A5076243028- EEG and Brain-Computer Interfaces
- Muscle activation and electromyography studies
- Advanced Vision and Imaging
- Image Processing Techniques and Applications
- Hand Gesture Recognition Systems
- Neuroscience and Neural Engineering
- Fault Detection and Control Systems
- Advanced Optical Sensing Technologies
- Robot Manipulation and Learning
Guangzhou University
2024
Shenzhen Institutes of Advanced Technology
2022-2023
Chinese Academy of Sciences
2022-2023
University of Chinese Academy of Sciences
2023
Cytoskeleton (United States)
2018
Northeastern University
2018
Dexterous control of robotic hand driven by human motor intent has drawn a lot attention in both industrial and rehabilitation scenarios. Providing simultaneous proportional become prevailing solution recently. Towards improving the finger kinematics estimation precision reducing its computational cost, convolution model with mechanism (CNN-Attention) was proposed this study. For comparison purpose, two previously used deep learning models, long short-term memory (LSTM) Sparse Pseudo-input...
Continuous estimation of finger joints based on surface electromyography (sEMG) has attracted much attention in the field human-machine interface (HMI). A couple deep learning models were proposed to estimate joint angles for specific subject. When applied onto a new subject, however, performance subject-specific model would degrade significantly due inter-subject differences. Therefore, novel cross-subject generic (CSG) was this study continuous kinematics users. Firstly, multi-subject...
On the basis of demonstration experience gained through learning, this paper proposes an interactive robot learning system, which uses wearable sensors that can detect surface electromyography signals (sEMG)and inertial information. Gesture recognition and trajectory calculation are main process in our system. Robot grasping other hand actions, be marked controlled human gesture recognition. A comparison 4 groups feature extraction project multiple kernel relevance vector machine...