Liqing Zhang

Papers

Total Citations

173

H-Index

About

Liqing Zhang is a leading researcher in brain-computer interfaces (BCIs) and neural signal processing, with a focus on rehabilitation engineering. Her seminal 2008 work on noninvasive BCIs introduced multiway signal-processing array decompositions, a foundational technique that has garnered 136 citations for advancing the decoding of neural activity. This work not only deepens understanding of brain function but also enables the development of bioengineering control devices and robots for medical applications. Zhang further explored object motion perception through phase discrepancy analysis (2011, 34 citations), contributing to computational neuroscience. Her notable achievement includes pioneering causal neurofeedback-based BCI-FES rehabilitation for post-stroke patients (2013), integrating real-time brain feedback with functional electrical stimulation to restore motor function. This work bridges theoretical signal processing with practical clinical interventions, offering new hope for stroke recovery. Zhang’s research, spanning from fundamental neural mechanisms to applied rehabilitation technologies, has significantly impacted the BCI field, inspiring innovations in assistive robotics and neurorehabilitation. Her contributions continue to shape how researchers and engineers harness brain signals for transformative medical devices.