Kar-Ming Fung

Papers

Total Citations

423

H-Index

About

Kar-Ming Fung is a leading researcher in rehabilitation robotics, with a primary focus on developing intelligent, intention-driven systems for stroke recovery. His work centers on the intersection of biomedical engineering and neurorehabilitation, specifically leveraging surface electromyography (EMG) to create assistive devices that respond to a patient’s own muscle signals. Fung’s major contributions include pioneering the design of EMG-driven exoskeleton hand training devices that enable chronic stroke subjects to perform task-specific rehabilitation by detecting their intended movements. His most cited work, "An EMG-driven exoskeleton hand robotic training device on chronic stroke subjects" (2011), has garnered 292 citations, demonstrating its foundational impact on the field. This was preceded by his 2010 paper on an intention-driven hand functions task training robotic system (131 citations), which established the core concept of using hemiplegic-side EMG signals to control robotic assistance. Fung’s innovations have directly advanced the development of more intuitive, patient-responsive rehabilitation technologies, offering new pathways for restoring hand function in individuals with long-term motor impairments. His research remains highly influential among engineers and clinicians seeking to bridge the gap between human intent and robotic action in therapeutic settings.