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2023 IEEE biomedical Circuits and Systems Conference, BioCAS 2023

作者： Han, Yiming Zhao, Linran Stephany, Raymond G Hsieh, Ju-Chun Wang, Huiliang Jia, Yaoyao The University of Texas at Austin Department of Electrical and Computer Engineering United States The University of Texas at Austin Department of Biomedical Engineering United States

ISBN: (纸本)9798350300260

This paper presents a scattered wirelessly powered Electroencephalographic (EEG) recording system with 32 standalone devices to enable untethered, continuous, long-term EEG recording. Each device incorporates a wireless low-power EEG recording ASIC, a receiver (Rx) coil, and a hydrogel electrode in a compact cube (1.2 cm × 1.2 cm × 0.5 cm). The 32 EEG devices are wirelessly powered by a transmitter (Tx) coil array, under the control of a central control unit, through an inductive link operating at 60 MHz. The 60 MHz carrier also serves as the data link, enabling forward data transmission of user commands from the central control unit to EEG devices and back data transmission from EEG devices to the central control unit. In each EEG device, the ASIC will decode the user commands that are loaded onto the inductive link carrier by a novel synchronized pulse width demodulator at a data rate of 4 Mbps to control the ASIC digitizing the EEG signal or transmitting the EEG data. The EEG analog frontend (AFE) with a gain of 45 dB, bandpass of 0.03 Hz to 800 Hz, and input-referred noise (IRN) of 4.5 μVrms amplifies and filters EEG signals. Then, the 10-bit successive approximation register analog-to-digital converter (SAR-ADC) with an effective number of bits (ENOB) of 9.6 bits digitizes the amplified EEG signals. The backscatter-based data Tx transfers the EEG data to the central control unit via load-shift-keying (LSK) modulation at a data rate of 3.75 Mbps. The overall ASIC and the prototype of the scattered wirelessly powered EEG recording system have been successfully evaluated on human subjects. © 2023 IEEE.

关键词： EEG recording inductive link scattered structure synchronized pulse width modulation

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Learning from Future: Prediction-based Data Augmentation to Enhance Power Grids Fault Detection 11

Learning from Future: Prediction-based Data Augmentation to ...

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11th IEEE International Conference on Smart Energy Grid engineering, SEGE 2023

作者： Rogers, Jennifer Danilczyk, William Lin, Hui Sun, Yan Lindsay University of Rhode Island Department of Electrical Computer and Biomedical Engineering KingstonRI United States

ISBN: (纸本)9798350340716

As power grids modernize to include wide area monitoring and advanced metering infrastructures, the applications for data-driven methods based on artificial intelligence (AI) for situational awareness, reliability, and security continue to grow. However, obtaining effective training data that captures normal and anomalous operations in power systems remains a great challenge. This paper proposes a data-augmentation method that can efficiently build effective training data sets, benefiting various data-driven applications used in power grids without increasing the size of training data set. By leveraging load prediction in smart grids, we obtain the knowledge of future operating conditions and potential anomalies, which are integrated with the historical data in the training data set. By utilizing this augmented training data set, we significantly increase the accuracy of data-driven fault detection, e.g., 8.6% on average, compared to the results trained based on historical data only. © 2023 IEEE.

关键词： Fault detection

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A Real Time Physics-Based Industrial Control System Honeynet Architecture for the Smart Grid 8

A Real Time Physics-Based Industrial Control System Honeynet...

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8th International Conference on Information and Network Technologies, ICINT 2023

作者： De Pace, Gabriel Lin, Hui Sun, Yan Lindsay University of Rhode Island Department of Electrical Computer and Biomedical Engineering KingstonRI United States

ISBN: (纸本)9798350301458

Many details of cyber attacks occurred to Industrial Control Systems (ICS) such as power grids remain as a secret. To reveal those secrets and benefit a broad research community, we propose an original cyber-physical honeypot architecture that can seamlessly couple IT and OT components in an power grid. Specifically, we will provide high interaction with adversaries as physical processes of an ICS move forward, revealing attack strategies according to adversaries' knowledge on physical trajectories of the target system. Our preliminary evaluations demonstrate that the proposed CPS honeypot can present realistic device fingerprints and application-layer payload that piggybacks meaningful measurements conforming to the physical model of a power grid. In addition, by leveraging runtime high-fidelity OPAL-RT simulator, our CPS honeypot causes small latency, at least one order of magnitude smaller compared to the existing work. © 2023 IEEE.

关键词： Smart power grids

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Microfluidic compartmentalization of rat vagal afferent neurons to model gut-brain axis

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Bioelectronic Medicine 2024年第1期10卷 1-13页

作者： Girardi, Gregory Zumpano, Danielle Raybould, Helen Seker, Erkin Department of Biomedical Engineering University of California – Davis DavisCA95616 United States Department of Anatomy Physiology and Cell Biology University of California – Davis DavisCA95616 United States Department of Electrical and Computer Engineering University of California – Davis DavisCA95616 United States

Background: Vagal afferent neurons represent the key neurosensory branch of the gut-brain axis, which describes the bidirectional communication between the gastrointestinal system and the brain. These neurons are important for detecting and relaying sensory information from the periphery to the central nervous system to modulate feeding behavior, metabolism, and inflammation. Confounding variables complicate the process of isolating the role of the vagal afferents in mediating these physiological processes. Therefore, we developed a microfluidic model of the sensory branch of the gut-brain axis. We show that this microfluidic model successfully compartmentalizes the cell body and neurite terminals of the neurons, thereby simulates the anatomical layout of these neurons to more accurately study physiologically-relevant processes. Methods: We implemented a primary rat vagal afferent neuron culture into a microfluidic platform consisting of two concentric chambers interconnected with radial microchannels. The microfluidic platform separated cell bodies from neurite terminals of vagal afferent neurons. We then introduced physiologically-relevant gastrointestinal effector molecules at the nerve terminals and assessed their retrograde transport along the neurite or capacity to elicit an electrophysiological response using live cell calcium imaging. Results: The angle of microchannel outlets dictated the probability of neurites growing into a chamber versus tracking along chamber walls. When the neurite terminals were exposed to fluorescently-labeled cholera toxin subunit B, the proteins were taken up and retrogradely transported along the neurites over the course of 24 h. Additionally, mechanical perturbation (e.g., rinsing) of the neurite terminals significantly increased intracellular calcium concentration in the distal soma. Finally, membrane-displayed receptor for capsaicin was expressed and trafficked along newly projected neurites, as revealed by confocal microscopy

关键词： Microfluidics

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Automated lumpy skin grading in bovine images using novel deep convolutional neural networks

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Multimedia Tools and Applications 2024年 1-26页

作者： Muhammad, Abdul Malik ur Rehman, Muhammad Zia Mushtaq, Zohaib Qureshi, Muhammad Farrukh Department of Biomedical Engineering Riphah International University Islamabad44000 Pakistan Department of Electrical Electronics and Computer Systems University of Sargodha Sargodha40100 Pakistan Department of Electrical Engineering Namal University Mianwali Mianwali42250 Pakistan Center of AI and BigData Namal University Mianwali Mianwali42250 Pakistan

The diagnosis and prevention of lumpy skin disease, a viral ailment affecting cattle and buffalo, present significant financial implications for the livestock industry. Traditional methods for identifying lumpy skin disease rely on manual visual inspection by veterinarians, which can be labor-intensive, subjective, and prone to errors. To address these challenges, this study proposes a novel deep convolutional neural network (DCNN) model for the automatic recognition and grading of lumpy skin disease from bovine images. The primary contributions of this research include the development of a DCNN architecture specifically tailored for this task, comprising five convolutional layers, five max pooling layers, two fully connected layers with ReLU activation, and a final fully connected layer with softmax activation. The model’s detection accuracy is further enhanced by applying image cropping and patching techniques, which divide each input image into 12 patches to improve local feature extraction. The proposed model was trained and tested using a publicly available dataset from Kaggle. Comparative analysis was conducted against several state-of-the-art models, including InceptionV3, ResNet50, MobileNetV3, VGG19, and Xception. The DCNN model demonstrated superior performance, achieving the highest validation accuracy of 0.96875, outperforming the compared models in terms of accuracy, precision, recall, and F1 score. Additionally, the study explores the potential of transitioning from binary to multiclass classification, which would allow for the assessment of the severity of lumpy skin disease. This future direction aims to provide more nuanced and actionable information for veterinary diagnostics. The significance of this research lies in its potential to offer an objective, efficient, and scalable solution for early disease detection and prevention in livestock, thereby presenting considerable economic benefits for farmers and the livestock industry as a whole. The me

关键词： Convolutional neural networks

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Assessing the stiffness of intact bone marrow with non-contact optical coherence elastography 12

Assessing the stiffness of intact bone marrow with non-conta...

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Optical Elastography and Tissue Biomechanics XII 2025

作者： Singh, Amandeep Singh, Manmohan Aglyamov, Salavat R. Mayerich, David Larin, Kirill V. Department of Biomedical Engineering University of Houston TX77204 United States Department of Mechanical and Aerospace Engineering University of Houston TX77204 United States Department of Electrical and Computer Engineering University of Houston TX77204 United States

ISBN: (纸本)9781510683907

Bone marrow plays an important role in regulating immunity for homeostasis and controlling stromal cell trafficking. Bone marrow cells are sustained by the framework of connective tissues that preserve the mechanical and functional integrity of the tissue. Optical coherence elastography (OCE) is a potential method to measure the biomechanical properties of bone marrow with high spatio-temporal resolution. In this work, we demonstrate the quantification of wave speed at different locations along the diaphysis of mice femur samples using non-contact air-coupled ultrasound OCE (ACUS-OCE). The preliminary results from the current approach show that the ACUS-OCE can characterize the mechanical stiffness of intact bone marrow and can be used for minimally invasive and ex vivo clinical applications. © 2025 SPIE.

关键词： Bone

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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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Supervised learning applied to electrocardiogram statistical features for the detection of premature ventricular contraction

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Research on biomedical engineering 2025年第1期41卷 1-12页

作者： Issa, Khouloud Rammal, Abbas Assaf, Rabih Ghandour, Ahmad Electrical and Communication Engineering Department College of Engineering Phoenicia University Zahrani South Lebanon Statistics and Informatics Department Faculty of Science Lebanese University Beirut Lebanon Mathematics and Computer Sciences Department Faculty of Arts and Sciences Lebanese American University Beirut Lebanon Department of Mathematics Faculty of Arts and Sciences Holy Spirit University of Kaslik Jounieh Lebanon Biomedical Engineering Department Faculty of Engineering Islamic University of Lebanon Wardenieh30014 Lebanon

Purpose: The development of an automated premature ventricular contraction (PVC) detection system has significant implications for early intervention and treatment decisions. This study aims to develop a novel approach using various supervised machine learning (ML) methods for detecting PVCs in electrocardiogram (ECG) recordings. Methodology: To achieve this, we extracted ten distinct statistical and temporal features from 33 long-term ECG recordings from the benchmark MIT-BIH arrhythmia database (MIT-BIH-AD), capturing significant characteristics from the signals. We then investigated the effectiveness of traditional ML algorithms in identifying PVCs based on these features, namely support vector machine (SVM), decision tree (DT), naïve Bayes (NB), k-nearest neighbor (KNN), linear discriminant analysis (LDA), and artificial neural network (ANN). Results: Among these classifiers, the SVM, KNN, ANN, and DT classifiers demonstrated exceptional discriminatory power and classification performance, yielding near-perfect area under the receiver operating characteristic curve (AUC-ROC) values of 97.3%, 95.4%, 95%, and 94.1%, respectively. On the other hand, the SVM classifier emerged as the most accurate, achieving an overall accuracy of 97.39%, indicative of making correct predictions. Conclusion: These findings underscore the generalization of the proposed approach, especially since we worked on an extended dataset encompassing different types of heartbeats to discriminate PVCs from other heartbeat types, not only normal ones, and providing closer alignment with real-world scenarios. Subsequently, the robustness and accuracy of these models highlight their suitability for clinical applications and their potential for efficient implementation and deployment in the diagnosis of cardiovascular diseases (CVDs), as they demand minimal computational resources and time. © The Author(s), under exclusive licence to The Brazilian Society of biomedical engineering 2025.

关键词： Decision trees

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An economic centralised combinational load shedding scheme to protect power system in case cascade and major disturbances occur

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International Journal of Ambient Energy 2022年第1期43卷 8949-8958页

作者： Mohammadzadeh, Hossein Mohammadzadeh, Mohammad Department of Electrical Engineering Shahid Chamran University of Ahvaz Ahvaz Iran School of Electrical Computer and Biomedical Engineering Southern Illinois University CarbondaleIL United States

This paper introduces an economic centralised combinational load shedding scheme for self-healing of the power system against cascading significant disturbances. The proposed method utilises the voltage stability risk index (VSRI) to maintain the power system's voltage and frequency stability margin. In this algorithm, the protection against cascading disturbances when the spinning reserve of the system cannot recover has been considered. Moreover, it considered the voltage and economic cost of loads to find the proper location of load shedding and minimised the number of customers being turned off to increase social welfare. Furthermore, a voltage stability index based on the maximum power limit of the transmission lines (L index) and frequency steps is used to offset issues associated with VSRI. According to the simulation results that have been performed over the 39-bus New England system, the proposed scheme has a better performance than the previous methods. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Electric load shedding

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Accuracy Testing of PQ Analyzers Using the OMICRON CMC 356 23

Accuracy Testing of PQ Analyzers Using the OMICRON CMC 356

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23rd International Scientific Conference on Electric Power engineering, EPE 2023

作者： Hlavaty, Lukas Bilik, Petr VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Department of Cybernetics and Biomedical Engineering Ostrava Czech Republic

ISBN: (纸本)9798350335934

This article deals with the accuracy check of the PQ analyzers using the OMICRON CMC 356 calibrator. This article describes the principle and concept of three applications used to test the accuracy of various quantities important in PQ measurements. Furthermore, the GUI of each application, its principle, and description of functionality, software architecture, and implementation in the LabVIEW graphical programming environment are described. The purpose of the applications is the automated generation of a three-phase voltage at the output of the OMICRON CMC 356 calibrator with parameters defined by the operator to test the accuracy of the PQ analyzers. The first application is used to generate the harmonic components according to EN 50160 with definable deviations from the standard and duration intervals. The second application is to generate defined sequence of events (overvoltages, undervoltages, faults) with a definable duration. The third application is used to simulate different types of voltage fluctuations called flicker at the output of the calibrator. © 2023 IEEE.

关键词： Power quality

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