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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Samolis, Panagis D. Zhu, Xuedong Sander, Michelle Y. Department of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Division of Materials Science and Engineering Boston University BrooklineMA02446 United States

ISBN: (纸本)9781957171258

关键词： Infrared devices

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Improving the Cooling Time of Twisted Coiled Actuators in Soft Robotics

Improving the Cooling Time of Twisted Coiled Actuators in So...

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IEEE/RAS-EMBS International Conference on biomedical Robotics and Biomechatronics (BioRob)

作者： Alex Lizotte Parisa Daemi Brendan DiFabio Ana Luisa Trejos School of Biomedical Engineering (BME) Western University BME Western University Department of Electrical and Computer Engineering (ECE) Department of Mechanical and Materials Engineering Mechatronics Program Western University ECE and BME Western University

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Fabric cooling channels for twisted coiled actuators (TCAs) were recently proposed to achieve the required response times for motion assistance in a manner suitable for soft wearable robotic devices. While previous work demonstrated that the fabric channel reduced the cooling time by 42% in comparison to the same TCA without the cooling channel, the TCAs were still not cooled quickly enough to support human motion. Therefore, in this paper, two variations to the channel are proposed to further reduce the cooling time of the TCAs. The variations include unsealing the inlet and adding vents along the length of the channel to take advantage of air entrainment and natural convection. While both variations reduced the cooling time on their own, when they were employed together there was a 34% reduction in cooling time compared to the original channel design ( $19.1 \pm 2.4\ \mathrm{s}$ vs. $13.5 \pm 0.9\ \mathrm{s}, \mathrm{p} < 0.001$ ). This decrease occurred without any significant differences in the stroke or heating time of the TCA. The modified channel was then compared to the TCA without the cooling apparatus and the cooling time was reduced by 57% ( $25.1 \pm 1.7\ \mathrm{s}$ vs. $14.0 \pm 1.2\ \mathrm{s}, \mathrm{p} < 0.001)$ . This work advances the development of a cooling system for TCAs, making it suitable for soft wearable robotic devices by improving portability, and thereby enabling their use in wearable devices for rehabilitation applications.

关键词： Heating systems Actuators Cooling Vents Soft robotics Fabrics Time factors Wearable devices Convection Testing

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Assessing the impact of a magnetic field generator on fluoroscopic image quality

Assessing the impact of a magnetic field generator on fluoro...

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Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Mirzaei, Mateen Garland, Lisa M. Peters, Terry M. Cunningham, Ian A. Chen, Elvis C.S. Department of Medical Biophysics Western University London Canada Imaging Laboratories Robarts Research Institute London Canada School of Biomedical Engineering Western University London Canada Department of Electrical and Computer Engineering Western University London Canada

ISBN: (纸本)9781510685949

Many spinal operations are performed using fluoroscopic guidance due to its excellent visualization of osseous structures and surgical instrumentation in real-time, however, its efficacy is conditional on accurate needle placement. Image-guided surgical navigation systems allow for intraoperative and continuous localization of surgical tools with respect to patient anatomy, leading to significantly improved needle placement accuracy. Magnetic navigation systems require a field generator (FG) whose placement must be near the patient and may partially obstruct the x-ray beam, causing image artifacts and degraded image quality. Northern Digital Inc. has developed a radiolucent FG (RLFG) prototype to reduce image artifacts, however, the X-ray photon scatter interactions from the RLFG may reduce image contrast, add noise and decrease spatial resolution. These scatter interactions can be assessed in terms of the scatter-to-primary ratio (SPR) and its effect on image quality can be described using the modulation transfer function (MTF) and the generalized detective quantum efficiency (DQE). SPR measurements of a 20 cm water phantom and surgical table were taken with and without the RLFG using a slanted-edge technique as described by Garland and Cunningham, as well as the SPR measurements of the isolated RLFG and isolated water phantom. MTF and generalized DQE measurements of the imaging system were taken with and without the RLFG using the commercially available DQEPro (DQE Instruments, Ontario, Canada). SPR measurments demonstrated an 8 % average increase when the RLFG was added underneath the surgical table, and the SPR of the water phantom was on average 5 times larger than the SPR of the RLFG. Therefore, the photon scatter interactions within the RLFG would likely cause minimal image quality deterioration, especially in comparison to a patient-representing water phantom. Introducing the RLFG in the imaging system demonstrates no practically significant difference in MT

关键词： Damage detection

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MODELING THE HODGKIN-HUXLEY NEURON TO DETERMINE NEURONAL ENERGY CONSUMPTION EFFICIENCY AND OXYGEN CONSUMPTION VALUES

Biomedical Sciences Instrumentation

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biomedical Sciences Instrumentation 2022年第2期58卷 50-58页

作者： Enochson, Avery Ewert, Daniel Mitar, Dipankar Striker, Ryan Cleveland, Jerika Wolf, Henry Gieser, Anna Braaten, Ben Allen, Jeffery Allen, Monica Department of Integrated Engineering at Iron Range Engineering Program of Minnesota State University Mankato MN United States Department of Computer Science and Computer Engineering University of Wisconsin – La Crosse La CrosseWI United States Department of Electrical and Computer Engineering North Dakota State University FargoND United States Air Force Research Laboratory Munitions Directorate Eglin Air Force Base Eglin AFB FL United States

Understanding neuronal structure and function is essential to studying the human brain. The goal of this project was to create a model of human brain neurons that accurately reflects neuronal function, energy consumption, and oxygen consumption. Extensive work has been performed on the Hodgkin-Huxley model of neurons to accurately model neuronal firing. This study focuses on the creation of a model of the Hodgkin-Huxley neuron in MATLAB with the assistance of the DynaSim toolbox. This model was used to compute values and using another model the energy efficiency of the neuron was calculated and related to oxygen consumption, which then corresponds to Blood Oxygenation Level Dependent (BOLD) imaging in fMRI. The results of this study provide detailed visual and technical information about how the brain neurons function, which is crucial to the further development in brain imaging techniques and to further our understanding of why and how our complex brains function. © 2022 IAE All rights reserved.

关键词： Neurons

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The Privacy Attitudes Questionnaire (PAQ) Turned 20: What’s Next for a Generalized Measure of Privacy Attitudes? 67th

The Privacy Attitudes Questionnaire (PAQ) Turned 20: What’s...

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67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023

作者： Giang, Wayne C. W. Iglar, Alyssa Chignell, Mark Samavi, Reza Nathan, Kopiha Department of Industrial and Systems Engineering University of Florida GainesvilleFL United States Department of Mechanical and Industrial Engineering University of Toronto TorontoON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University TorontoON Canada Vector Institute India Healthcare Insurance Reciprocal of Canada TorontoON Canada

Attitudes and concerns related to privacy are not homogeneous, but instead differ based on the individual and context at hand. Understanding how these attitudes and concerns vary could inform product, service, and policy design. Questionnaires, such as the Privacy Attitudes Questionnaire (PAQ), can be used to evaluate and derive implications from people’s privacy orientations in numerous domains, including healthcare, social media, and e-commerce. Our objective is to refine the PAQ to reflect areas of privacy concern in today’s landscape. The panel will serve as a forum for conversation about areas of privacy concern, guided by our panelists’ expertise and questions about demographic and user considerations for the revised PAQ, a framework-inspired understanding of privacy, and privacy in healthcare. Insights and perspectives arising from the discussion panel will be considered for subsequent revisions of the PAQ. © 2023 Human Factors and Ergonomics Society.

关键词： attitudes concerns context healthcare privacy questionnaire

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Tm-doped Chirped-pulse-amplification Fiber Laser System at 1.9 μm

Tm-doped Chirped-pulse-amplification Fiber Laser System at 1...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Xu, Shutao Turnali, Ahmet Lim, Timothy Sander, Michelle Y. Department of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States Division of Materials Science and Engineering Boston University BrooklineMA02446 United States Department of Biomedical Engineering Boston University BostonMA02215 United States

We report a high-energy Tm-doped chirped-pulse-amplification fiber laser system seeded by dissipative solitons at 1902 nm. The system provides output pulses with a pulse energy of 120 nJ and a pulse duration of 940 fs... 详细信息

ISBN: (纸本)9781957171258

关键词： Fiber lasers

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SF(DA)2: SOURCE-FREE DOMAIN ADAPTATION THROUGH THE LENS OF DATA AUGMENTATION 12

SF(DA)2: SOURCE-FREE DOMAIN ADAPTATION THROUGH THE LENS OF D...

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12th International Conference on Learning Representations, ICLR 2024

作者： Hwang, Uiwon Lee, Jonghyun Shin, Juhyeon Yoon, Sungroh Division of Digital Healthcare Yonsei University Korea Republic of Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

In the face of the deep learning model's vulnerability to domain shift, source-free domain adaptation (SFDA) methods have been proposed to adapt models to new, unseen target domains without requiring access to source domain data. Although the potential benefits of applying data augmentation to SFDA are attractive, several challenges arise such as the dependence on prior knowledge of class-preserving transformations and the increase in memory and computational requirements. In this paper, we propose Source-free Domain Adaptation Through the Lens of Data Augmentation (SF(DA)2), a novel approach that leverages the benefits of data augmentation without suffering from these challenges. We construct an augmentation graph in the feature space of the pretrained model using the neighbor relationships between target features and propose spectral neighborhood clustering to identify partitions in the prediction space. Furthermore, we propose implicit feature augmentation and feature disentanglement as regularization loss functions that effectively utilize class semantic information within the feature space. These regularizers simulate the inclusion of an unlimited number of augmented target features into the augmentation graph while minimizing computational and memory demands. Our method shows superior adaptation performance in SFDA scenarios, including 2D image and 3D point cloud datasets and a highly imbalanced dataset. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Deep learning

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Comparative Analysis of Clusterization Methods Applied to a Solid-State LiDAR

Comparative Analysis of Clusterization Methods Applied to a ...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Henrique N. Poleselo Andre G. S. Conceicao Postgraduate Program in Electrical Engineering Federal University of Bahia Salvador Brazil Department of Electrical and Computer Engineering Federal University of Bahia Salvador Brazil

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Object segmentation is one of the main activities for the robot to create a sense of its environment. This task is a precursor to other activities, such as autonomous navigation in a given environment. Through sensors such as LiDAR, it's possible to generate high-resolution three-dimensional maps of the environment in which the robot is located, thus enabling their interpretation so that tasks such as object segmentation can be performed. In this article, the DBSCAN and HDBSCAN unsupervised clustering methods are explored. Results in a simulated environment in Gazebo together with Robot Operating System ROS framework for capturing sensory data from LiDAR Livox Mid-70 coupled to a mobile robot show the performance of such techniques through comparisons.

关键词： Laser radar Operating systems Clustering methods Object segmentation Robot sensing systems Sensors Mobile robots Autonomous robots

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Automatic Identification of Abnormal Lung Sounds Using Time-Frequency Analysis and Convolutional Neural Network 15

Automatic Identification of Abnormal Lung Sounds Using Time-...

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15th International Conference on Information Technology and electrical engineering, ICITEE 2023

作者： Phettom, Rattanathon Theera-Umpon, Nipon Auephanwiriyakul, Sansanee Biomedical Engineering Institute Chiang Mai University Chiang Mai Thailand Graduated School Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Chiang Mai University Chiang Mai Thailand Department of Computer Engineering Chiang Mai University Chiang Mai Thailand

ISBN: (纸本)9798350304466

This research focuses on the development of a method utilizing signal processing and machine learning techniques to identify abnormal lung sounds, specifically adventitious lung sounds, for diagnosis and monitoring. The proposed algorithm combines short-time Fourier transform (STFT) with convolutional neural networks (CNN) to automatically analyze breath sounds captured by a stethoscope. By employing a band pass filter, noise is effectively removed, facilitating accurate identification of lung sounds. The algorithm classifies abnormal lung sounds, such as crackles and wheezes, with an impressive accuracy rate of 85.27%. This research not only enhances the efficiency of physical examinations but also enables the recording and analysis of lung sounds, thereby offering valuable insights into the progression of treatments. Furthermore, the development of this medical device has significant implications for advancing human healthcare and information retrieval in the field of respiratory medicine. © 2023 IEEE.

关键词： Convolution

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Fuzzy Support Vector Regression with Grey Wolf Optimization in Stock Market Prediction

Fuzzy Support Vector Regression with Grey Wolf Optimization ...

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

作者： Titimakan Sonsupap Sansanee Auephanwiriyakul Nipon Theera-Umpon Computer Engineering Department Faculty of Engineering Graduate School Chiang Mai University Chiang Mai Thailand Computer Engineering Department Faculty of Engineering Biomedical Engineering Institute Biomedical Engineering and Innovation Research Center Chiang Mai University Chiang Mai Thailand Electrical Engineering Department Faculty of Engineering Biomedical Engineering Institute Biomedical Engineering and Innovation Research Center Chiang Mai University Chiang Mai Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

The stock market price is influenced by many factors both domestic and international factors. To help stock traders in make buying or selling decision, a stock price prediction model is needed. In this paper, a stock closing price prediction system is introduced. We utilized 17 financial factors, i.e., 8 technical analysis factors (Crude oil price, Gold spot, Thai Baht to US Dollar exchange rate, High price, Low price, Opening price, Closing price, and Volume) and 9 fundamental factors (Exponential moving average, Relative strength index, Current ratio, Return on equity ratio, Return on assets ratio, Net profit margin ratio, Debt to equity ratio, Price to earning ratio, and Price to book value) from 18 previous working days as our inputs. We then computed chaos centroids from each factor. Finally, to predict the Monday closing price, the fuzzy support vector regression with the grey wolf optimization is utilized. There are 29 companies in 6 industry groups, i.e., RESOURCE, SERVICE, INDUS, PROPCON, AGRO, and TECH, considered in this research. We found that the minimum root mean square error of the blind test set is 0.3698 and the maximum of that is 11.66. However, the prediction trend of each company is very similar to the real closing price.

关键词： Support vector machines Industries Gold Oils Companies Market research Indexes

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