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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

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IoT-Driven Solution for Time-Varying Kinematics: 'Reflected'Trajectory Prediction in Dynamic Grasping Tasks 23

IoT-Driven Solution for Time-Varying Kinematics: 'Reflected'...

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8th International Conference on Cloud Computing and Internet of Things, CCIOT 2023

作者： Ng, Chung Hou Eu, Kok Seng Yap, Kian Meng Ping, Julian Tan Kok Research Centre for Human-Machine Collaboration Department of Engineering Department of Computing and Information Systems School of Engineering and Technology Sunway University Selangor Bandar Sunway Malaysia Taylors University Selangor Petaling Jaya Malaysia

ISBN: (纸本)9798400708046

Time-varying kinematics is a problem with extreme relevance in an increasingly automated world, with no more than a handful of papers studying it. For any industry nowadays to include automation within their pipeline, there will almost always be a need to have purpose-built robotics with expensive and elaborate infrastructure built around it. The reasoning for this is that any robotic-based automation implemented requires movement commands with pin-point precision to work reliably. The Kinematics of the robot is already a well-studied subject, however kinematics only ever reliably works on static object goals, not on moving object goals. This would pose a problem as any industry seeking to implement robotic automation would have no solution toward moving object goals. Additionally, traditional robotic automation incurs time-cost due to the necessity of static object goals during collection. Stopping the object goal or halting robot movement adds to the time overhead, impacting overall efficiency. To address these limitations, this research explores the integration of the Internet of Things (IoT) to develop a more robust "Reflected"trajectory prediction methodology. By leveraging IoT capabilities, it is possible to enhance the adaptability and responsiveness of robotic systems to dynamic grasping tasks involving moving object goals. The introduction of IoT design principles would also allow for a more robust range of robotics to be able to integrate the proposed system, as the computationally complex tasks might not be able to run well alone on a miniaturized robotic system. © 2023 ACM.

关键词： Kinematics

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Data Augmentation for Improving the Performance of Raga (Music Genre) Classification systems 5

Data Augmentation for Improving the Performance of Raga (Mus...

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5th International Conference on Electronics and Sustainable Communication systems, ICESC 2024

作者： Pushparajan, M. Sreekumar, K.T. Ramachandran, K.I. Kumar, C. Santhosh Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Mechanical Engineering Coimbatore India Amrita School of Engineering Amrita Vishwa Vidyapeetham Machine Intelligence Research Laboratory Department of Electronics and Communication Engineering Coimbatore India Amrita School of Engineering Amrita Vishwa Vidyapeetham Intelligent Systems Research Laboratory Department of Mechanical Engineering Coimbatore India

ISBN: (纸本)9798350379945

The ability to identify the ragas (music genres) of Indian musical compositions is considered to be a rare talent or gift among musicians and music aficionados. It would take years of rigorous training and exposure to various ragas for elevating an ardent learner of music to such levels of expertise. machine learning supported raga identification systems try to mimic this cognitive ability of an ace musician to recognize the patterns or signatures of ragas so that the ragas of music compositions can be identified. In this work, the audio samples obtained from the flute concerts of a legendary flutist were analyzed for recognizing the ragas. First a convolutional neural network (CNN) algorithm based raga classification system was developed with mel-spectrogram as input which yielded an accuracy of 52.4%. When this system was revamped with the techniques of data augmentation, the classification accuracy was substantially enhanced to 83%. This system can be made more versatile by incorporating more ragas in the corpus, by including signals from musical instruments other than flute and by incorporating signals from vocal concerts and also musical renderings set on different sruthis (tonic). © 2024 IEEE.

关键词： Convolutional neural networks

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Adaptive Soft Pneumatic Robot Inspired by Locomotion of Snake

Adaptive Soft Pneumatic Robot Inspired by Locomotion of Snak...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Lu, Jinxuan Hu, Xinshu Zhu, Xiaoyu Chen, Cheng Wang, Hongqiang Southern University of Science and Technology Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Shenzhen China Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering and Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities Shenzhen China Guangzhou China

ISBN: (纸本)9781665481090

Pneumatic soft robots have garnered widespread attention for their flexibility and adaptability in various applications. However, existing soft robots generally struggle to effectively navigate diverse terrains, especially when it comes to climbing obstacles. This paper introduces an adaptive pneumatic soft robot designed based on snake-like locomotion, which effectively addresses this issue. The robot utilizes four corrugated tubes as its soft actuators, complemented by silicone-made feet with bidirectional friction anisotropy, enabling it to adapt to various terrains and exhibit climbing capabilities. Experiments demonstrate that the robot can traverse different surfaces such as sand, gravel, and slopes, and can climb obstacles up to 20 centimeters high. Additionally, it features a self-regulation mechanism that allows it to recover from accidental overturns. This study presents a soft robot design with multi-terrain adaptability and self-recovery capabilities. © 2024 IEEE.

关键词： Pneumatics

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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 ...

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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)

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Latency Localization of Auditory Brainstem Response by Different Deep Learning Methods

Latency Localization of Auditory Brainstem Response by Diffe...

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

作者： Ji, Junyu Wang, Xin Jia, Desheng Zhao, Chunrui He, Yuchao Ahmad, Ijaz Zhu, Mingxing Pan, Hongguang Chen, Shixiong Li, Guanglin University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Shenzhen Children's Hospital Department of Otolaryngology Shenzhen518033 China Chinese Academy of Sciences Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Harbin Institute of Technology School of Electronics and Information Engineering Shenzhen518055 China

ISBN: (纸本)9798350327182

Auditory brainstem response (ABR) is an evoked potential generated by the auditory brainstem nuclei in response to auditory stimuli. Hearing loss or impairment in the auditory pathway can be objectively reflected by extracting the latencies of the peaks of characteristic waves (especially wave V) in the clinic. The commonly used clinical method of peak localization is the manual labeling approach by subjective visualization. However, this method is time-consuming and highly dependent on the experience of the clinician. In this study, three different types of neural networks were proposed to realize the automatic intelligent recognition of the wave V position. Firstly, during the data preprocessing, the ABR data of humans was clipped and normalized. Then three types of neural networks, namely DNN, CNN, and RNN, were proposed for the latency localization of wave V. The performances of these three networks were further evaluated under different sound pressure levels and different error scales. The results showed that DNN was the best network for localizing the wave V position. The highest overall accuracy rate was 91.70% and the error scale was 0.1ms. This study showed that the proposed automatic method with neural networks can greatly reduce the workload of medical personnel in finding the ABR latencies and can assist doctors in further diagnosis. © 2023 IEEE.

关键词： Deep learning

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A Novel Carbon Paste Electrode for Convenient and Efficient Auditory Brainstem Response Acquisition: A Pilot Study 1

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15th International Conference on Sensing Technology, ICST 2022

作者： Wang, Xin Tian, Qiong Xu, Yangjie Zhu, Mingxing Wang, Yingying He, Yuchao Chen, Shixiong Liu, Zhiyuan Li, Guanglin CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Interdisciplinary Centre for Security Reliability and Trust University of Luxembourg Luxembourg1855 Luxembourg School of Electronics and Information Engineering Harbin Institute of Technology Shenzhen518055 China

ISBN: (数字)9783031298714

ISBN: (纸本)9783031298707

Auditory Brainstem Response (ABR) is the commonly used tool in Otology for clinical hearing loss and disease diagnoses. Wet electrodes, served as the gold standard, are widely used in clinical settings to acquire ABR signals for superior performance. However, it is a complex and time-consuming process to fix the electrodes by applying bandages or adhesive tapes. Moreover, wet electrodes might cause allergy and uncomfortable for patients, especially for children. Therefore, a novel anhydrous carbon paste electrode (CPE) with adhesion and biocompatibility was proposed to solve the aforementioned problems. The impedance of unfixed CPE and Conductive Paste-based electrode was recorded, and the ABR waveforms obtained by both two methods were systematically compared to further investigate and verify the feasibility of the proposed unfixed CPE. The results showed that the proposed CPE could achieve high-quality ABR recording under unfixed condition, which was comparable with the gold standard method. Besides, the analyses of the latency and amplitude of the ABRs showed that unfixed CPE could acquire higher amplitudes which would help with wave recognition, while the latency was similar. This proved that the unfixed CPE could obtain ABR with the same information compared with that of Paste-based ABR, since the physicians always made the diagnosis by analyzing the latency. Furtherly, we compared the correlation coefficient of the ABRs under different averaging times, and the results showed that unfixed CPE was comparable, even better than the conventional method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Electrodes

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

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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

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

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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

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Network-aware Shared Autonomy in Bilateral Teleoperation 23

Network-aware Shared Autonomy in Bilateral Teleoperation

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23rd IEEE-RAS International Conference on humanoid Robots, humanoids 2024

作者： Chen, Xiao Michel, Youssef Sadeghian, Hamid Haddadin, Sami Technical University of Munich Human-centered Assistive Robotics Munich Germany Munich Institute of Robotics and Machine Intelligence Robotics Science and Systems Intelligence Technical University of Munich Munich Germany University of Isfahan Faculty of Engineering Isfahan*** Iran

ISBN: (纸本)9798350373578

In this paper, an autonomy allocation approach is proposed for bilateral teleoperation systems to improve user performance under suboptimal communication networks. To achieve this, time-varying communication quality metrics such as delay and jitter are continuously monitored on the teleoperated side, and the autonomy level is dynamically adjusted based on the communication network quality. An autonomous agent is also deployed on the teleoperated side, leveraging preexisting task knowledge for shared autonomy. Additionally, a time-domain passivity approach is employed to maintain communication channel passivity, mitigating the impact of adverse network behavior on task performance. The proposed approach is validated through extensive experiments and user studies, and the result shows our approach significantly improved the performance of the subjects (p © 2024 IEEE.

关键词： Teleconferencing

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