检索结果-内蒙古大学图书馆

17th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2024

作者： Zhou, Xiaomeng Cui, Fengxi Yang, Zijian Zhao, Chunlei Li, Guanglin Bao, Shi-Chun Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Shenzhen Dongdixin Technology Co. Ltd Shenzhen518057 China National Innovation Center for Advanced Medical Devices Shenzhen518126 China

ISBN: (纸本)9798350355154

Extracorporeal shock wave therapy is a non-invasive technique, which has been widely used in the clinical treatment of various musculoskeletal diseases such as frozen shoulder and muscle spasms. Conventional pneumatic radial shock wave therapy devices, as the mainstream products today, have shortcomings such as complex structure, high noise, and high requirements for airtightness. Alternatively, electromagnetic radial extracorporeal shock waves can effectively overcome the deficiencies of existing pneumatic technologies by introducing novel system designs. This article introduced the principles of electromagnetic launch technology, demonstrated the feasibility of electromagnetic radial extracorporeal shock wave therapy device by self-designed hardware and control strategy, and investigated the transmission process of shock waves from its generation to its effects on the human body. The feasibility and effectiveness of the design scheme were verified through finite element simulation and prototype manufacturing. © 2024 IEEE.

关键词： Shock waves

来源：评论

学校读者我要写书评

暂无评论

Organic-inorganic hybrid hole transport layers with SnS doping boost the performance of perovskite solar cells

引用

Journal of Energy Chemistry 2022年第5期31卷 637-645页

作者： Xiaolu Zheng Haibing Wang Feihong Ye Cong Chen Weijun Ke Wenjing Zhang Chuanxin He Yanlong Tai Guojia Fang College of Chemistry and Environmental Engineering Institute of Microscale OptoelectronicsShenzhen UniversityShenzhen 518060GuangdongChina Shenzhen Institute Wuhan UniversityShenzhen 518057GuangdongChina Key Laboratory of Human-Machine Intelligence-Synergy Systems of Chinese Academy of Sciences and Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055GuangdongChina

Perovskite solar cells(PSCs) have demonstrated excellent photovoltaic performance which currently rival the long-standing silicon solar cells’ efficiency. However, the relatively poor device operational stability of PSCs still limits their future commercialization. Binary sulfide is a category of materials with promising optoelectrical properties, which shows the potential to improve both the efficiency and stability of *** we demonstrate that the inorganic tin monosulfide(Sn S) can be an efficient dopant in 2,2’,7,7’-tet rakis(N,N-di-p-methoxy-phenylamine)-9,9’-spirobifluorene(spiro-OMe TAD) to form a composite hole transport layer(HTL) for PSCs. Sn S nanoparticles(NPs) synthesized through a simple chemical precipitation method exhibit good crystallization and suitable band matching with the perovskites. The introduction of Sn S NPs in Spiro-OMTAD HTLs enhanced charge extraction, reduced trap state density, and shallowed trap state energy level of the devices based on the composite HTLs. Therefore, the resulting solar cells employing Sn S-doped spiro-OMe TAD HTLs delivered an improved stabilized power output efficiency of 21.75% as well as enhanced long-term stability and operational stability. Our results provide a simple method to modify the conventional spiro-OMe TAD and obtain PSCs with both high efficiency and good stability.

关键词： Perovskite solar cells SnS nanoparticles Trap state passivation Stability

来源：评论

学校读者我要写书评

暂无评论

Contrast of multi-resolution analysis approach to transhumeral phantom motion decoding

引用

CAAI Transactions on intelligence Technology 2021年第3期6卷 360-375页

作者： Ejay Nsugbe Oluwarotimi William Samuel Mojisola Grace Asogbon Guanglin Li Independent Scholar Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences(CAS)Shenzhen Institutes of Advanced TechnologyShenzhenChina

In signal processing,multiresolution decomposition techniques allow for the separation of an acquired signal into sub levels,where the optimal level within the signal minimises redundancy,uncertainties,and contains the information required for the characterisation of the sensed *** the area of physiological signal processing for prosthesis control,scenarios where a signal decomposition analysis are required:the wavelet decomposition(WD)has been seen to be the favoured time-frequency approach for the decomposition of non-stationary *** a research perspective,the WD in certain cases has allowed for a more accurate motion intent decoding process following feature extraction and *** this,there is yet to be a widespread adaptation of the WD in a practical setting due to perceived computational ***,for neuro-muscular(electromyography)and brainwave(electroencephalography)signals acquired from a transhumeral amputee,a computationally efficient time domain signal decom-position method based on a series of heuristics was applied to process the acquired signals before feature *** results showed an improvement in motion intent decoding prowess for the proposed time-domain-based signal decomposition across four different classifiers for both the neuromuscular and brain wave signals when compared to the WD and the raw signal.

关键词： motion approach analysis

来源：评论

学校读者我要写书评

暂无评论

Comparison of Blood Pressure Modulation by Low-Intensity Focused Ultrasound Stimulation of Carotid Sinus, Nodose Ganglion, and Vagus Nerve 46

Comparison of Blood Pressure Modulation by Low-Intensity Foc...

引用

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

作者： Wei, Jingjing Ji, Ning Wang, Lin Wu, Xinyu Li, Guanglin Lin, Wan-Hua Chinese Academy of Sciences Cas Key Lab of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Shandong Zhongke Advanced Technology CO. LTD. Jinan250000 China

ISBN: (纸本)9798350371499

Low-intensity focused ultrasound stimulation (FUS) of the vagus nerve has proven effective in lowering blood pressure (BP) in our pilot animal study, opening new possibilities for noninvasive physiotherapy for hypertension. To further explore the impact of BP regulation by FUS on other targets, we compared the BP modulation pattern when applying FUS to the left carotid sinus, nodose ganglion, and vagus nerve trunk, respectively. FUS with different acoustic intensities was applied to each target, while continuous BP waveforms were synchronously recorded in the right common carotid artery. Subsequently, systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were extracted and analyzed before, during, and after FUS. The results revealed that FUS targeting the carotid sinus and nodose ganglion could also induce reductions in BP. However, both the degree of BP reduction and the sustained duration were less than those achieved with vagus nerve stimulation. Moreover, the ultrasound stimulation intensity threshold for inducing a hypotensive effect is lower when stimulating the vagus nerve compared to stimulating the carotid sinus and nodose ganglion. This study provides compelling evidence supporting the selection of the vagus nerve as the appropriate target for FUS in regulating BP. © 2024 IEEE.

关键词： Blood pressure

来源：评论

学校读者我要写书评

暂无评论

Single-Wavelength Laminar Optical Tomography for In Vivo Microvascular Three-Dimensional Imaging

Single-Wavelength Laminar Optical Tomography for In Vivo Mic...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Han Cui Dewei Han Wenquan Liu Xinping Deng Zhixuan Xin Guanglin Li CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Laminar Optical Tomography (LOT) is a promising non-invasive technique for three-dimensional imaging of complex biological structures, combining high resolution and deep penetration. In this study, a LOT system was assembled using a 520nm continuous-wave laser, exploiting the contrast mechanism provided by the unique optical absorption coefficient of hemoglobin at this wavelength for microvascular imaging. The system utilizes raster scanning to illuminate the target tissue's surface, capturing backscattered light intensity with a multi-channel Photomultiplier Tubes. The inverse problem of light propagation within the tissue is solved to reconstruct a three-dimensional image of microvasculature. Phantom and in-vivo rat ear results demonstrate the system's ability to image micro vessels with diameters of several hundred micrometers within the tissue. The implemented LOT system, known for its simplicity and cost-effectiveness, showcases its potential for applications in microvascular physiological and pathological research, as well as clinical diagnostics.

关键词： Micrometers Surface reconstruction Biomedical optical imaging Three-dimensional displays Surface waves Tissue engineering Tomography Optical imaging Image reconstruction Tumors

来源：评论

学校读者我要写书评

暂无评论

A Spatial Feature Extraction Method for Enhancing Upper Limb Motion Intent Prediction in EMG-PR System 46

A Spatial Feature Extraction Method for Enhancing Upper Limb...

引用

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

作者： Peng, Boxing Zhang, Haoshi Li, Xiangxin Zheng, Yue Li, Guanglin Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China Southern University of Science and Technology Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen518055 China Siat Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

ISBN: (纸本)9798350371499

High-Density Surface Electromyography (HD-sEMG) enriches motion intention pattern recognition systems by providing more spatial information. Multichannel linear descriptors (MLD) could provide a comprehensive description of the overall state characteristics within the muscle regions. In this study, an MLD-based spatial feature extraction method was proposed to capture differences and correlations in various muscle regions during movement, ultimately enhancing the system's classification accuracy. The performance of the feature extraction method was compared with traditional time domain feature extraction method under various classifiers and different movement types. The results show that employing the proposed method with the spatial features improves the classification error rates of combined movements from 11.14% to 7.28%, and better adaptability for all classifiers utilized in this study, which shows the effect of utilization of spatial information in different muscle regions. © 2024 IEEE.

关键词： Electromyography

来源：评论

学校读者我要写书评

暂无评论

Microcavity assisted graphene pressure sensor for single-vessel local blood pressure monitoring

引用

Nano Research 2024年第11期17卷 10058-10068页

作者： Jinan Luo Jingzhi Wu Xiaopeng Zheng Haoran Xiong Lin Lin Chang Liu Haidong Liu Hao Tang Houfang Liu Fei Han Zhiyuan Liu Zhikang Deng Chuting Liu Tianrui Cui Bo Li Tian-Ling Ren Jianhua Zhou Yancong Qiao School of Biomedical Engineering Shenzhen Campus of Sun Yat-sen University Shenzhen 518107 China Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province School of Biomedical Engineering Sun Yat-sen University Guangzhou 510275 China School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing 100084 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen 518055 China Cardiovascular surgery Seventh affiliated Hospital of Sun Yat-sen University Shenzhen 518107 China

Dynamic monitoring of blood pressure (BP) is beneficial to obtain comprehensive cardiovascular information of patients throughout the day. However, the clinical BP measurement method relies on wearing a bulky cuff, which limits the long-term monitoring and control of BP. In this work, a microcavity assisted graphene pressure sensor (MAGPS) for single-vessel local BP monitoring is designed to replace the cuff. The microcavity structure increases the working range of the sensor by gas pressure buffering. Therefore, the MAGPS achieves a wide linear response of 0–1050 kPa and sensitivity of 15.4 kPa^(−1). The large working range and the microcavity structure enable the sensor to fully meet the requirements of BP detection at the radial artery. A database of 228 BP data (60-s data fragment detected by MAGPS) and 11,804 pulse waves from 9 healthy subjects and 5 hypertensive subjects is built. Finally, the BP was detected and analyzed automatically by combining MAGPS and a two-stage convolutional neural network algorithm. For the BP detection method at local radial artery, the first stage algorithm first determines whether the subject has hypertension by the pulse wave. Then, the second stage algorithm can diagnose systolic and diastolic BP with the accuracy of 93.5% and 97.8% within a 10 mmHg error, respectively. This work demonstrates a new BP detection method based on single vessel, which greatly promotes the efficiency of BP detection.

关键词： graphene pressure sensor microcavity assisted pressure sensor single-vessel BP monitoring two-stage neural network algorithm

来源：评论

学校读者我要写书评

暂无评论

An Efficient Deep Transfer Learning Network for Characterization of Stroke Patients' Motor Execution from Multi-Channel EEG-Recordings 46

An Efficient Deep Transfer Learning Network for Characteriza...

引用

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

作者： Samuel, Oluwarotimi Williams Asogbon, Mojisola Grace Kulwa, Frank McEwan, Alistair A. Aboyeji, Sunday Timothy Khushaba, Rami Fang, Peng Li, Guanglin University of Derby School of Computing and Data Science Research Centre DerbyDE22 3AW United Kingdom SIAT-CAS Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Sydney University Australian Centre for Field Robotics ChippendaleNSW2008 Australia

ISBN: (纸本)9798350371499

Recent advances in stroke rehabilitation technology have been focused on developing Intelligent Rehabilitation Robots (IRR) that can effectively engage post-stroke patients (PSP) in intuitive motor training for full function recovery. Most existing rehabilitation robots incorporate functionalities that are passive in nature, constraining PSP to predetermined trajectories that often deviate from patients' limb movement intentions, consequently hindering recovery. To resolve this issue, a robust deep-transfer learning driven network (DTLN) is developed to adequately characterize PSP's motion intention signatures from neural oscillations towards achieving intuitive and active training. Thus, we investigated and proposed the utilization of mu-frequency spectrum (muFS) based CWT approach for Scalograms construction, which serves as inputs to the DTLN model that characterizes multiple classes of PSP's motor execution signatures from multi-channel electroencephalography (EEG) recordings. Then, we evaluated the proposed method using EEG data from six PSP and compared the decoding results to those of related approaches under similar experimental settings. The proposed method resulted in a significant increment of 10.84 % - 13.19% decoding accuracy across stroke patients and better convergence in comparison to other methods. Additionally, the method exhibited distinct task separability for individual motor execution signature across patients. In conclusion, our method offers a consistently accurate decoding of motor tasks that could enable intuitively active robotic training in PSPs with impaired motor function. © 2024 IEEE.

关键词： Brain computer interface

来源：评论

学校读者我要写书评

暂无评论

A Novel Hybrid Brain-Computer Interface Based on Integration of Steady-State Visual Stimulation and Rapid Serial Visual Presentation Paradigm

A Novel Hybrid Brain-Computer Interface Based on Integration...

引用

2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Xie, Jun Zhang, Huanqing Tao, Qing Fang, Peng Liu, Junjie Ge, Zengle Shao, Yixuan Ding, Yuhang School of Mechanical Engineering Xinjiang University Urumqi830017 China School of Mechanical Engineering Xi'an Jiaotong University Xi'an710049 China Shenzhen Institute of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Engineering Laboratory of Neural Rehabilitation Technology Shenzhen518055 China

ISBN: (纸本)9781665481090

Brain-computer interface (BCI) is a kind of human-computer interaction which can realize the communication and control between human brain and the external environment. The single-modality BCI has the problems of small command set and the difficulty to realize multi-dimensional control. To address these issues, a hybrid paradigm combining steady-state visual evoked potential (SSVEP) and rapid serial visual presentation (RSVP) was proposed and designed in this study. A 16-target SSVEP-RSVP hybrid BCI (hBCI) was constructed. This novel paradigm aims to achieve fast information transmission, guarantee system performance through efficient visual stimulation, and effectively overcome the crowding effect problem in the traditional BCIs. Through offline and online experiments, the hBCI system based on the SSVEP-RSVP integration paradigm shows high performance, which provides new insights and technical and theoretical supports for the applicable hBCIs. © 2024 IEEE.

关键词： Brain computer interface

来源：评论

学校读者我要写书评

暂无评论

Effect of Camera Position on Knee Angle Extracted by Single RGB Camera Markerless Method of human Posture

Effect of Camera Position on Knee Angle Extracted by Single ...

引用

2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Hu, Rui Diao, Yanan Sheng, Juyi Sun, Yue Ning, Yunkun Liu, GenYuan Wang, Yingchi Li, Guanglin Zhao, Guoru Chinese Academy of Sciences Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Research Center for Neural Engineering Shenzhen Institutes of Advanced Technology China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen China

ISBN: (纸本)9798350327182

Medical rehabilitation robots have shown strong potential for rehabilitation assessment and monitoring of the elderly. Accurate estimation of human posture based on video analysis can help the clinical application of medical rehabilitation robots. However, the current human pose estimation still needs to improve its accuracy;it is missing 3D posture information and has an unclear occlusion effect on accuracy. This paper proposes a markerless human pose measurement method based on a monocular RGB camera to find the knee joint angle using a 2D and 3D pose estimator. Eleven young people were recruited to participate in the experiments to study the effects of different camera positions on the joint angle extraction results. The results showed a camera angle of 45° was more effective in measuring sitting posture, with a standard deviation of 5.97 for the left leg. A camera angle of 90° was more effective in measuring gait, with a standard deviation of 9.34 for the left leg. In summary, the proposed method can fully use 3D posture information and consider the influence of camera angle on accuracy to improve posture estimation accuracy. The execution of this study is beneficial to promote medical rehabilitation robots to clinical applications. © 2023 IEEE.

关键词： Joints (anatomy)

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：