Papers

2

Total Citations

8

H-Index

2

About

Yusen Guo is a researcher at the forefront of human-machine interaction and intelligent robotic systems, with a primary focus on wearable sensing technologies and tactile feedback for robotics. His work bridges the gap between biological signals and machine control, particularly through the development of surface electromyographic (sEMG)-based wearable human-machine interfaces (HMI). In his highly cited 2023 paper, Guo introduced a real-time robotic arm control system that leverages edge artificial intelligence to process sEMG signals for intuitive gesture and motion recognition, achieving 5 citations for its innovative integration of deep learning with resource-constrained hardware. This work demonstrates his commitment to creating practical, low-latency solutions for assistive robotics and prosthetics. Additionally, his 2024 study on flexible three-axis pressure sensor arrays, with 3 citations, presents a groundbreaking capacitive tactile sensing system for robotic grasping feedback, featuring a 4×2 array of 3D sensing units capable of simultaneous multi-channel acquisition. This advancement enhances robots’ ability to perceive and respond to complex mechanical stimuli, improving dexterous manipulation. Guo’s research, with its emphasis on real-time performance and sensor miniaturization, holds significant promise for next-generation wearable devices and autonomous robotic systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
8
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
sEMG-Based Wearable HMI System For Real-Time Robotic Arm Control With Edge AI
5 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: State Key Laboratory of Transducer Technology, Chinese Academy of Sciences

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago