Siqi Huang
Papers
1
Total Citations
11
H-Index
1
About
Siqi Huang is a rising researcher in neural rehabilitation engineering, specializing in the intersection of soft robotics and brain-computer interfaces. Her work centers on understanding how mirror visual feedback (MVF) combined with robotic systems can enhance motor recovery after neurological injury. In her most-cited study (2022, 11 citations), Huang investigated the synergistic effects of MVF paired with a soft robotic bilateral hand rehabilitation system, using functional near-infrared spectroscopy (fNIRS) to map cortical activation patterns. This self-controlled trial with 20 healthy subjects revealed immediate, synergistic cortical responses, providing mechanistic insights into why combination therapies may outperform single-modality interventions. Her research bridges the gap between wearable robotics and neuroplasticity, offering a foundation for more effective, evidence-based rehabilitation protocols. While early in her career, Huang’s work has already contributed to the growing field of closed-loop rehabilitation systems, where real-time neural feedback guides robotic assistance. Her findings hold promise for stroke survivors and patients with hand motor deficits, positioning her as an emerging voice in translational neuroengineering.
Research Focus
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Top Papers
- 1