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11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Bakr, Hend A. Salama, Ahmed M. Fares, Ahmed Zaky, Ahmed B. Cairo University Biomedical Engineering Program Faculty of Engineering Giza Egypt Benha University Computer Systems Engineering Program Faculty of Engineering at Shoubra Banha Egypt Computer science and information technology Programs Alexandria Egypt Benha University On leave from Computer Systems Engineering Program Faculty of Engineering at Shoubra Egypt

ISBN: (纸本)9798350369328

Physician scheduling is a critical task that impacts the quality of patient care, staff satisfaction, and operational efficiency in healthcare institutions. The traditional approach to physician scheduling is manual and time-consuming, which can result in errors, staff burnout, and suboptimal schedules. To address these challenges, researchers have turned to optimization techniques like CSP, which has shown promise in solving physician scheduling problems. This paper reviews the existing literature on CSP for physician scheduling and highlights the benefits and limitations of this approach. CSP's benefits include generating schedules quickly and efficiently, incorporating complex constraints and preferences, and handling changes and disruptions in real time. However, CSP also has some limitations, such as the need for a formalized model and the fact that it may not always generate the most intuitive schedules. Overall, the findings suggest that CSP is a promising approach to physician scheduling that can produce high-quality schedules while minimizing staff burnout and improving operational efficiency. © 2023 IEEE.

关键词： Constraint satisfaction problems

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Neuromodulation of the peripheral nervous system:Bioelectronic technology and prospective developments

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BMEMat(biomedical engineering Materials) 2024年第1期2卷 88-114页

作者： Hayoung Song Moohyun Kim Enji Kim Jakyoung Lee Inhea Jeong Kyeonghee Lim Seoung Young Ryu Myoungjae Oh Younhee Kim Jang-Ung Park Department of Materials Science and Engineering Yonsei UniversitySeoulSouth Korea Center for Nanomedicine Institute for Basic Science(IBS)SeoulSouth Korea Department of Neurosurgery Yonsei University College of MedicineSeoulSouth Korea Graduate Program of Nano Biomedical Engineering(NanoBME) Advanced Science InstituteYonsei UniversitySeoulSouth Korea

The peripheral nervous system(PNS)is a fascinatingly complex and crucial component of the human body,responsible for transmitting vital signals throughout the body's intricate network of *** efficient functioning is paramount to our health,with any dysfunction often resulting in serious medical conditions,including motor disorders,neurological diseases,and psychiatric *** strides in science and technology have made neuromodulation of the PNS a promising avenue for addressing these health *** involves modifying nerve activity using a range of techniques,such as electrical,chemical,optical,and mechanical *** plays a critical role in this effort,allowing for precise,controlled,and sustained stimulation of the *** paper provides an overview of the PNS,discusses the current state of neuromodulation devices,and presents emerging trends in the field,including advances in wireless power transfer and materials,that are shaping the future of neuromodulation.

关键词： bioelectronics neuromodulation peripheral nervous system

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A motion-level-aware denoising framework for x-ray fluoroscopic images

A motion-level-aware denoising framework for x-ray fluorosco...

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Medical Imaging 2023: Physics of Medical Imaging

作者： Jo, Geonhui Jang, Minhee Jeon, Sun-Young Kim, Wonjin Choi, Jang-Hwan Department of Computer Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of

ISBN: (纸本)9781510660311

Fluoroscopy in a low-dose tube output is used to reduce the damage associated with radiation exposure. However, lowering the radiation dose inevitably increases random noise in x-ray images, resulting in poor diagnostic image quality, which requires noise reduction for accurate diagnosis. Also, in the case of non-static objects, the image is blurred due to motion. The most-used denoiser with a recursive filter (RF) preserves details well when applied to temporal data, but it is vulnerable to motion blur. Existing convolutional neural network (CNN)-based algorithms with single-frame input cannot use the temporary context, and others with multi-frame input are good for motion detection but poor for detail preservation. Therefore, we propose a motion-level-aware denoising framework to combine the results of RF- and CNN-based algorithms depending on the pixel-wise magnitude of motion to complement each other. The data we use are fluoroscopy images taken in continuous time, and we aim at many-to-one so that one frame is denoised by considering sequential frames. Also, since both RF- and CNN-based algorithms used in our architecture are many-to-one methods, they can consider spatiotemporal information. In the multi-frame input, the difference in intensity of each pixel between frames is calculated to obtain a moving map. Depending on the factor value from the moving map, the final image is obtained by reflecting the outputs of the RF- and CNN-based algorithms. If the factor value is high, the pixel intensity of the final image is like the CNN-based output, which is good for motion detection, and vice versa, it more reflects the intensity of RF output, which is excellent in perceptual quality. Therefore, it prevents motion blur and does not over-smooth microdetails, such as bones and muscles. The results show that combining the two outputs together records higher peak signal-to-noise ratio (PSNR) and has better perceptual quality for diagnosis than using only one method. F

关键词： Deep learning

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NIR-Responsive Methotrexate-Modified Iron Selenide Nanorods for Synergistic Magnetic Hyperthermic, Photothermal, and Chemodynamic Therapy

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ACS Applied Materials and Interfaces 2024年第20期16卷 25622-25636页

作者： Thirumurugan, Senthilkumar Muthiah, Kayalvizhi Samuvel Lin, Yu-Chien Dhawan, Udesh Liu, Wai-Ching Wang, An-Ni Liu, Xinke Hsiao, Michael Tseng, Ching-Li Chung, Ren-Jei No. 1 Section 3 Zhongxiao East Road Taipei10608 Taiwan Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom Faculty of Science and Technology Technological and Higher Education Institute of Hong Kong Hong Kong New Territories999077 Hong Kong Scrona AG Grubenstrasse 9 Zürich8045 Switzerland College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Genomics Research Center Academia Sinica Taipei115 Taiwan Department and Graduate Institute of Veterinary Medicine School of Veterinary Medicine National Taiwan University Taipei10617 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Research Center of Biomedical Device College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Taipei10608 Taiwan

Breast cancer is a malignant tumor with a high mortality rate among women. Therefore, it is necessary to develop novel therapies to effectively treat this disease. In this study, iron selenide nanorods (FeSe2 NRs) were designed for use in magnetic hyperthermic, photothermal, and chemodynamic therapy (MHT/PTT/CDT) for breast cancer. To illustrate their efficacy, FeSe2 NRs were modified with the chemotherapeutic agent methotrexate (MTX). MTX-modified FeSe2 (FeSe2-MTX) exhibited excellent controlled drug release properties. Fe2+ released from FeSe2 NRs induced the release of •OH from H2O2 via a Fenton/Fenton-like reaction, enhancing the efficacy of CDT. Under alternating magnetic field (AMF) stimulation and 808 nm laser irradiation, FeSe2-MTX exerted potent hyperthermic and photothermal effects by suppressing tumor growth in a breast cancer nude mouse model. In addition, FeSe2 NRs can be used for magnetic resonance imaging in vivo by incorporating their superparamagnetic characteristics into a single nanomaterial. Overall, we presented a novel technique for the precise delivery of functional nanosystems to tumors that can enhance the efficacy of breast cancer treatment. © 2024 The Authors. Published by American Chemical Society

关键词： Magnetic resonance imaging

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A novel methodology based on static visual stimuli and kinesthetic motor imagery for upper limb neurorehabilitation

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Research on biomedical engineering 2024年第3-4期40卷 687-700页

作者： Bastos-Filho, T.F. Villa-Parra, A.C. Guerrero-Méndez, C.D. González-Cely, A.X. Blanco-Díaz, C.F. Delisle-Rodríguez, D. Igasaki, T. Vitoria Brazil Biomedical Engineering Research Group Salesian Polytechnic University Cuenca Ecuador Postgraduate Program in Neuroengineering Edmond and Lily Safra International Institute of Neurosciences Santos Dumont Institute Macaiba Brazil Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan

Purpose: This work proposes a protocol to be used in a Brain-Computer Interface (BCI) for hand and finger movement rehabilitation aimed at post-stroke patients. This strategy is based on Electroencephalography (EEG) and uses concepts of both Static Visual Stimuli (SVS) of the own subject’s hand (OwnSVS) and Kinesthetic Motor Imagery (KMI) to improve the motor task recognition of the same limb. Methods: The protocol proposed here takes into account several aspects, such as physical rehabilitation strategies, Active Hand Orthosis (AHO) — represented by a robotic glove —, and the acquisition of the EEG signal over the brain motor area. Power Spectral Density (PSD) and Riemannian Geometry (RG) are used for feature extraction in this work, considering Mu (μ, 8–12 Hz), Low-Beta (Low-β, 13–17 Hz) and High-Beta (High-β, 18–24 Hz) frequency bands. Moreover, a feature selection stage using Pair-Wise Feature Proximity (PWFP) is also used before input to a Machine Learning (ML) classifier. Here, Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Decision Tree (DT) are compared. Results: As results, evaluated in 10 healthy subjects, features using PSD-PWFP and kNN achieved a maximum ACC of 89.81% (with AHO movements), improving by 3% the standard protocol (without AHO movements). Conclusions: The findings of this work indicate that AHO movement assistance can improve the recognition of hand opening and closing MI tasks, which can be implemented in the design of robotic BCI controllers for hand and finger movement neurorehabilitation in stroke patients. © The Author(s), under exclusive licence to The Brazilian Society of biomedical engineering 2024.

关键词： Electroencephalography

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Mathematical Modeling and Characterization of a Wearable Soft Robotic Device for Muscle Mechanotherapy 46

Mathematical Modeling and Characterization of a Wearable Sof...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Ticllacuri, Victor Mio, Renato Biomedical Engineering Program PUCP-UPCH Lima Peru Pontificia Universidad Catolica del Peru Laboratory of Biomechanics and Applied Robotics Lima Peru Universidad Peruana Cayetano Heredia Laboratory of Biomedical Engineering Lima Peru University of Bayreuth Digital Health with a Focus on Data Science Germany

ISBN: (纸本)9798350371499

Treatments of disuse-induced muscle atrophy entail unmet clinical needs due to the lack of medical devices capable of mimicking physicians manual therapies. Therefore, in this paper we develop and model a wearable soft pneumatic elastomeric actuator to perform deep cyclic compression stimuli on human soft tissues for muscle rehabilitation by mechanotherapy. Static and dynamic characterization of the prototype demonstrate a 2.5 mm active deformation at 100 kPa with 600 mm3/s and a 5 Hz bandwidth. We estimate the transfer function of the experimentally acquired pressure, flow and deformation signals, processed by a Gaussian kernel-based approach. Our mathematical model accurately describes the actuator behavior and enables to extract its mechanical parameters. Then, through computational simulations, we illustrate its efficacy in emulating multiple complex bio-inspired movements. Our proposed methodology aims to improve the control efficiency in wearable soft robotics for muscle atrophy treatment. © 2024 IEEE.

关键词： Pneumatic actuators

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Targeting glial metabolism in neurodegenerative diseases:detail matters

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Neural Regeneration Research 2023年第11期18卷 2393-2394页

作者： Ruqayya Afridi Kyoungho Suk Department of Pharmacology School of MedicineKyungpook National UniversityDaeguSouth Korea Department of Biomedical Sciences BK21 PLUS KNU Biomedical Convergence ProgramSchool of MedicineKyungpook National UniversityDaeguSouth Korea Brain Science and Engineering Institute Kyungpook National UniversityDaeguSouth Korea

Neurodegenerative diseases,a group of disorders associated with advanced age,are typified by the disease-specific accumulation of mutant proteins and *** decades,treatment modalities for these disorders have focused on addressing neuronal malfu nction,which has resulted in the failure of *** studies have identified the crucial role of glial cells in exacerbating neurodegenerative processes via the release of neuroinflammatory ***,the major immune component of the central nervous system (CNS),undergo numerous phenotypic transitions and regulate the outcomes of various pathologies (Afridi et al.,2022).

关键词： degenerative metabolism diseases

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3D Image Generation from X-ray Projections Using Generative Adversarial Networks 23

3D Image Generation from X-ray Projections Using Generative ...

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23rd IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2023

作者： AlShurbaji, Mohammad Dhou, Salam Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Engineering American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798350393118

The human brain can effortlessly imagine a 3D image from only 2D images with a little expertise and imagination, but for machines, this is not a trivial task. Because of this, reconstructing 3D images from 2D ones is a hot topic and has many applications. In this paper, we propose a Generative Adversarial Network (GAN)-based approach that generates CT-like images using pairs of orthogonal X-ray projections taken from different angles. In this work, a variety of orthogonal pairs from different angles, ranging from 0 &90 to 60 &150, were considered as input to the 3D image generation model. The effectiveness of the proposed method was assessed by measuring the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR), which resulted in values of 0.641 and 29.21, respectively. Furthermore, the model's ability to capture the respiratory motion in the input projections and reflect it in the generated images was also assessed. This work demonstrated the feasibility of generating CT-like images from X-ray projections captured from different orthogonal angles taking into consideration the respiratory motion exhibited in these projections. © 2023 IEEE.

关键词： Generative adversarial networks

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View-Invariant Object Representation in Anterior and Posterior Inferotemporal Cortex: A Machine Learning Approach

SSRN

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SSRN 2025年

作者： Okamura, Jun-Ya Fukano, Daisuke Wang, Gang Information Science and Biomedical Engineering Program Graduate School of Science and Engineering Kagoshima University Kagoshima890-0065 Japan

Inferotemporal (IT) cortex is the final visual area in the ventral stream where object information is processed. Previous electrophysiological studies showed viewing angle tolerance of 30-60° of single IT cells to the objects experienced in discrimination at each of several viewing angles, and to the objects experienced in learning association of different views. IT is divided into anterior (cytoarchitectonic area TE) and posterior (TEO) parts. It was reported that single cells in area TE showed the viewing angle tolerance while those in area TEO did not. In the present study population activities were compared between cell populations in area TE and those in area TEO using machine learning algorithm. An object set consisted of four similar objects created by deforming a prototype object, and four views each separated by 30°. A population vector was created by aligning responses of the cells to each object image. A classifier was trained by support vector machine (SVM) to create a hyperplane that separated one object from the other three objects at the same viewing angles, and then tested by response vectors to the object images at different viewing angles. In area TE, dynamics of the performance evaluated by d’ showed viewing angle tolerance of 30-60° to the objects with prior experience in learning association of different views. In area TEO, populations of the cells did not show the viewing angle tolerance. Significant increase of the d’ values in area TE in the late time period for the objects with prior experience in learning association of different views may suggest view-invariance is more represented in late time period than early time period. These results suggest that viewpoint invariance is expressed more strongly in the TE region, providing new insights into the neural basis of object recognition © 2025, The Authors. All rights reserved.

关键词： Support vector machines

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Haptic Interfaces Integration in Upper Limb Rehabilitation 3

Haptic Interfaces Integration in Upper Limb Rehabilitation

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3rd International Congress of biomedical engineering and Bioengineering, CIIBBI 2024

作者： Del Pilar Rubiano Giraldo, Andrea Dario Vargas Cardona, Hernan Felipe Amador, Andres Cobo, Estefania Montoya Pontificia Universidad Javeriana Cali Biomedical Engineering Student Cali Colombia Pontificia Universidad Javeriana Cali Applied Mathemathics Program Director Cali Colombia Pontificia Universidad Javeriana Cali MSc. Biomedical Science - Research Group Bchs Cali Colombia

ISBN: (纸本)9798331532352

The activities of daily living (ADLs) encompass self-care tasks that often rely on upper limb function. Stroke, or cerebrovascular accident (CVA), and musculoskeletal injuries (MSIs) can compromise these ADLs, necessitating rehabilitation therapy. However, many individuals exhibit poor adherence to prescribed therapies, which exacerbates their conditions and further impairs upper limb functionality. To tackle this challenge, we devised a software tool that integrates a mathematical model with haptic interfaces within a Unity-developed game for the Meta Quest 2 platform. Validation by physiotherapists indicated successful results, affirming its utility as an effective tool for upper limb rehabilitation therapy. © 2024 IEEE.

关键词： Haptic interfaces

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