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30th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2023

作者： Yarragunta, Jaya Satyanarayana Aprile, Antonio Fugger, Andreas Conzatti, Francesco Bonizzoni, Edoardo Malcovati, Piero University of Pavia Department of Electrical Computer and Biomedical Engineering Italy Infineon Technologies Austria Villach Austria

ISBN: (纸本)9798350326499

Shunt current measurements are widely used for monitoring and controlling the current flow in various applications, such as power converters and battery management systems (BMS). The accuracy and resolution of this kind of measurements depend on the performance of the sample-and-hold (S/H) circuit that captures the voltage across a shunt resistor. In this paper, we propose a noise analysis of a S/H circuit that operates in accumulation mode;this technique enables to lower the thermal noise by 3 dB for every doubling of the number of accumulation cycles. The proposed analysis, confirmed by extensive simulation results, demonstrates that this approach offers a lower noise power spectral density and a higher signal-to-noise ratio if compared with conventional amplification-based S/H solutions. © 2023 IEEE.

关键词： Signal to noise ratio

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A Smart Optofluidic Sensing Platform Ensuring Patients' Safety during Parenteral Nutrition Administration

A Smart Optofluidic Sensing Platform Ensuring Patients' Safe...

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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023

作者： Bello, Valentina Bodo, Elisabetta Merlo, Sabina Department of Electrical Computer and Biomedical Engineering University of Pavia Via Ferrata 5 Pavia27100 Italy

ISBN: (纸本)9798350345995

Parenteral nutrition (PN) is a lifesaving treatment for a large number of patients suffering from different pathologies, from cancer to intestinal failure, from eating disorders to inflammatory bowel disease. In PN, liquid nutritive drugs are injected into the patient's body intravenously through an infusion delivery pump. As reported in the scientific literature, among all medical treatments, PN is the most commonly prone one to human errors [1]. In particular, very often wrong PN mixtures (PNMs) are administered. The consequences can be very dangerous to the patient's health, leading to death in the most severe cases. Despite this fact, currently no standard safety protocols or control devices are implemented to prevent medication errors in PN. Hence, in the framework of the DSF (Digital Smart Fluidics - project No. 1175234, founded by POR FESR 2014-2020), we have developed an optofluidic sensing platform to distinguish different types of transparent commercial PNMs on the basis of their refractive index (RI). Indeed, each mixture contains different concentrations of glucose, amino acids, and electrolytes, determining different values of their RI. The instrumental configuration of the sensor (Fig 1(a)) features a laser diode that generates a red beam (wavelength of 670 nm) travelling obliquely through a plastic cuvette channel containing the PNM under test. Light is then back-reflected by a mirror applied to the back of the cuvette, and finally exits the channel at a position that depends on the RI of the PNM. The position of the output light spot is easily detected with a linear position sensitive detector (PSD) [2]. The two photo-currents I1 and I2 generated at the extremities of the sensitive area are given as the PSD outputs: by proper normalization, it is possible to retrieve the measured light beam position as pPSD = L/2 × (I1 - I2)/(I1 + I2), where L is the PSD length. The sensor response is then retrieved, after defining the baseline signal measured in pre

关键词： Glucose

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Modeling of a Hexagonal Microstrip Patch Antenna for Breast Cancer Detection

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Journal of engineering and Science in Medical Diagnostics and Therapy 2024年第3期7卷 031007页

作者： Chowdhury, Nure Alam Wang, Lulu Islam, Md Shazzadul Gu, Linxia Kaya, Mehmet Department of Biomedical Engineering and Science Florida Institute of Technology MelbourneFL32901 United States Biomedical Device Innovation Center Shenzhen Technology University Shenzhen518118 China Department of Electrical and Computer Engineering International Islamic University Malaysia Jalan Gombak Selangor Kuala Lumpur53100 Malaysia

Breast cancer is a global problem, and it is inevitable to detect cancerous cells at early stages. In recent years, microwave imaging (MWI) technology has been widely applied in biomedical applications for its nonionizing radiation. Therefore, in this paper, a low profile hexagonal microstrip patch antenna has been proposed for the technology to detect breast cancer. This antenna has wide operating bandwidth of 13.5 GHz (6.6 GHz to 20.1 GHz), and the return loss is as low as -50.83 dB at 8 GHz. To evaluate the antenna performances, the proposed antenna has been simulated in two different simulation software like HFSS and CST MWS. The antenna has achieved a maximum gain of 8.82 dBi with a quasi-omnidirectional radiation pattern. A three-layered human body mimicking breast phantom with different dielectric properties has been designed with and without tumor mimicking tissue. The difference between the dielectric properties of the tumor and the dielectric properties of different layers of breast phantom in the presence of external radiation field can inform the existence of tumor inside the breast phantom. An array of eight elements of proposed antenna is distributed around the breast phantom to detect the tumor with a minimum radius of 2 mm. Because of the low profile and compact in size (7:9 mm X 11:4 mm), the proposed antenna is suitable for multistatic MWI technology for breast cancer detection at early stage. Copyright © 2024 by ASME.

关键词： Tumors

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Digital Twin-Based 3D Map Management for Edge-Assisted Mobile Augmented Reality

Digital Twin-Based 3D Map Management for Edge-Assisted Mobil...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Zhou, Conghao Gao, Jie Li, Mushu Cheng, Nan Shen, Xuemin Sherman Zhuang, Weihua University of Waterloo Department of Electrical and Computer Engineering Canada Carleton University School of Information Technology Canada Toronto Metropolitan University Department of Electrical Computer and Biomedical Engineering Canada Xidian University School of Telecommunication Engineering Xi'an China

ISBN: (纸本)9798350345384

In this paper, we design a 3D map management scheme for edge-assisted mobile augmented reality (MAR) to support the pose estimation of individual MAR device, which uploads camera frames to an edge server. Our objective is to minimize the pose estimation uncertainty of the MAR device by periodically selecting a proper set of camera frames for uploading to update the 3D map. To address the challenges of the dynamic uplink data rate and the time-varying pose of the MAR device, we propose a digital twin (DT)-based approach to 3D map management. First, a DT is created for the MAR device, which emulates 3D map management based on predicting subsequent camera frames. Second, a model-based reinforcement learning (MBRL) algorithm is developed, utilizing the data collected from both the actual and the emulated data to manage the 3D map. With extensive emulated data provided by the DT, the MBRL algorithm can quickly provide an adaptive map management policy in a highly dynamic environment. Simulation results demonstrate that the proposed DT-based 3D map management outperforms benchmark schemes by achieving lower pose estimation uncertainty and higher data efficiency in dynamic environments. © 2023 IEEE.

关键词： Cameras

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Cognitive Analysis based on Brain Connectivity for Learning Task fMRI Data using CONN Software Package 1

Cognitive Analysis based on Brain Connectivity for Learning ...

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1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Jatoi, Munsif Ali Teevino, Sadam Hussain Dharejo, Fayaz Ali Salim Habib University Department of Biomedical Engineering Sindh Karachi Pakistan Tenologico de Monterrey School of Engineering and Sciences Mexico Khalifa University Department of Electrical Engineering and Computer Science United Arab Emirates

ISBN: (纸本)9798350373042

The educational psychology is dependent upon the cognition and learning. The productive research in this domain yields the results for improvements in novel pedagogical methods at various educational level. The learning and memory are closely affiliated with brain structure and functioning i.e., neurobiology which has been the topic of research in philosophy, psychology and social sciences. Hence, to study the learning mechanism for improvements in educational methods, its essential to understand theoretical background of cognitive analysis through brain sciences. The human brain consists of billions of neurons with trillions of synaptic connections structurally and functionally organized in multiple scales of space and time, respectively. This complex structure is responsible for various complex and simple mental/physical tasks such as learning, memory, listening, sequencing, reasoning, motion, thinking, controlling, etc. The brain activity is analyzed through either source analysis or connectivity analysis. The connectivity analysis is carried out by either anatomical way, which is termed as anatomical connectivity, or through the functional way, which is termed as functional connectivity. However, the third explores the cause and effect relationship for a set of neurons and is termed as effective connectivity. This research work produces a generalized review for educational learning and then its relationship with connectivity analysis, including its introduction, graph theory implication, discussion for its types, and parameter discussion. Finally, functional connectivity was implemented on brain data using the CONN software package to compare various degrees, Eigenvalue, and betweenness centrality using fMRI data. The results show that the Eigenvalue centrality measure performs the best result for functional connectivity compared with other centrality measures. © 2024 IEEE.

关键词： Software packages

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Event-triggered robust cooperative output regulation for a class of linear multi-agent systems with an unknown exosystem

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Journal of Automation and Intelligence 2024年第2期3卷 119-127页

作者： Yangyang Qian Lu Liu Charles L.Brown Department of Electrical and Computer Engineering University of VirginiaCharlottesvilleVA 22904USA Department of Biomedical Engineering City University of Hong KongKowloonHong Kong999077China

This paper investigates the robust cooperative output regulation problem for a class of heterogeneousuncertain linear multi-agent systems with an unknown exosystem via event-triggered control (ETC). By utilizingthe internal model approach and the adaptive control technique, a distributed adaptive internal model isconstructed for each agent. Then, based on this internal model, a fully distributed ETC strategy composed ofa distributed event-triggered adaptive output feedback control law and a distributed dynamic event-triggeringmechanism is proposed, in which each agent updates its control input at its own triggering time instants. It isshown that under the proposed ETC strategy, the robust cooperative output regulation problem can be solvedwithout requiring either the global information associated with the communication topology or the bounds ofthe uncertain or unknown parameters in each agent and the exosystem. A numerical example is provided toillustrate the effectiveness of the proposed control strategy.

关键词： Adaptive control Event-triggered control Internal model Multi-agent systems Output regulation

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A Multimodality Electrochemical and Impedance Spectroscopy System-on-a-Chip With Temperature Sensing and Impedance-Boosting Techniques

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IEEE Transactions on biomedical Circuits and Systems 2023年第4期17卷 857-871页

作者： Lin, Yi-Jie Liu, Wei-Cheng Huang, Yu-Chiao Huang, Ying-Jie Yeh, Yung-Hua Chang, Min-Hua Lin, Shu-Ping Liao, Ying-Chih Liao, Yu-Te National Yang Ming Chiao Tung University Institute of Electrical and Computer Engineering Hsinchu300 Taiwan National Chung Hsing University Graduate Institute of Biomedical Engineering Taichung40227 Taiwan National Taiwan University Department of Chemical Engineering Taipei10617 Taiwan

This article presents a multimodal electrochemical sensing system-on-chip (SoC), including the functions of cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and temperature sensing. CV readout circuitry achieves an adaptive readout current range of 145.5 dB through an automatic range adjustment and resolution scaling technique. EIS has an impedance resolution of 9.2 mΩ Hz at a sweep frequency of 10 kHz and an output current of up to 120 μA. With an impedance boost mechanism, the maximum detectable load impedance is extended to 22.95 kΩ, while the total harmonic distortion is less than 1%. A resistor-based temperature sensor using a swing-boosted relaxation oscillator can achieve a resolution of 31 mK in 0-85 °C. The design is implemented in a 0.18 μm CMOS process. The total power consumption is 1 mW. © 2007-2012 IEEE.

关键词： Temperature sensors

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A Unified Modulated Model Predictive Control for a Two-Stage AC-DC Converter Interfacing a Vanadium Redox Flow Battery

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IEEE Transactions on Industry Applications 2025年

作者： Volpini, Andrea Salvo, Salvatore R. Di Tresca, Giulia Leuzzi, Riccardo Zanchetta, Pericle Electrical Computer and Biomedical Engineering Dept. Pavia Italy Department of Electrical and Information Engineering Bari Italy

With the increasing integration of renewable energy sources into electrical grids, energy storage systems have become crucial for stability and regulation. Thus, dedicated two-stage AC-DC converters are essential for integrating batteries into the grid infrastructure. These converters typically employ either single-phase or three-phase inverters paired with a Dual Active Bridge (DAB) in a back-to-back configuration, ensuring high efficiency and galvanic isolation. The conventional control scheme for such converters involves two separate PI-based control loops, one for each stage. This paper proposes a novel control strategy based on a Modulated Model Predictive Control (MMPC) algorithm for a two-stage AC-DC converter. The proposed approach utilizes a single cost-function optimization routine to simultaneously control both the grid-side and the battery-side stages, simplifying the control architecture and enhancing performance. Finally, the proposed MMPC is implemented on a DSP and FPGA-based board and the experimental results show that the proposed solution achieves faster dynamics than conventional control with no overshoots or undershoots. © 1972-2012 IEEE.

关键词： Predictive control systems

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Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara Rehman Muhammad Farrukh Qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

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NutriA: A Responsive Web App to Monitor Nutrition and Clinical Outcomes in Inflammatory Bowel Disease Patients

NutriA: A Responsive Web App to Monitor Nutrition and Clinic...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Petrini, Giorgia Pala, Daniele Lenti, Marco Vincenzo Lepore, Federica Bosoni, Pietro Quaglini, Silvana Lanzola, Giordano University of Pavia Department of Computer Electrical and Biomedical Engineering Pavia Italy University of Pavia First Department of Internal Medicine Pavia Italy

ISBN: (纸本)9798350386226

Inflammatory Bowel Disease (IBD) is a term that includes two chronic conditions characterized by inflammation of the gastrointestinal tract, i.e., Ulcerative Colitis and Crohn's Disease. IBD can be associated to symptoms that significantly reduce quality of life and can lead to serious complications, therefore proper disease monitoring and treatment is necessary. To this end, Telemedicine has been identified as a useful tool, since it can ease the patients' burden on the management of nutrition and pharmacological treatment, and can improve the connection with the physicians. In this paper, we present NutriA, a new responsive web application for the management of IBD patients in Italy, created to assist patients with diet, medications and symptoms monitoring, optimizing the follow-ups frequency and providing direct assistance by the doctors. Besides being useful to improve the patients' well-being, NutriA is also designed to be used in a new clinical study on the effects of malnutrition on IBD treatment. © 2024 IEEE.

关键词： Telemedicine

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