lugli","doi":"10.1109/LSENS.2025.3561689","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3561689","url":null,"abstract":"This letter presents a monolayer onion epidermis as an ultrathin substrate for the development of dry electrodes used in electrical impedance spectroscopy (EIS), offering biocompatibility, flexibility, and high fidelity. The dry electrode is fabricated by sputtering a 100 nm layer of molybdenum onto the hydrophilic side of the epidermis membrane. Optical characterization confirms the structural integrity and quality of the thin metal film. Electrical characterization reveals a low sheet resistance of 151.28 <inline-formula><tex-math>$pm$</tex-math></inline-formula> 0.08 <inline-formula><tex-math>$Omega$</tex-math></inline-formula>/m<inline-formula><tex-math>$^{2}$</tex-math></inline-formula>, and experimental EIS studies demonstrate the electrode's enhanced electrical characteristics and capability to acquire impedance spectra from various fruits. In addition, durability tests over six months show comparable performance to commercial electrodes. This biocompatible electrode offrs a promising, cost-effective, and sustainable solution with reduced resource utilization, ideal for agrifood and wearable electronics applications.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929666","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":"An RF Amplifier Integrated With a Monitoring Sensor and a Terminal Power Sensor","authors":"Jiarui Hao;Xiaoping Liao;Zaifa Zhou","doi":"10.1109/LSENS.2025.3560545","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3560545","url":null,"abstract":"This work proposes a radio frequency (RF) amplifier that integrates a monitoring sensor and a terminal power sensor. It is fabricated in a 0.18-µm RF complementary metal oxide semiconductor (CMOS) technology. The monitoring sensor placed 2.25 µm away from the <sc>mosfet</small> detects the dissipated heat of the RF amplifier and monitors its operational status. The terminal power sensor serves as the load that enables in-line output power measurement. The monitoring sensor and terminal power sensor comprise 22 and 24 sets of thermocouples, respectively, which are made of aluminum and p-type polysilicon. The RF amplifier exhibits a minimum input return loss of −9.11 dB at 3.04 GHz. The peak gain at 3.5 GHz is 9.38 dB, which is determined from the analysis of the output voltage of the terminal power sensor. The output voltage of the monitoring sensor changes from 0.986 to 0.957 mV as the input power varies from −12 to 0 dBm. In relation to conventional state detection methods, this approach eliminates the need for external test equipment.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143871093","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":"Relaxation Oscillator Based Improved Resistance to Frequency Converter","authors":"Ekta Sharma;Mohammad Idris Wani;Shahid Malik","doi":"10.1109/LSENS.2025.3561019","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3561019","url":null,"abstract":"The relaxation oscillator-based circuits find utility in various resistive and capacitive sensor interfaces, thanks to their quasi-digital output. The integration of relaxation oscillator with Wheatstone bridge brings the unique advantage of a high-resolution resistive sensing system without any additional analog-to-digital converters. However, the conventional topologies of a Wheatstone bridge circuit with relaxation oscillator encounter challenges, such as dc offset voltage and output nonlinearity, particularly for single-element resistive sensors. This letter introduces an improved relaxation oscillator-based configuration to mitigate these issues. It employs a dc-servo loop between the Wheatstone bridge and the relaxation oscillator for offset voltage compensation. In addition, the quarter bridge circuit is modified to linearly convert the resistance change into output frequency change across a broad dynamic range of “<inline-formula><tex-math>$Delta R$</tex-math></inline-formula> .” The design and experimental results are discussed. The results show that quarter and full bridge configurations are immune to offset voltage variations as high as 100 and 60 mV, respectively, and provide linear frequency response for the “<inline-formula><tex-math>$Delta R/text{R'}$</tex-math></inline-formula>’ variations up to 190% and 90% in quarter and full bridge configuration, respectively, with nonlinearity error of less than 0.01%.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943952","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 Wafer-Level Vacuum-Packaged MEMS Quadruple Mass Gyroscope Operated in Mode-Split and Open-Loop Detection","authors":"Shaolei Ge;Bo Jiang;Shenhu Huang;Yan Su","doi":"10.1109/LSENS.2025.3560456","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3560456","url":null,"abstract":"This letter proposes a wafer-level vacuum-packaged micro - electro - mechanical systems (MEMS) quadruple mass gyroscope (QMG) based on the classical QMG architecture. The design incorporates several innovations to enhance performance in open-loop and mode-split operation modes. The proposed QMG employs variable-area comb electrodes to improve driving electrostatic nonlinearities and sensing nonlinearities. Quadrature errors are reduced through electrostatic negative stiffness using quadrature electrodes on proof masses. Wafer-level vacuum packaging achieves a high drive mode Q-factor of 1.06 million, enabling a low ac driving voltage of 4.7 mV, thereby effectively suppressing the feedthrough interference. The use of numerous sensing combs and a frequency and damping regulator reduces the sense mode Q-factor to 0.11 million, enhancing environmental interference resistance. In addition, the numerous sensing combs further enhance the open-loop scale factor. Leveraging these innovative designs, the QMG achieves a bias instability of 0.54°/h at a frequency split of 70 Hz, an angle random walkof 0.55°/√h, a dynamic range of ±300°/s, and a theoretical bandwidth of 37.8 Hz. These characteristics demonstrate that the proposed QMG achieves satisfactory performance in frequency-split and open-loop modes.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888384","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}
Deniz Kumlu;Timothee Vincon;Muhammad Arsalan;Ernesto Horne
{"title":"A Novel Hybrid TDMA–DDMA Approach for Imaging Automotive Radar Systems","authors":"Deniz Kumlu;Timothee Vincon;Muhammad Arsalan;Ernesto Horne","doi":"10.1109/LSENS.2025.3560791","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3560791","url":null,"abstract":"In this letter, we propose a novel hybrid time-division multiple access (TDMA) and Doppler-division multiple access (DDMA) model for cascaded radar systems, targeting high-resolution automotive radar applications. By leveraging the Texas instruments AWR2243 radar sensor, configured in a cascaded multiple-input multiple-output arrangement, we demonstrate the advantages of combining TDMA and DDMA for enhanced performance in both velocity resolution and range accuracy. Conventional TDMA and DDMA approaches suffer from inherent tradeoffs between maximum unambiguous velocity, Doppler resolution, and frame rate. Our hybrid method dynamically toggle between TDMA and DDMA activation patterns, achieving a balance between these metrics. Through theoretical analysis and experimental validation, we show that our model improves Doppler resolution while maintaining a competitive frame rate and range resolution. The proposed hybrid solution is particularly advantageous for scenarios where both high velocity measurements and high angular resolution are critical, such as in advanced driver-assistance systems and autonomous driving. This approach provides a flexible and efficient means of optimizing radar performance without compromising key system parameters, as supported by our experimental results and theoretical calculations.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888320","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":"Human Activity Classification With User-Held FMCW Radar Using Deep Recurrent Neural Networks","authors":"Juho Cha;Insoo Choi;Kyungwoo Yoo;Youngwook Kim","doi":"10.1109/LSENS.2025.3560919","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3560919","url":null,"abstract":"This letter proposes a human activity recognition method using user-held frequency-modulated continuous wave radar, which can be embedded in wireless devices, such as smartphones that come into direct contact with the user's body. Unlike the previous research that primarily measured human activities from a distance, our approach assumes that the radar is in the user's pocket, monitoring the movements of the body parts, such as limbs to recognize five distinct activities. We utilized range-Doppler maps to capture temporal changes in range and Doppler frequency, and employed deep learning models, including a 3D-convolutional neural networks (CNN) and a combination of long short-term memory (LSTM) with a 2D-CNN, to classify activities. Experimental results show that the LSTM-2D-CNN achieved a validation accuracy of 95.94%. Human activity classification using user-held radar offers robust performance while maintaining user privacy, making it suitable for a wide range of applications, such as healthcare, security, and defense.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900592","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":"An Attention Guided Lightweight Network-Based Scheme for Anxiety Detection Using Multimodal Analysis of Single-Channel Wearable ECG and RSP Sensor Signals","authors":"Utsab Saha;Swojan Datta Sammya;Puja Saha;Shaikh Anowarul Fattah;Celia Shahnaz","doi":"10.1109/LSENS.2025.3560396","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3560396","url":null,"abstract":"This letter presents an attention-guided, lightweight deep learning (DL) network-based approach that utilizes electrocardiogram (ECG) and respiration (RSP) sensor signals to detect various stages of anxiety. For accurate detection, an effective attention mechanism has been incorporated into our proposed DL baseline architecture with a multiobjective loss function. Our proposed model has proven to be highly effective, with minimal trainable parameters and a very simple structural design, achieving an impressive accuracy of 98.67% on a publicly available benchmark dataset in predicting four different anxiety classes. The proposed model has been thoroughly tested using various data window durations, different loss functions, and attention mechanisms. Finally, it has been demonstrated that the proposed architecture, incorporating adaptive attention and a multiobjective loss function, outperforms existing methods in anxiety stages detection.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932266","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":"m-MTDATA:WSe2:Alq3 Nanocomposite-Based Broadband Photodetector","authors":"Tulika Bajpai;Shweta Tripathi","doi":"10.1109/LSENS.2025.3560538","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3560538","url":null,"abstract":"The authors demonstrate a high response broad band photodetector using poly(3,4-ethylenedioxythiophene):polystyrene sulfonate as hole transport layer, 4,4′,4″-tris(3-methylphenylphenylamino) triphenylamine (m-MTDATA), tris(8-hydroxyquinoline) aluminum (III) (Alq<sub>3</sub>), and Tungsten di-selenide (WSe<sub>2</sub>) material-based nanocomposite (NC) film working as an active layer prepared through dispersion method. The photodetector is fabricated on an ITO-coated glass substrate. A spin coater is utilized for the film (NC) deposition, followed by aluminum (Al) electrode deposition in a thermal evaporation unit. The proposed structure Al/m-MTDATA:WSe<sub>2</sub>:Alq<sub>3</sub>/ITO-coated glass-based broadband photodetector exhibits a broad photo response with maximum responsivity <inline-formula><tex-math>${{{bm{R}}}_{bm{S}}}$</tex-math></inline-formula> (A/W) of 523, 550, and 430 A/W; at 350 nm (UV), 550 nm (visible), and 850 nm (IR) at +1V bias. The device possesses the rise/fall time of 4.11 μs/2.55 μs at 350 nm, 0.27 μs/0.33 μs at 550 nm, and 1.17 μs/1.16 μs at 850 nm. The proposed organic–inorganic NC has encouraging properties for optoelectronic applications.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888414","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":"Standardizing Number of EEG Sensors for AI-Driven Dementia Detection","authors":"Quoc-Toan Nguyen","doi":"10.1109/LSENS.2025.3560259","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3560259","url":null,"abstract":"For Alzheimer's disease (AD), the most prevalent dementia subtype, early detection is paramount for slowing disease progression because cures are not available. Artificial intelligence (AI) has gained significant attention for AD detection, particularly through electroencephalography (EEG)—a cost-effective, accessible technique that records brain activity from sensors placed on the scalp. However, the variability in EEG sensor configurations across different settings poses a significant challenge, as typical AI models require different models for specific setups. To address this limitation, this letter explores using EEG microstates to standardize sensor configurations and propose a new AI model, E-FastKAN, to validate sensor generalization, ensuring effectiveness regardless of the original number of sensors. Using data from 115 participants with 575 samples from high-density and low-density sensor setups, this study aims to open a new approach to reduce costs, increase accessibility, and broaden the usability of AI-driven dementia detection.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892362","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":"Highly Stretchable, Sensitive, and Robust Wearable Strain Sensor Based on CNTs/AgNWs Nanocomposite for Health and Fitness Monitoring","authors":"Jagan Singh Meena;Lucas Lum Yu Xiang;Yeow Kheng Lim","doi":"10.1109/LSENS.2025.3560735","DOIUrl":"https://doi.org/10.1109/LSENS.2025.3560735","url":null,"abstract":"This letter reports a resistive-type wearable strain sensor fabricated using an electrically conductive hybrid network of single-walled carbon nanotubes (CNTs) and silver nanowires (AgNWs). AgNWs degrade over time due to silver corrosion in ambient conditions, leading to electrode failure. To mitigate this issue, CNTs were incorporated as a protective shield, effectively interlinking the AgNWs. This not only improved the stability and durability of the AgNWs but also resulted in a robust and highly conductive CNTs/AgNWs hybrid network. The hierarchical CNTs/AgNWs-based strain sensor exhibited better performance, achieving a large elongation of up to 100% with high sensitivity, demonstrated by a gauge factor (GF) of 79. It also featured a fast response time of 42 ms and outstanding mechanical stability, maintaining performance over 5000 stretch-release cycles. The sensor's performance was assessed under normal environmental conditions for a period of 180 days (approximately 6 months), showing minimal degradation in GF. This provides valuable insights into long-term changes, aiding the development of more robust, durable, and reliable nanocomposite-based strain sensors for practical applications. The sensor was used to monitor various human motions, including finger, throat, and elbow movements.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 5","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908432","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}