Papers
2
Total Citations
25
H-Index
1
About
Qiqi Ma is a pioneering researcher at the intersection of rehabilitation robotics, virtual reality (VR), and cognitive neuroscience. Her work focuses on understanding how robot-assisted multi-sensory training—combining force-haptic feedback with visual and auditory cues—modulates brain activity during motor rehabilitation. Using functional near-infrared spectroscopy (fNIRS), Ma has provided groundbreaking insights into cortical activation patterns during both dynamic and static (isometric) resistance training. Her most-cited study (2023, 24 citations) demonstrated that VR-enhanced interactive training significantly engages cognitive and motor cortex regions, offering a neural basis for more effective rehabilitation protocols. A second influential paper (2023) further explored the distinct cortical responses to dynamic versus isometric exercises, addressing a critical gap in upper-limb rehabilitation robotics. Ma’s work is notable for bridging engineering, neuroscience, and clinical application, with implications for stroke recovery and neurorehabilitation. By quantifying how different training modalities activate the brain, she is helping to design smarter, more personalized robotic therapies. Her research is essential reading for anyone interested in neurorehabilitation, human-robot interaction, or the neural mechanisms of motor learning.
Research Focus
Key Achievements
Top Papers
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