Papers
2
Total Citations
39
H-Index
2
About
Sailan Liang investigates the neural mechanisms underlying robot-assisted rehabilitation, with a focus on how the brain adapts to different training modalities. Her work bridges neurorehabilitation engineering and cognitive neuroscience, particularly through the use of functional near-infrared spectroscopy (fNIRS) to map cortical activation patterns. In her highly cited 2021 study (26 citations), she demonstrated that active and passive training modes of upper-limb rehabilitation robots elicit distinct cortical responses, with speed-dependent effects that inform personalized therapy design. Her 2022 work (13 citations) advanced this line of inquiry by identifying interacting brain networks during robot-assisted training with multimodal stimulation, revealing how visual and auditory cues can enhance neural engagement. These contributions provide a neurophysiological foundation for optimizing rehabilitation protocols, moving beyond purely mechanical assistance to brain-responsive therapy. Liang’s research has significant implications for stroke recovery and motor rehabilitation, offering evidence that robotic training can be tailored to individual neural states. Her work is widely cited in rehabilitation robotics and neuroimaging communities, establishing her as a key voice in the integration of brain-computer interfaces with physical therapy.
Research Focus
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Top Papers
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