Tianyou Yu

Papers

Total Citations

194

H-Index

About

Tianyou Yu is a leading researcher in brain-computer interfaces (BCIs) and assistive robotics, specializing in hybrid systems that integrate neural signals with autonomous control. His major contributions center on developing practical, multi-functional assistive devices for severely disabled individuals. His most cited work (2019, 97 citations) introduced an EEG-/EOG-based hybrid BCI to control an integrated wheelchair robotic arm system, solving the critical challenge of operating multiple assistive devices simultaneously for complex daily tasks. Yu advanced this field further with shared control frameworks that combine asynchronous BCI with computer vision for three-dimensional robotic arm manipulation (2023, 55 citations), enabling precise grasping and reaching. His intention-driven semi-autonomous robotic system for drinking (2017, 42 citations) demonstrated how non-invasive brain-machine interfaces could be paired with visual detection to restore independence for patients with severe motor impairments. Yu's research bridges the gap between laboratory BCI demonstrations and real-world assistive applications, addressing the practical challenges of integrating neural control with autonomous robotic intelligence to improve quality of life for individuals with paralysis or neurodegenerative conditions.