About

Effie Chew is a leading figure in neurorehabilitation, whose work sits at the intersection of robotics, brain-computer interfaces (BCIs), and non-invasive brain stimulation. Her research is driven by a singular goal: to restore motor function after stroke. She has pioneered the integration of motor imagery BCIs with robotic feedback and transcranial direct current stimulation (tDCS), demonstrating that this combined approach can significantly enhance neuroplasticity and recovery. Her highly cited 2014 paper on neural network control of rehabilitation robots (253 citations) laid the groundwork for intelligent, interactive therapy systems. Chew’s impact extends from the lab to the clinic; she has led pragmatic, multicentre implementation programmes evaluating overground robotic exoskeletons in real-world inpatient settings and conducted rigorous cost-effectiveness analyses from a health system perspective. Her work on portable knee-ankle-foot robots aims to democratize rehabilitation, moving it from hospitals to home settings. With a portfolio of papers that collectively amass hundreds of citations, Chew is not just advancing technology—she is reshaping the standard of care for millions of stroke survivors worldwide.

Research Focus

Key Achievements

10
H-Index
12
Papers
679
Total Citations
57
Avg Citations/Paper
🏆 Most Cited Paper
Neural Network Control of a Rehabilitation Robot by State and Output Feedback
253 citations · 2014
📈 Most Prolific Year: 2013 (3 Papers)
🤝 Key Collaborators: 49
🏛 Institutions: National University Hospital, National University Health System, National University of Singapore, Alexandra Hospital

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago