检索结果-内蒙古大学图书馆

IEEE Symposium (IUS) Ultrasonics

作者： I Gede Eka Sulistyawan Daisuke Nishimae Takuro Ishii Yoshifumi Saijo Graduate School of Biomedical Engineering Tohoku University Sendai Japan Frontier Research Institute for Interdisciplinary Sciences Tohoku University Sendai Japan

We spot the insufficiency of a band-pass filter (BPF) to recognize the overlapping noise that limits the gain in signal-to-noise ratio (SNR) and produces a low contrast-to-noise ratio (CNR) image on the optical-resolution photoacoustic microscopy system (OR-PAM). To alleviate the issue, frequency decomposition was utilized to further decompose the frequency spectrum within the band-passed frequency of multiple A-lines PA signals (e.g., during C-mode imaging) into principal spectra (PS) based on the singular value decomposition (SVD) technique. We hypothesized that the PA signal could be recovered from noise by selecting the appropriate PSs. We found PSs carry better decomposing performance that splits signal and noise beyond BPF. With this property, higher CNR and doubled SNR were achieved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Wrist Joint Movements Restoration System Using Wearable Functional Electrical Stimulation with a Fuzzy-PID Controller: Design and implementation of wearable functional electrical stimulation with a Fuzzy-PID Controller which is obtained good results and can reduce the physical burden of patients 4

Design and Implementation of Wrist Joint Movements Restorati...

引用

4th International Conference on Computational Biology and Bioinformatics, ICCBB 2020

作者： Ayu Rachmawati, Dyah Arifin, Achmad Halimah Baki, Siti Leonardo, Kevin Arrofiqi, Fauzan Hilman Fatoni, Muhammad Watanabe, Takashi Institut Teknologi Sepuluh Nopember Biomedical Engineering Department Tohoku University Graduate School of Biomedical Engineering

ISBN: (纸本)9781450388443

Stroke disease is a condition that occurs when blood flow to the brain is reduced or poor caused of blockage or rupture of blood vessels. It causes parts of body that are controlled by the dead brain cannot work properly or run into paralysis. Functional Electrical Stimulation (FES) is one of method to activate sensoric-motoric system with sending electrical pulses to the specified muscle. The controller used in this study for FES is Fuzzy-PID controller. Fuzzy controller was used to determine which channel to be activated based on the amount of error, meanwhile PID controller as a feedback controller. It also has good stimulation pattern, which can determine which stimulation channel to be activated based on the amount of error. Combining Fuzzy and PID in the control system obtained good results, which the average angular error has a value less than 100 and able to produce a circular motion as desired. Further clinical test with paralyzed subjects would be next research step. © 2020 ACM.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Haptic Interfaces Integration in Upper Limb Rehabilitation

Haptic Interfaces Integration in Upper Limb Rehabilitation

引用

biomedical engineering and Bioengineering (CI-IB&BI), IEEE International Congress of

作者： Andrea Del Pilar Rubiano Giraldo Hernán Darío Vargas Cardona Andrés Felipe Amador Estefanía Montoya Cobo Biomedical Engineering Student Pontificia Universidad Javeriana Cali Cali Colombia Applied Mathemathics Program Director Pontificia Universidad Javeriana Cali Cali Colombia MSc. Biomedical Science - Research group BCHS Pontificia Universidad Javeriana Cali Cali Colombia

ISBN: (数字)9798331532352

ISBN: (纸本)9798331532369

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.

关键词： Visualization Musculoskeletal system Medical treatment Virtual environments Stroke (medical condition) User experience Haptic interfaces Trajectory Software tools biomedical engineering

来源：评论

学校读者我要写书评

暂无评论

OPTIMIZING TRADING STRATEGIES IN QUANTITATIVE MARKETS USING MULTI-AGENT REINFORCEMENT LEARNING

arXiv

引用

arXiv 2023年

作者： Zhang, Hengxi Shi, Zhendong Hu, Yuanquan Ding, Wenbo Kuruoglu, Ercan E. Zhang, Xiao-Ping Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Electrical Computer and Biomedical Engineering Ryerson University Toronto Canada

Quantitative markets are characterized by swift dynamics and abundant uncertainties, making the pursuit of profit-driven stock trading actions inherently challenging. Within this context, Reinforcement Learning (RL) - which operates on a reward-centric mechanism for optimal control - has surfaced as a potentially effective solution to the intricate financial decision-making conundrums presented. This paper delves into the fusion of two established financial trading strategies, namely the constant proportion portfolio insurance (CPPI) and the time-invariant portfolio protection (TIPP), with the multi-agent deep deterministic policy gradient (MADDPG) framework. As a result, we introduce two novel multi-agent RL (MARL) methods: CPPI-MADDPG and TIPP-MADDPG, tailored for probing strategic trading within quantitative markets. To validate these innovations, we implemented them on a diverse selection of 100 real-market shares. Our empirical findings reveal that the CPPI-MADDPG and TIPP-MADDPG strategies consistently outpace their traditional counterparts, affirming their efficacy in the realm of quantitative trading. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Examining physical activity clustering using machine learning revealed a diversity of 24-hour step-counting patterns

引用

Journal of activity, sedentary and sleep behaviors 2024年第1期3卷 19页

作者： Saida Salima Nawrin Hitoshi Inada Haruki Momma Ryoichi Nagatomi Laboratory of Health and Sports Sciences Tohoku University Graduate School of Biomedical Engineering Sendai Miyagi Japan. Laboratory of Health and Sports Sciences Tohoku University Graduate School of Biomedical Engineering Sendai Miyagi Japan. hinada@med.tohoku.ac.jp. Department of Biochemistry & Cellular Biology National Center of Neurology and Psychiatry Kodaira Tokyo Japan. hinada@med.tohoku.ac.jp. Department of Medicine and Science in Sports and Exercise Tohoku University Graduate School of Medicine Sendai Miyagi Japan. Laboratory of Health and Sports Sciences Tohoku University Graduate School of Biomedical Engineering Sendai Miyagi Japan. nagatomi@med.tohoku.ac.jp. Department of Medicine and Science in Sports and Exercise Tohoku University Graduate School of Medicine Sendai Miyagi Japan. nagatomi@med.tohoku.ac.jp.

BACKGROUND:Physical activity is a crucial aspect of health benefits in the public society. Although studies on the temporal physical activity patterns might lead to the protocol for efficient intervention/program, a standardized procedure to determine and analyze the temporal physical activity patterns remains to be developed. Here, we attempted to develop a procedure to cluster 24-hour patterns of physical activity as step counts measured with an accelerometer-based wearable sensor. METHODS:The 1 Hz step count data was collected by a hip-worn triaxial accelerometer from 42 healthy participants, comprising 35 males and 7 females, at the Sendai Oroshisho center in 2008. This is a cross sectional study using unsupervised machine learning, specifically the kernel k-means algorithm with the global alignment kernel was applied on a total of 815 days from 42 participants, and 6 activity patterns were identified. Further, the probability of each 24-hour step-counting pattern was calculated for every participant and used for spectral clustering of step-behavioral patterns. RESULTS:We could identify six 24-hour step-counting patterns and five daily step-behavioral clusters. We could further identify five step-behavioral clusters, all-day dominant (21 participants), all-day + bi-phasic dominant (8 participants), bi-phasic dominant (6 participants), all-day + evening dominant (4 participants), and morning dominant (3 participants). When the amount of physical activity was categorized into tertile groups reflecting highly active, moderately active, and low active, each tertile group consisted of different proportions of six 24-hour step-counting patterns CONCLUSIONS: Our study introduces a novel approach using an unsupervised machine learning method to categorize daily hourly activity, revealing six distinct step counting patterns and five clusters representing daily step behaviors. Our procedure would be reliable for finding and clustering physical activity patterns/behaviors

关键词： Daily step behaviors Physical activity Step-counting patterns Unsupervised machine learning

来源：评论

学校读者我要写书评

暂无评论

Application of Asymmetric Windowing Recurrence Plots in ECG Signal Encoding for Emotion Classification

Application of Asymmetric Windowing Recurrence Plots in ECG ...

引用

International Conference on biomedical engineering (IBIOMED)

作者： Noan Yaseka Pradanya Noor Akhmad Setiawan Sri Kusrohmaniah Master of Biomedical Engineering Multidiciplinary Graduate School Faculty Universitas Gadjah Mada Yogyakarta Indonesia Departement of Electrical and Information Engineering Faculty of Engineering Universitas Gadjah Mada Yogyakarta Indonesia Departement of Psychology Faculty of Psychology Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798350389265

ISBN: (纸本)9798350389272

Human emotions are influenced by various external stimuli but can often be concealed through facial expressions. Therefore, detecting emotions using physiological signals becomes a more reliable alternative, as humans cannot easily manipulate their subconscious responses. This study aims to classify human emotional states based on electrocardiogram (ECG) signals using the LeNet-5 model. The main contribution of this research is the improved accuracy in classifying valence and arousal based on ECG signals obtained from two public datasets, namely AMIGOS and DREAMER. The Asymmetric Windowing Recurrence Plots (AWRP) encoding technique is applied to transform the cardiac signals into two-dimensional (2D) images, enabling more in-depth and accurate analysis. The results show classification using the AWRP encoding technique outperforms recurrence plot performance even with a small amount of data. The accuracy results using the AWRP encoding technique were compared with the recurrence plots encoding technique. The AMIGOS dataset achieved its best accuracy with AWRP32 at 74.79%, while the DREAMER dataset achieved its best accuracy with AWRP98 at 85.69%. The results revealed that the AWRP encoding technique had a better capability than recurrence plots in transforming time series data into 2D image data.

关键词： Accuracy Sensitivity Image coding Two-dimensional displays Time series analysis Transforms Electrocardiography Sensitivity and specificity Encoding Research and development

来源：评论

学校读者我要写书评

暂无评论

A lightweight hybrid CNN-LSTM model for ECG-based arrhythmia detection

arXiv

引用

arXiv 2022年

作者： Alamatsaz, Negin Tabatabaei, Leyla s Yazdchi, Mohammadreza Payan, Hamidreza Alamatsaz, Nima Nasimi, Fahimeh The Department of Biomedical Engineering Faculty of Engineering University of Isfahan Isfahan Iran The Department of Electrical Engineering Amirkabir University of Technology Tehran Iran The Department of Biomedical Engineering New Jersey Institute of Technology Newark United States The Graduate School of Biomedical Sciences Rutgers University Newark United States

Objective: Electrocardiogram (ECG) is the most frequent and routine diagnostic tool used for monitoring heart electrical signals and evaluating its functionality. The human heart can suffer from a variety of diseases, including cardiac arrhythmias. Arrhythmia is an irregular heart rhythm that in severe cases can lead to heart stroke and can be diagnosed via ECG recordings. Since early detection of cardiac arrhythmias is of great importance, computerized and automated classification and identification of these abnormal heart signals have received much attention for the past decades. Methods: This paper introduces a light deep learning approach for high accuracy detection of 8 different cardiac arrhythmias and normal rhythm. To leverage deep learning method, resampling and baseline wander removal techniques are applied to ECG signals. In this study, 500 sample ECG segments were used as model inputs. The rhythm classification was done by an 11-layer network in an end-to-end manner without the need for hand-crafted manual feature extraction. Results: In order to evaluate the proposed technique, ECG signals are chosen from the two physionet databases, the MIT-BIH arrhythmia database and the long-term AF database. The proposed deep learning framework based on the combination of Convolutional Neural Network(CNN) and Long Short Term Memory (LSTM) showed promising results than most of the state-of-the-art methods. The proposed method reaches the mean diagnostic accuracy of 98.24%. Conclusion: A trained model for arrhythmia classification using diverse ECG signals were successfully developed and tested. Significance: Since the present work uses a light classification technique with high diagnostic accuracy compared to other notable methods, it could successfully be implemented in holter monitor devices for arrhythmia detection. © 2022, CC BY-SA.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Scalable synthesis of lipid nanoparticles for nucleic acid drug delivery using an isometric channel-size enlarging strategy

引用

Nano Research 2024年第4期17卷 2899-2907页

作者： Zesen Ma Haiyang Tong Sijin Lin Li Zhou Demeng Sun Baoqing Li Changlin Tian Jiaru Chu Department of Precision Machinery and Precision Instrumentation University of Science and Technology of ChinaHefei 230027China Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes University of Science and Technology of ChinaHefei 230027China Science Island Branch Graduate SchoolUniversity of Science and Technology of ChinaHefei 230026China Anhui Provincial Key Laboratory of High Field Magnetic Resonance Imaging High Magnetic Field LaboratoryHefei Institute of Physical ScienceChinese Academy of SciencesHefei 230031China Anhui Provincial Engineering Laboratory of Peptide Drugs University of Science and Technology of ChinaHefei 230027China School of Biomedical Engineering Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaSuzhou 215127China

Lipid nanoparticles(LNPs)have emerged as highly effective delivery systems for nucleic acid-based ***,the broad clinical translation of LNP-based drugs is hampered by the lack of robust and scalable synthesis techniques that can consistently produce formulations from early development to clinical *** this work,we proposed a method to achieve scalable synthesis of LNPs by scaling inertial microfluidic mixers isometrically in three ***,a theoretical predictive method,which controls the mixing time to be equal across different chips,is developed to ensure consistent particle size and size distribution of the synthesized *** loaded with small interfering RNA(siRNA)were synthesized at different flow rates,exhibiting consistent physical properties,including particle size,size distribution and encapsulation *** work provides a practical approach for scalable synthesis of LNPs consistently,offering the potential to accelerate the transition of nucleic acid drug development into clinical application.

关键词： lipid nanoparticles nucleic acid delivery microfluidics scalable synthesis consistent particle size

来源：评论

学校读者我要写书评

暂无评论

Achieving high surface bioactivity and adhesion in Ti-6Al-4V alloy via anodic oxidation and electrophoretic deposition

引用

Ceramics International 2025年第16期51卷 22755-22765页

作者： Wu, Yu-Jie Wang, Chi-Yun Mana-ay, Haidee Tu, Chi-Shun Lai, Po-Liang Chen, Pin-Yi International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City24301 Taiwan Research Center for Intelligent Medical Devices Ming Chi University of Technology New Taipei City24301 Taiwan Department of Physics Fu Jen Catholic University New Taipei City24205 Taiwan Bone and Joint Research Center Department of Orthopedic Surgery Chang Gung Memorial Hospital Taoyuan City33305 Taiwan Department of Mechanical Engineering Chang Gung University Taoyuan City33302 Taiwan Department of Physics Silliman University Dumaguete City6200 Philippines

This study combines 3D printing, anodic oxidation (AO), and electrophoretic deposition (ED) technologies to develop Ti-6Al-4V alloy (abbreviated as Ti64) with high hydrophilicity, adhesion, and bioactivity. Titanium oxide nanotubes formed by AO treatment on the Ti64 surface exhibited reduced contact angles from 53 ° to 10 °. The adhesion of the calcium (Ca) layer through the integrated technology of the AO and ED treatments (herein abbreviated as AED) displays an optimal adhesive force of over 30 N on the Ti64 surface, which is attributed to the stable chemical bond due to the formation of OH− ions on the substrate after the AO treatment and the subsequent oxidation reaction of the Ca2+ ions to form a predominantly Ca(OH)2 layer after the ED treatment. Moreover, the AED treatment forms tiny needle-like structures that can effectively promote osteogenic differentiation. The expressions of the osteocyte marker genes (i.e., OCN, OPN, and DMP1) were improved after the AED treatment, showing increased osteogenic differentiation into mature bone tissue. This work presents the AED treatment as a valuable surface modification technique to boost the surface bioactivity of Ti64 for clinical orthopedic applications. © 2025

关键词： Anodic oxidation

来源：评论

学校读者我要写书评

暂无评论

Benefits and drawbacks of radiofrequency ablation via percutaneous or minimally invasive surgery for treating hepatocellular carcinoma

引用

World Journal of Gastrointestinal Surgery 2024年第11期16卷 3400-3407页

作者： Ching-Lung Hsieh Cheng-Ming Peng Chun-Wen Chen Chang-Hsien Liu Chih-Tao Teng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724Taiwan Department of Surgery Chung Shan Medical University HospitalTaichung 40201Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Department of Radiology Taichung Armed Forces General HospitalTaichung 406Taiwan Department of Medical Imaging and Radiological Sciences Central Taiwan University of Science and TechnologyTaichung 406Taiwan Department of Radiology School of MedicineNational Defense Medical CenterTaipei 11490Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital and China Medical UniversityHsinchu 302Taiwan Institute of Nuclear Engineering and Science National Tsing Hua UniversityHsinchu 300Taiwan Department of Radiology Nantou Hospital of the Ministry of Health and WelfareNantou 540Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia UniversityTaichung 407Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

The management of early stage hepatocellular carcinoma(HCC)presents significant *** radiofrequency ablation(RFA)has shown safety and effectiveness in treating HCC,with lower mortality rates and shorter hospital stays,its high recurrence rate remains a significant ***,achieving improved survival solely through RFA is challenging,particularly in retrospective studies with inherent *** is commonly used for guiding percutaneous RFA,but its low contrast can lead to missed tumors and the risk of HCC *** enhance the efficiency of ultrasound-guided percutaneous RFA,various techniques such as artificial ascites and contrast-enhanced ultrasound have been developed to facilitate complete tumor *** invasive surgery(MIS)offers advantages over open surgery and has gained traction in various surgical *** studies suggest that laparoscopic intraoperative RFA(IORFA)may be more effective than percutaneous RFA in terms of survival for HCC patients unsuitable for surgery,highlighting its ***,combining MIS-IORFA with these enhanced percutaneous RFA techniques may hold greater significance for HCC treatment using the MIS-IORFA *** article reviews liver resection and RFA in HCC treatment,comparing their merits and proposing a trajectory involving their combination in future therapy.

关键词： Percutaneous radiofrequency ablation Minimally invasive surgery Hepatocellular carcinoma Intraoperative radiofrequency ablation Contrast-enhanced ultrasound

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：