Papers

6

Total Citations

33

H-Index

3

About

Dr. Aimin Wang’s research lies at the intersection of brain-computer interfaces, intelligent robotics, and advanced control systems, with a focus on translating neural signals into practical rehabilitation and autonomous manipulation technologies. His most cited work, “Index finger motor imagery EEG pattern recognition in BCI applications using dictionary cleaned sparse representation-based classification for healthy people” (2017, 15 citations), demonstrates a novel approach to decoding motor imagery from EEG signals, offering a pathway for controlling rehabilitation devices for patients with neurological impairments. In robotics, Wang’s “FastGNet” (2024, 6 citations) introduces an efficient 6-DOF grasp detection method integrating multi-attention mechanisms and point transformer networks, enabling robotic arms to grasp objects in cluttered environments without human intervention. His earlier work on magneto-rheological fluid dampers for flexible robot vibration control (2010, 5 citations) underscores a sustained interest in enhancing robotic precision and stability. More recently, his trajectory planning algorithm for intelligent robot cutting-grinding (2023, 3 citations) and improved Euclidean clustering for workpiece identification (2024, 2 citations) advance autonomous manufacturing. Wang’s contributions bridge signal processing, machine learning, and mechatronics, with cumulative citations reflecting growing impact in assistive and industrial robotics.

Research Focus

Key Achievements

3
H-Index
6
Papers
33
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Index finger motor imagery EEG pattern recognition in BCI applications using dictionary cleaned sparse representation-based classification for healthy people
15 citations · 2017
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Southeast University, Beijing Institute of Technology, Chang'an University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago