Yunmeng Liu

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About

Yunmeng Liu is a leading researcher in neurorehabilitation, specializing in the intersection of brain-computer interfaces, motor recovery, and neural plasticity following stroke. Her most-cited work, "Changes in electroencephalography complexity and functional magnetic resonance imaging connectivity following robotic hand training in chronic stroke" (2020, 25 citations), represents a pivotal contribution to understanding how robotic-assisted therapy reshapes brain function. By combining EEG complexity analysis with fMRI connectivity measures, Liu demonstrated that robotic hand training not only improves motor control but also induces measurable reorganization of cortical networks in chronic stroke survivors. This dual-modality approach has established a new paradigm for assessing rehabilitation efficacy, bridging clinical outcomes with neurophysiological biomarkers. Her research has significant implications for designing personalized, technology-driven therapies that leverage neural plasticity. Liu’s work is widely recognized for advancing the integration of non-invasive brain monitoring into rehabilitation protocols, offering hope for patients with long-standing motor deficits. Her findings continue to influence both clinical practice and the development of adaptive robotic systems, positioning her as a key figure in translational neuroscience and restorative neurology.