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Next-Generation Prosthetic Hand:from Biomimetic to Biorealistic

Research 2021年第1期2021卷 222-225页

作者： Ning Lan Manzhao Hao Chuanxin MNiu He Cui Yu Wang Ting Zhang Peng Fang Chih-hong Chou Institute of Medical Robotics Shanghai Jiao Tong UniversityShanghaiChina Laboratory of Neurorehabilitation Engineering School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina Department of Rehabilitation Medicine Ruijin HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghaiChina Center for Excellence in Brain Science and Intelligent Technology Chinese Academy of SciencesShanghaiChina School of Biological Science and Medical Engineering Beihang UniversityBeijingChina Beijing Advanced Innovation Center for Biomedical Engineering School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina i-lab Key Laboratory of Multifunctional Nanomaterials and Smart SystemsSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhouChina Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhenChina

Integrating a prosthetic hand to amputees with seamless neural compatibility presents a grand challenge to neuroscientists and neural engineers for more than half *** anatomical structure or appearance of human hand does not lead to improved neural connectivity to the sensorimotor system of *** functions of modern prosthetic hands do not match the dexterity of human hand due primarily to lack of sensory awareness and compliant ***,progress in restoring sensory feedback has marked a significant step forward in improving neural continuity of sensory information from prosthetic hands to ***,little effort has been made to replicate the compliant property of biological muscle when actuating prosthetic ***,a full-fledged biorealistic approach to designing prosthetic hands has not been contemplated in neuroprosthetic *** this perspective article,we advance a novel view that a prosthetic hand can be integrated harmoniously with amputees only if neural compatibility to the sensorimotor system is *** ongoing research supports that the next-generation prosthetic hand must incorporate biologically realistic actuation,sensing,and reflex functions in order to fully attain neural compatibility.

关键词： neural compatibility primarily

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Development of a magnetoelectric neural stimulator for in vitro experiments

Development of a magnetoelectric neural stimulator for in vi...

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IEEE Biomedical Circuits and systems (BIOCAS)

作者： Stratis Matsoukis Joana Covelo Maria V. Sanchez-Vives Andrea Veciana Donghoon Kim Xiang-Zhong Chen Salvador Pané Hidelberto Macedo-Zamudio Ulrike Wallrabe Ren Xu Guenter Edlinger Josef Scharinger G.tec Medical Engineering GmbH Austria Institute for Computational Perception Johannes Kepler University Linz Austria Institut D'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Barcelona Spain Institució Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain Multi-Scale Robotics Lab (MSRL) Institute of Robotics and Intelligent Systems (IRIS) ETH Zurich Zurich Switzerland Laboratory for Microactuators IMTEK Albert-Ludwigs-Universität Freiburg Freiburg Germany

Magnetoelectric (ME) materials hold the potential for wireless and minimally invasive brain stimulation with high spatial precision. However, comprehensive integration of ME materials in neurophysiology experiments remains an open challenge. In this study, we present the development of a ME stimulator prototype for in vitro brain stimulation, specifically tested with BiFeO 3 -CoFe 2 O 4 (BFO-CFO) nanoparticles. Our approach entails the design and implementation of a ME stimulator, which seamlessly integrates with existing electrophysiology setups while supporting a wide range of frequencies. To optimize the stimulator's design and evaluate its performance, we conducted modeling and simulations, bench tests, and in vitro experiments using cortical slices. The proposed ME stimulator offers neuroscientists a reliable and versatile tool to advance their understanding of brain function and potentially enhance the treatment of neurological disorders.

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Fundus-Image-Based Retinal Vascular Analysis in Myopic Eyes 42

Fundus-Image-Based Retinal Vascular Analysis in Myopic Eyes

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42nd Chinese Control Conference, CCC 2023

作者： Shen, Jichen Zou, Haohan Wang, Yan Liu, Jinchao Yu, Ningbo College of Artificial Intelligence Nankai University Tianjin300350 China Clinical College of Ophthalmology Tianjin Medical University Tianjin300070 China Tianjin Key Lab of Ophthalmology and Visual Science Tianjin Eye Institute Tianjin Eye Hospital Nankai University Affiliated Eye Hospital Tianjin300020 China Nankai University Eye Institute Nankai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

ISBN: (纸本)9789887581543

Myopia is prevalent worldwide and it is of great significance to prevent, control and intervene myopia in an early stage. The etiopathogenesis of myopia remains unclear and needs further research. Fundus photographs can show biomarkers and lesions of the retina in a non-invasive way directly. To discover some potential changes in myopic eyes, we extracted the retinal vascular features from vessel segmented results, and calculated the Spearman correlation coefficients between the retinal vascular features and the spherical refractive errors. The Kruskal-Wallis test was applied to explore the difference exists in the characteristics of retinal vessels among the mild, moderate and high myopia groups. The statistical analysis results indicated that the higher the degrees of myopia, the smaller the retinal vessels. This study found vascular changes in myopic eyes through fundus images, which could help to explain the mechanism of myopia and the damage caused by myopia. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Ophthalmology

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Gesture Recognition Based on Attention and Dilated Causal Convolution

Gesture Recognition Based on Attention and Dilated Causal Co...

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2022 IEEE International Conference on Real-Time Computing and robotics, RCAR 2022

作者： Zhou, Xin Liu, Jiaqing Huai, Yaping Ye, Jiancong Wang, Can Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China Department of Rehabilitation Medicine Shenzhen Longhua District Central Hospital Shenzhen518000 China University of Science and Technology of China China University of Chinese Academy of Sciences China South China University of Technology China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

In recent years, based on surface electromyography (sEMG), great progress has been made in gesture recognition tasks, which is significant to the study of computer interaction and prosthesis control. Prior to this, many researches have focused on feature selection and time series modeling of data. However, it is difficult and complicated to manually perform feature extraction and feature selection on data. Besides, most of the time series modeling is based on recurrent neural networks with memory cell, that is, Long Short-term Memory (LSTM). Even though LSTM has memory gate, but cannot completely records historical information. In this paper, to address the above problems, we propose a Temporal Convolutional Network based on Attention mechanism (ATCN), in which Attention is used to characterize temporal features, and dilated causal convolution to capture more historical information. ATCN achieves 95.26% accuracy with this method on the public dataset NinaPro DB2, which exceeds the state-of-the-art accuracy of 5%. The experiments show that this approach is feasible and effective for gesture recognition tasks. Our contributions are as follows: Firstly, Attention mechanism is introduced into the field of prosthetic control. Then, ATCN is proposed for gesture recognition. Finally, ATCN achieves better results than LSTM on multiple public datasets. © 2022 IEEE.

关键词： Long short-term memory

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Sleep Position Detection for Closed-Loop Treatment of Sleep-Related Breathing Disorders

Sleep Position Detection for Closed-Loop Treatment of Sleep-...

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IEEE International Conference on Rehabilitation robotics (ICORR)

作者： A. Breuss N. Vonau C. Ungricht E. Schwarz M. Irion M. Bradicich F. A. Grewe S. Liechti S. Thiel M. Kohler R. Riener E. Wilhelm Department of Health Science and Technology Sensory-Motor Systems Lab Institute of Robotics and Intelligent Systems ETH Zurich Zurich Switzerland Sleep Disorders Centre of the Department of Pulmonology of the University Hospital Zurich University Hospital of Zurich (USZ) Zurich Switzerland Spinal Cord Injury Center University Hospital Balgrist Zurich Switzerland Engineering and Technology Institute Faculty of Science and Engineering University of Groningen The Netherlands

ISBN: (数字)9781665488297

ISBN: (纸本)9781665488303

Reliable detection of sleep positions is essential for the development of technical aids for patients with position-dependent sleep-related breathing disorders. We compare personalized and generalizable sleeping position classifiers using unobtrusive eight-channel pressure-sensing mats. Data of six male patients with confirmed position-dependent sleep apnea was recorded during three subsequent nights. Personalized position classifiers trained using leave-one-night-out cross-validation on average reached an F1-score of 61.3% for supine/non-supine and an F1-score of 46.2% for supine/lateral-left/lateral-right classification. The generalizable classifiers reached average F1-scores of 62.1% and 49.1% for supine/non-supine and supine/lateral-left/lateral-right classification, respectively. In-bed presence (“bed occupancy”) could be detected with an average F1-score of 98.1%. This work shows that personalized sleep-position classifiers trained with data from two nights have comparable performance to classifiers trained with large interpatient datasets. Simple eight-channel sensor mattresses can be used to accurately detect in-bed presence required for closed-loop systems but their use to classify sleep-positions is limited.

关键词： Pressure sensors Medical treatment Robot sensing systems Assistive robots Sleep apnea Robustness Real-time systems

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Impedance control for a novel composite modular lower-limb hemiplegic exoskeleton

Impedance control for a novel composite modular lower-limb h...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Bao, Ruoyu Li, Pengbo He, Bailin Wang, Can Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology University of Chinese Academy of Sciences Department of Mechanical and Automation Engineering Chinese University of Hong Kong College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shaanxi Xi'an710021 China

ISBN: (纸本)9781665436786

This paper proposes a control scheme based on impedance control for the smoothing control of the operating movements of a lower-limb hemiplegic exoskeleton robot on the basis of a new composite modular lower-limb hemiplegic ex-oskeleton(CMLHE) structure. The CMLHE has good structural performance and can be used in the rehabilitation of patients with hemiplegia caused by stroke and other diseases. At the same time, the smoothing control by means of impedance control ensures that patients with lower limb hemiplegia can use the CMLHE to achieve smooth walking movements without additional injuries caused by the CMLHE during the rehabilitation training. This paper analyses the performance of this CMLHE robot based on walking movements and demonstrates through kinematic and kinetic modelling and simulation that the impedance control scheme of this CMLHE robot is feasible and effective and can be more widely used in the rehabilitation training of patients with lower limb hemiplegia. © 2021 IEEE.

关键词： Exoskeleton (robotics)

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A modular rehabilitation lower limb exoskeleton for stroke patients with hemiplegia

A modular rehabilitation lower limb exoskeleton for stroke p...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Li, Pengbo Wei, Wenhao Bao, Ruoyu He, Bailin Su, Zhilong Wang, Can Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology University of Chinese Academy of Sciences Department of Mechanical and Automation Engineering The Chinese University of Hong Kong College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shaanxi Xi'an710021 China

ISBN: (纸本)9781665436786

A modular rehabilitation exoskeleton robot for hemiplegic patients (SIAT-H) is created in this paper. The design of the exoskeleton is based on the gait analysis of hemiplegic patients and the movement data of healthy people. Through the motion capture experiments at different speeds, the walking style of patients with hemiplegia is understood. A modular exoskeleton robot, including an independent hip joint, knee joint and ankle joint, is designed. The mechanical structure which is optimized based on the physiological characteristics of human body would not cause additional damage to the joints during walking. In order to ensure the reliability of use, the structural strength is also considered. The kinematics relationship is verified by comparison of simulation data and calculated data. In the end, we made an experimental prototype, and the wearing experiment verified the reliability of the mechanism. © 2021 IEEE.

关键词： Exoskeleton (robotics)

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A differential public PUF design for lightweight authentication 16

A differential public PUF design for lightweight authenticat...

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2021 International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2021 and 16th Conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Duan, Shengyu Sai, Gaole School of Computer Engineering and Science Shanghai University Shanghai200444 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9783800755899

Physical Unclonable Functions (PUFs) have emerged as a promising primitive to provide a hardware keyless security mechanism for integrated circuit applications. Public PUFs (PPUFs) address the crucial PUF vulnerability of requiring databases to store the secrete reference information. This paper investigates one of the PPUF families, differential PPUF (dPPUF), which exploits complexly interacted logic to create time gap between actual execution and simulation, and to prevent simulation attacks. Conventional dPPUFs have high costs. We observe the repressers have large impact on simulation time, but take a great proportion in current dPPUF structure. We thereby present a represser network with specially designed interconnection and shared logic, to maintain a high circuit complexity and to reduce the area cost. We show the proposed dPPUF has similar resilience over simulation attacks as the conventional design. Area cost can be reduced by up to 44%, and thus the proposed design can be used for lightweight authentication. © VDE VERLAG GMBH.

关键词： Authentication

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CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI

TechRxiv

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TechRxiv 2022年

作者： Chen, Yirong Fan, Weiquan Xing, Xiaofen Pang, Jianxin Huang, Minlie Han, Wenjing Tie, Qianfeng Xu, Xiangmin The UBTECH-SCUT Joint Research Lab Engineering Research Center Ministry of Education on Human Body Data Perception School of Electronic and Information Engineering South China University of Technology Guangzhou510641 China UBTECH Robotics Corp Shenzhen518000 China CoAI Group State Key Lab of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

Human language expression is based on the subjective construal of the situation instead of the objective truth conditions, which means that speakers’ personalities and emotions after cognitive processing have an important influence on conversation. However, most existing datasets for conversational AI ignore human personalities and emotions, or only consider part of them. It’s difficult for dialogue systems to understand speakers’ personalities and emotions although large-scale pre-training language models have been widely used. In order to consider both personalities and emotions in the process of conversation generation, we propose CPED, a large-scale Chinese personalized and emotional dialogue dataset, which consists of multi-source knowledge related to empathy and personal characteristic. These knowledge covers gender, Big Five personality traits, 13 emotions, 19 dialogue acts and 10 scenes. CPED contains more than 12K dialogues of 392 speakers from 40 TV shows. We release the textual dataset with audio features and video features according to the copyright claims, privacy issues, terms of service of video platforms. We provide detailed description of the CPED construction process and introduce three tasks for conversational AI, including personality recognition, emotion recognition in conversations as well as personalized and emotional conversation generation. Finally, we provide baseline systems for these tasks and consider the function of speakers’ personalities and emotions on conversation. Our motivation is to propose a dataset to be widely adopted by the NLP community as a new open benchmark for conversational AI research. The full dataset is available1 © 2022, CC BY-NC-SA.

关键词： Emotion Recognition

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CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI

arXiv

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arXiv 2022年

作者： Chen, Yirong Fan, Weiquan Xing, Xiaofen Pang, Jianxin Huang, Minlie Han, Wenjing Tie, Qianfeng Xu, Xiangmin The UBTECH-SCUT Joint Research Lab Engineering Research Center of Ministry of Education on Human Body Data Perception School of Electronic and Information Engineering South China University of Technology Guangzhou510641 China UBTECH Robotics Corp Shenzhen518000 China CoAI Group State Key Lab of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

Human language expression is based on the subjective construal of the situation instead of the objective truth conditions, which means that speakers' personalities and emotions after cognitive processing have an important influence on conversation. However, most existing datasets for conversational AI ignore human personalities and emotions, or only consider part of them. It's difficult for dialogue systems to understand speakers' personalities and emotions although large-scale pre-training language models have been widely used. In order to consider both personalities and emotions in the process of conversation generation, we propose CPED, a large-scale Chinese personalized and emotional dialogue dataset, which consists of multi-source knowledge related to empathy and personal characteristic. These knowledge covers gender, Big Five personality traits, 13 emotions, 19 dialogue acts and 10 scenes. CPED contains more than 12K dialogues of 392 speakers from 40 TV shows. We release the textual dataset with audio features and video features according to the copyright claims, privacy issues, terms of service of video platforms. We provide detailed description of the CPED construction process and introduce three tasks for conversational AI, including personality recognition, emotion recognition in conversations as well as personalized and emotional conversation generation. Finally, we provide baseline systems for these tasks and consider the function of speakers' personalities and emotions on conversation. Our motivation is to propose a dataset to be widely adopted by the NLP community as a new open benchmark for conversational AI research. The full dataset is available. © 2022, CC BY-NC-ND.

关键词： Speech processing

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