Papers
6
Total Citations
130
H-Index
5
About
Xingguo Long is a leading researcher in rehabilitation robotics, specializing in lower-limb exoskeleton systems that restore mobility to patients with stroke or spinal cord injury. His work bridges multiple control modalities—vision assistance, surface electromyography (sEMG), and brain-computer interfaces (BCI)—to create intuitive, adaptive exoskeletons. Long’s most influential paper, “Vision-Assisted Autonomous Lower-Limb Exoskeleton Robot” (87 citations), tackles the critical challenge of complex terrain navigation, enabling patients to walk more naturally. He further advanced the field with real-time sEMG-based active control (16 citations) and haptic-visual enhanced motor imagery BCI (10 citations), improving human-robot interaction efficiency. His bionic mechanical designs, including stair-climbing gait planning (8 citations), demonstrate practical daily-living applications. Long also optimized EEG-based exoskeleton systems through channel selection strategies (5 citations), reducing computational load while maintaining performance. Beyond medical robotics, he developed the OM-C01 intelligent quadruped robot (4 citations), showcasing his versatility in bionic design. With cumulative citations exceeding 130, Long’s work is foundational for next-generation assistive devices, directly impacting rehabilitation engineering and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Vision-Assisted Autonomous Lower-Limb Exoskeleton Robot87 citations · 2019
- 2Real-time Active Control of a Lower Limb Exoskeleton Based on sEMG16 citations · 2019
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- 6Design and Development of an Intelligent Pet-Type Quadruped Robot4 citations · 2021