检索结果-内蒙古大学图书馆

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： El-Den, Niveen Nasr Elsharkawy, Mohamed Ghazal, Mohammed Mahmoud, Ali Sandhu, Harpal Mahdi, Hani El-Baz, Ayman Department of Computer and System Engineering Ain Shams University Egypt Department of Bioengineering University of Louisville LouisvilleKY United States Electrical Computer and Biomedical Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350368741

Accurate early diagnosis is crucial in addressing Age-related Macular Degeneration (AMD), a chronic retinal disease that is a leading cause of blindness among the elderly. Medical imaging, particularly fundus imaging, is essential in facilitating timely detection and intervention. Due to the variability in image sizes within our dataset, this paper introduces the SABiT-MNet model, which effectively discriminates between healthy retinas, dry AMD, and wet AMD. The model integrates a novel scale-adaptive (SA) approach by combining an autoencoder with Big Transfer (BiT) as its backbone. Unlike traditional resizing methods, which often result in the loss of critical diagnostic information, the SA model dynamically adjusts to varying image sizes, preserving key retinal features essential for accurate diagnosis. The primary aim of this architecture is to retain crucial details in fundus images to ensure precise classification. In this study, 648 subjects were recruited through the Comparisons of AMD Treatments Trials study group, sponsored by the University of Pennsylvania. Experimental results demonstrate that the proposed SABiT-MNet model outperforms state-of-the-art approaches, including transformer-based models, achieving superior diagnostic accuracy. The model recorded performance metrics of 94% accuracy, 97% sensitivity, and 93.94% specificity. To further validate the robustness of the system, we tested it on the public ODiR dataset, where it achieved similarly promising results, confirming the effectiveness of our approach. © 2025 IEEE.

关键词： AMD Deep Learning fundus photography

来源：评论

学校读者我要写书评

暂无评论

A Novel Investigation on Multi-Sensor Signal Signatures for Induction Motors Diagnostics

A Novel Investigation on Multi-Sensor Signal Signatures for ...

引用

2022 International Conference on electrical Machines, ICEM 2022

作者： Minervini, Marcello Frosini, Lucia Mantione, Lorenzo University of Pavia Computer and Biomedical Engineering Department of Electrical Pavia Italy

ISBN: (数字)9781665414326

ISBN: (纸本)9781665414326

Multi-sensor diagnostics for induction motors can provide numerous signal signatures. In this work, novel diagnostic signatures in the time and frequency domain are shown, for the first time, in stray flux, stator current and vibration. The time domain envelope of the stray flux can give information on the slip of the machine. Moreover, new observations on the waveform are highlighted to describe peculiar features of the stray flux. A study on the phase shift of the electromagnetic signals in different load conditions is presented for both healthy and faulty machine with localized bearing defect. The phase-shift between the current and the radial and axial stray flux changes, demonstrating that the radial flux contains information more similar to the current. Vibration harmonics at frequencies below the rotational one are observed with faulty bearing and new signatures are proposed. © 2022 IEEE.

关键词： Frequency domain analysis

来源：评论

学校读者我要写书评

暂无评论

Bi-modal tissue-mimicking breast phantoms: comparison between the performance of agar- and gelatin-based phantoms 3

Bi-modal tissue-mimicking breast phantoms: comparison betwee...

引用

3rd URSI Atlantic and Asia Pacific Radio Science Meeting, AT-AP-RASC 2022

作者： Di Meo, Simona Cannata, Alessia MacChello, Chiara Morganti, Simone Pasian, Marco Matrone, Giulia University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia Italy

ISBN: (纸本)9789463968058

Tissue-mimicking phantoms represent a key point for the development of biomedical systems for diagnostic imaging. In this paper, new recipes for tissue-mimicking breast phantoms are proposed and tested, both dielectrically and mechanically. Phantoms mimicking human breast neoplastic tissues are considered, as they are anatomically stiffer than the surrounding healthy tissues. In our recipes, only cheap, easy-to-manage and safe components are involved, and the performance of two solidifying agents (i.e., gelatin and agar) are evaluated both from a dielectric and a mechanical point of view. Dielectric measurements are performed from 500 MHz to 40 GHz, and mechanical tests are performed with the unconfined compression approach, using a preload of 0.2 N and a test speed of 0.5 mm/min. This analysis shows that agar is more suitable for the fabrication of stiffer phantoms as compared to gelatin. © 2022 URSI.

关键词： Phantoms

来源：评论

学校读者我要写书评

暂无评论

Filtering Trans-Impedance Amplifiers: from mW of Power to GHz of Bandwidth 43

Filtering Trans-Impedance Amplifiers: from mW of Power to GH...

引用

43rd Annual IEEE Custom Integrated Circuits Conference, CICC 2022

作者： Miral, Nimesh Nadishka Sohal, Karan Manstretta, Danilo Castello, Rinaldo University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia Italy

Trans-impedance amplifiers (TIAs) are used as building blocks in many applications: from wireless transceivers to qubit manipulation and readout in quantum computing [1] or as amplifying circuits in fiber optics recei... 详细信息

ISBN: (纸本)9781665407564

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Different Magnet Materials and Skewed Geometries for IPMSM at High Speed

Evaluation of Different Magnet Materials and Skewed Geometri...

引用

2022 International Conference on electrical Machines, ICEM 2022

作者： Mantione, Lorenzo Frosini, Lucia Minervini, Marcello University of Pavia Computer and Biomedical Engineering Department of Electrical Pavia Italy

ISBN: (数字)9781665414326

ISBN: (纸本)9781665414326

In this paper, an investigation on various permanent magnet materials and rotor geometries for Interior Permanent Magnet Synchronous Motors is presented, to achieve optimal performance both at base speed and in a wide flux-weakening region. The research starts from the updated state of the art, which suggests single V-shape magnets, to obtain a good compromise between performance and industrial interest, and rotor step-skewing. To design, analyze and compare several rotor topologies, two software (FluxMotor and Flux2D) have been used. The results highlight that less performing magnet materials are not convenient, due to the need of greater mass of material to reach the same performance, while a simple three steps skewing, combined with the best choice of rotor geometry, provides a strong reduction of torque ripple, which remains low up to 8000 rpm. © 2022 IEEE.

关键词： Finite element method

来源：评论

学校读者我要写书评

暂无评论

Analysis of Brain Excitability After Transcranial Direct Current Stimulation and Brain-computer Interface Based on Motor Imagery on a Post-stroke Patient 9th

Analysis of Brain Excitability After Transcranial Direct Cu...

引用

9th Latin American Congress on biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on biomedical engineering, CBEB 2022

作者： Silva, Leticia Lima, Jéssica Schreider, Sheila Delisle-Rodriguez, Denis Krishnan, Sridhar Bastos-Filho, Teodiano Postgraduate Program in Electrical Engineering Universidade Federal do Espirito Santo Vitoria Brazil Postgraduate Program in Biotechnology Universidade Federal do Espirito Santo Vitoria Brazil Edmond and Lily Safra International Institute of Neurosciences Instituto Santos Dumont Macaiba Brazil Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada

ISBN: (纸本)9783031494062

Stroke is a neurological syndrome that may cause severe cognitive and motor impairments for survival. Alternative rehabilitation techniques have been developed to recover lower-limb movements and gait of post-stroke patients, such as Motor Imagery (MI)-based Brain-computer Interfaces (BCIs), Virtual Reality (VR), and robotic devices. Transcranial Direct Current Stimulation (tDCS) is a non-invasive technique to stimulate the brain and modulate cortical excitability. This study aims to analyze the short-term effects of tDCS compared to sham stimulation before a lower-limb MI-BCI pedaling training (through a robotic monocycle) task in a patient with subacute stroke. We studied a post-stroke patient with 2 months of ischemic stroke and right hemiparesis who was submitted to the following tasks: active pedaling, sham tDCS and MI-BCI, and tDCS and MI-BCI. We evaluated the relative power around the foot area (Cz electrode), and a significant (p-value © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Brain computer interface

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Applied to Electronic Health Record Data: Opportunities and Challenges

Machine Learning Applied to Electronic Health Record Data: O...

引用

16th International Joint Conference on biomedical engineering Systems and Technologies, BIOSTEC 2023

作者： Bellazzi, Riccardo Department of Electrical Computer and Biomedical Engineering University of Pavia IRCCS ICS Maugeri Pavia Italy

The increasing success of application of machine and deep learning in many areas of medicine, in particular in imaging diagnostics (Rajpurkar et al., 2020), is pushing towards the implementation of AI-based approaches to extract knowledge from health records data (EHR) (Li et al., 2020). The potential of sophisticated strategies to derive regularities from very large collection of textual data, such as language models, is also generating strong expectations about the capability of extracting information unstructured textual notes as well as in generating biomedical texts (Segura-Bedmar et al., 2022;Luo et al., 2022). The COVID-19 pandemics, being one of the most relevant healthcare challenges synchronously happened worldwide, has represented a strong push towards the timely use of EHR data to characterize the clinical course of the COVID-19 disease. Successful examples are represented by cooperative international efforts, such as the Consortium for Clinical Characterization of COVID-19 by EHR (4CE) initiative (Brat et al., 2020). However, EHR data are particularly complex, due to their multifaceted nature and inherent relationship with the health care organizations generating the data. In a recent paper, Kohane and colleagues summarizing the experience carried on in leading 4CE have identified six main challenges that have proven to be crucial for running EHR-based projects (Kohane et al., 2021): i) data completeness, ii) data collection and handling, iii) data type, iv) robustness of methods against EHR variability (within and across institutions, countries, and time), v) transparency of data and analytic code, and vi) the need of multidisciplinary approach. Those topics, in the context of structured EHR data, have been recently further systematized by a consensus paper by the European Society of Cardiology and the BigData(S?Heart consortium that has defined the CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical re

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Development of Antimicrobial Envelope for RFID Card 20

Development of Antimicrobial Envelope for RFID Card

引用

20th International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2023

作者： Paripurana, Sukritta Kittiamornkul, Navapadol Watcharakitchakorn, Orrathai Keawon, Rapeepan King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand Christian University of Thailand Faculty of Health Sciences Department of Biomedical Engineering Thailand Silpakorn University Faculty of Engineering and Industrial Technology Department of Electrical Engineering Thailand

ISBN: (纸本)9798350310467

This paper proposes the development of an RFID envelope coated with an antimicrobial material that can stop microorganisms' growth while the card is still regularly used. Copper is chosen as the antimicrobial material for coating on an envelope made of polyethylene terephthalate (PET) by using DC sputtering. The antimicrobial ability of the proposed envelope is investigated against Escherichia coli (E. coli). The result shows that the survival time of E. coli on the proposed envelope is decreased compared with the PET envelope without the copper thin film coated on. Besides its antimicrobial quality, copper can let radio frequency pass through. Thus, the effectiveness of electromagnetic wave transmission through the proposed envelope coated with different thickness of a copper thin film is tested. To evaluate the performance of the proposed envelope, three experiments which cover the test of the antimicrobial ability of copper thin film, the resistance of copper thin film, and performance of RF transmission of RFID reader and tag are conducted. The results of the three experiments show that a copper thin film can prevent the microorganisms' growth, the resistance of the copper thin film is decreasing while the thickness of the copper thin film is increasing, and the radio frequency can pass though the proposed envelope. © 2023 IEEE.

关键词： Escherichia coli

来源：评论

学校读者我要写书评

暂无评论

Understanding Acoustic Phenomena in Stenosed Coronary Arteries through Bond Graph Modeling of Sound Generation 46

Understanding Acoustic Phenomena in Stenosed Coronary Arteri...

引用

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

作者： Sandoval, Loreto Rojas Ulloa, René Araya Da Silva, Ana Karoline Almeida De Almeida Nunes, Gustavo Adolfo Marcelino Faria, Rafael Mendes Sepúlveda, José Parra Da Costa, Lindemberg Barreto Mota Acevedo, Luca Rubilar Rosa, Mário Fabrício Fleury Pino, Esteban J. De Siqueira Rodrigues Fleury Rosa, Suélia Universidad de Concepción Electrical Engineering Department Chile University of Brasilia Mechanical Engineering Department Distrito Federal Brasilia70910-900 Brazil University of Brasilia Postgraduate Program in Biomedical Engineering Distrito Federal Brasilia70910-900 Brazil

ISBN: (纸本)9798350371499

Coronary artery stenosis is characterized by the obstruction or narrowing of coronary arteries, impairing blood flow to the cardiac muscle. Cardiovascular diseases rank among the leading global causes of death. Understanding the mechanisms, risk factors, and impacts of coronary artery stenosis (CAD) is essential for developing effective strategies for prevention, early diagnosis, and treatment, aiming to enhance cardiovascular health and reduce adverse consequences associated with this condition. Previous studies explore the potential of acoustic devices in non-invasive CAD detection through the analysis of cardiac sounds. A theoretical model utilized a cardiac microphone and signal processing to generate sounds in partially obstructed coronary arteries. Emphasizing the model's sensitivity to geometric and dynamic parameters, this article integrates Bond Graph (BG) models into the analog sound circuit, aiming to develop a dynamic representation of biological processes in complex systems like coronary arteries. This research seeks to construct a comprehensive mathematical model using a state-space approach to enhance understanding, diagnostics, and interventions in cardiovascular conditions. The utilization of BG demonstrated notable similarity to the pathology of the disease, providing an accurate representation of its effects. The model's sensitivity to geometric and dynamic parameters allowed an in-depth understanding of the specific physiological characteristics of the disease, highlighting its ability to reproduce patterns observed in patients with CAD. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

A machine learning-guided design and manufacturing of wearable nanofibrous acoustic energy harvesters

引用

Nano Research 2024年第10期17卷 9181-9192页

作者： Negar Hosseinzadeh Kouchehbaghi Maryam Yousefzadeh Aliakbar Gharehaghaji Safoora Khosravi Danial Khorsandi Reihaneh Haghniaz Ke Cao Mehmet R.Dokmeci Mohammad Rostami Ali Khademhosseini Yangzhi Zhu Terasaki Institute for Biomedical Innovation Los AngelesCA 91367USA Department of Textile Engineering Amirkabir University of Technology(Tehran Polytechnic)Hafez Avenue*** TehranIran Department of Electrical and Computer Engineering University of British ColumbiaVancouverBC V6T1Z4Canada Chemical Sciences Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Department of Computer Science University of Southern CaliforniaLos AngelesCA 90007USA

Nanofibrous acoustic energy harvesters(NAEHs)have emerged as promising wearable platforms for efficient noise-to-electricity conversion in distributed power energy systems and wearable sound amplifiers for assistive listening ***,their reallife efficacy is hampered by low power output,particularly in the low-frequency range(<1 kHz).This study introduces a novel approach to enhance the performance of NAEHs by applying machine learning(ML)techniques to guide the synthesis of electrospun polyvinylidene fluoride(PVDF)/polyurethane(PU)nanofibers,optimizing their application in wearable *** use a feed-forward neural network along with solving an optimization problem to find the optimal input values of the electrospinning(applied voltage,nozzle-collector distance,electrospinning time,and drum rotation speed)to generate maximum output performance(acoustic-to-electricity conversion efficiency).We first prepared a dataset to train the network to predict the output power given the input variables with high *** introducing the neural network,we fix the network and then solve an optimization problem using a genetic algorithm to search for the input values that lead to the maximum energy harvesting *** ML-guided wearable PVDF/PU NAEH platform can deliver a maximal acoustoelectric power density output of 829μW/cm^(3) within the surrounding noise *** addition,our system can function stably in a broad frequency(0.1-2 kHz)with a high energy conversion efficiency of 66%.Sound recognition analysis reveals a robust correlation exceeding 0.85 among lexically akin terms with varying sound intensities,contrasting with a diminished correlation below 0.27 for words with disparate semantic ***,this work provides a previously unexplored route to utilize ML in advancing wearable NAEHs with excellent practicability.

关键词： wearable electronics acoustic energy harvester machine learning piezoelectric nanogenerator electrospun nanofiber

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：