Papers
1
Total Citations
10
H-Index
1
About
Ruizhu Zhang is a researcher at the forefront of human-robot interaction, with a primary focus on lower-limb exoskeleton robotics and bio-signal processing. Their most cited work, "A Real-Time Gait Switching Method for Lower-Limb Exoskeleton Robot Based on sEMG Signals" (2019), introduces a novel approach to enabling seamless, intuitive control of assistive devices by leveraging surface electromyography (sEMG) signals. This contribution addresses a critical challenge in rehabilitation robotics: achieving fluid, user-responsive gait transitions without manual intervention. By demonstrating that muscle activity patterns can reliably trigger real-time mode shifts, Zhang’s method enhances both safety and autonomy for individuals with mobility impairments. Though still early in their career, this work has garnered 10 citations, signaling growing recognition among peers in the exoskeleton and neurorehabilitation communities. Zhang’s research bridges the gap between neural control and mechanical assistance, offering a pathway toward more natural, adaptive prosthetic and orthotic systems. Their work holds particular promise for advancing personalized rehabilitation protocols and restoring mobility in clinical and daily-life settings.
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Top Papers
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