Papers
2
Total Citations
26
H-Index
2
About
Ruoqing Zhang is a rising researcher at the forefront of neurorehabilitation, specializing in hybrid brain-computer interfaces (BCIs) and soft robotics for stroke recovery. Their work centers on integrating motor imagery (MI) with steady-state visual evoked potentials (SSVEP) to enhance BCI performance, directly addressing the limitations of static visual feedback in rehabilitation systems. Zhang’s most cited paper, "Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation" (2024, 24 citations), demonstrates a novel approach by combining a soft robotic glove with a hybrid BCI, achieving improved hand rehabilitation outcomes for stroke patients. This work highlights their contribution to making BCI systems more intuitive and effective. Their subsequent 2025 study further refines this integration, using peripheral field SSVEP stimulation to boost user engagement and control. With a growing citation impact, Zhang’s research bridges engineering and clinical application, offering scalable solutions for motor recovery. Their achievements underscore a commitment to advancing assistive technologies, positioning them as a key innovator in the field of neurorehabilitation and human-machine interaction.
Research Focus
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Top Papers
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