Yiqi Zhou

Papers

Total Citations

H-Index

About

Yiqi Zhou’s research lies at the intersection of rehabilitation robotics, biomedical signal processing, and human–machine interaction, with a focused commitment to restoring motor function in patients with upper limb impairments. Zhou’s foundational work, “Design of an Upper Limb Rehabilitation Robot Based on Medical Theory” (2011, 16 citations), established a critical medical-theoretical framework for robot-assisted therapy, translating principles of motor recovery into tangible robotic design. This contribution helped shift rehabilitation paradigms from traditional manual therapy to precise, repeatable robotic assistance. Building on this, Zhou advanced the field by developing methods for identifying upper limb motion through surface electromyography (sEMG) in “The Signal Processing and Identification of Upper Limb Motion Based on sEMG” (2018, 16 citations), enabling more intuitive, bio-signal-driven control of rehabilitation devices. Further exploring control theory, Zhou investigated fractional order control systems integrated with sEMG signals (2015), pushing the boundaries of how robotic systems can adapt to a patient’s physiological state. With over 30 total citations, Zhou’s work has directly informed the design of smarter, more responsive rehabilitation robots, making significant strides toward personalized, data-driven recovery for patients with neuromuscular injuries.