| Multi-sensor guided hand gesture recognition for a teleoperated robot using a recurrent neural network W Qi, SE Ovur, Z Li, A Marzullo, R Song IEEE Robotics and Automation Letters 6 (3), 6039-6045, 2021 | 183 | 2021 |
| A Smartphone-Based Adaptive Recognition and Real-Time Monitoring System for Human Activities W Qi*, H Su, A Aliverti IEEE Transactions on Human-Machine Systems, 2020 | 158 | 2020 |
| Deep neural network approach in robot tool dynamics identification for bilateral teleoperation H Su, W Qi, C Yang, J Sandoval, G Ferrigno, E De Momi IEEE Robotics and Automation Letters 5 (2), 2943-2949, 2020 | 155 | 2020 |
| An incremental learning framework for human-like redundancy optimization of anthropomorphic manipulators H Su, W Qi*, Y Hu, HR Karimi, G Ferrigno, E De Momi IEEE Transactions on Industrial Informatics, 2020 | 145 | 2020 |
| A Multimodal Wearable System for Continuous and Real-time Breathing Pattern Monitoring During Daily Activity W Qi*, A Aliverti IEEE Journal of Biomedical and Health Informatics, 2019 | 124 | 2019 |
| A fast and robust deep convolutional neural networks for complex human activity recognition using smartphone W Qi, H Su, C Yang, G Ferrigno, E De Momi, A Aliverti Sensors 19 (17), 3731, 2019 | 119 | 2019 |
| A cybertwin based multimodal network for ecg patterns monitoring using deep learning W Qi, H Su IEEE Transactions on Industrial Informatics 18 (10), 6663-6670, 2022 | 108 | 2022 |
| Fuzzy Approximation-based Task-Space Control of Robot Manipulators with Remote Center of Motion Constraint H Su, W Qi*, J Chen, D Zhang IEEE Transactions on Fuzzy Systems 30 (6), 1564-1573, 2022 | 104 | 2022 |
| Pneumatic Soft Robots: Challenges and Benefits H Su, X Hou, X Zhang, W Qi*, S Cai, X Xiong, J Guo Actuators 11 (3), 92, 2022 | 92 | 2022 |
| Deep neural network approach in human-like redundancy optimization for anthropomorphic manipulators H Su, W Qi, C Yang, A Aliverti, G Ferrigno, E De Momi IEEE Access 7, 124207-124216, 2019 | 74 | 2019 |
| A human activity-aware shared control solution for medical human–robot interaction H Su, W Qi*, Y Schmirander, SE Ovur, S Cai, X Xiong Assembly Automation, 2022 | 73 | 2022 |
| Deep neural network approach in EMG-based force estimation for human–robot interaction H Su, W Qi, Z Li, Z Chen, G Ferrigno, E De Momi IEEE Transactions on Artificial Intelligence 2 (5), 404-412, 2021 | 68 | 2021 |
| Depth vision guided hand gesture recognition using electromyographic signals H Su, SE Ovur, X Zhou, W Qi*, G Ferrigno, E De Momi Advanced Robotics, 1-13, 2020 | 68 | 2020 |
| Parallel structure of six wheel-legged robot trajectory tracking control with heavy payload under uncertain physical interaction J Li, J Wang, S Wang, H Peng, B Wang, W Qi, L Zhang, H Su Assembly Automation 40 (5), 675-687, 2020 | 66 | 2020 |
| Deep C-LSTM neural network for epileptic seizure and tumor detection using high-dimension EEG signals Y Liu, YX Huang, X Zhang, W Qi, J Guo, Y Hu, L Zhang, H Su IEEE Access 8, 37495-37504, 2020 | 63 | 2020 |
| Recent Advancements in Multimodal Human–robot Interaction H Su, W Qi*, J Chen, C Yang, J Sandoval, med amine Laribi Frontiers in Neurorobotics, DOI:10.3389/fnbot.2023.10840, 1-21, 2023 | 61 | 2023 |
| Neural approximation-based model predictive tracking control of non-holonomic wheel-legged robots J Li, J Wang, S Wang, W Qi, L Zhang, Y Hu, H Su International Journal of Control, Automation and Systems 19 (1), 372-381, 2021 | 53 | 2021 |
| A novel autonomous learning framework to enhance sEMG-based hand gesture recognition using depth information SE Ovur, X Zhou, W Qi, L Zhang, Y Hu, H Su, G Ferrigno, E De Momi Biomedical Signal Processing and Control 66, 102444, 2021 | 50 | 2021 |
| An adaptive reinforcement learning-based multimodal data fusion framework for human–robot confrontation gaming W Qi, H Fan, HR Karimi, H Su Neural Networks 164, 489-496, 2023 | 47 | 2023 |
| DCNN based human activity recognition framework with depth vision guiding W Qi, N Wang, H Su, A Aliverti Neurocomputing 486, 261-271, 2022 | 44 | 2022 |
Giancarlo FerrignoProfessor of Biomedical Engineering, NearLab, DEIB, Politecnico di Milano在 polimi.it 的电子邮件经过验证
