Baozeng Wang

Papers

Total Citations

154

H-Index

About

Baozeng Wang is a leading researcher at the intersection of neural engineering and rehabilitation robotics, with a primary focus on developing intuitive, multimodal human-machine interfaces. His most impactful contribution is the design of a groundbreaking EEG/EMG/EOG-based system that enables real-time control of a soft robotic hand, a work that has garnered over 140 citations. This innovation directly addresses a critical challenge in stroke rehabilitation: providing diverse, natural control commands to leverage neural plasticity for motor recovery. Wang’s expertise extends to advanced signal processing, as demonstrated by his work on nonlinear EEG decoding using particle filter models. By tackling the inherent complexity and non-stationarity of brain signals, he has improved the accuracy and reliability of brain-computer interfaces (BCIs). His research is pivotal in translating BCI technology from laboratory settings into practical, life-changing applications for aging populations and patients with neurological disorders, aiming to restore motor function and enhance quality of life through more responsive and adaptive rehabilitation robots.