Papers
1
Total Citations
4
H-Index
1
About
Yixi Chen’s research lies at the intersection of rehabilitation robotics and human motor control, with a focus on developing intelligent assistive technologies for gait recovery. Her most-cited work, “A Center of Mass Estimation and Control Strategy for Body-Weight-Support Treadmill Training” (2021), addresses a critical challenge in post-stroke rehabilitation: the risk of falling and reduced patient engagement caused by fixed weight support and walking speed in body-weight-support (BWS) systems. By proposing a novel control strategy that dynamically estimates and adjusts the center of mass, Chen’s approach enhances safety and promotes active participation during treadmill training for individuals with hemiplegia. This contribution has garnered 4 citations, reflecting its emerging impact on the design of adaptive rehabilitation devices. Chen’s work exemplifies a commitment to bridging engineering and clinical practice, offering a pathway toward more personalized and effective gait training interventions. Her research not only advances the technical capabilities of BWS systems but also underscores the importance of patient-centered design in neurorehabilitation, making her a promising voice in the field of assistive robotics.
Research Focus
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Top Papers
- 1