Papers
2
Total Citations
46
H-Index
2
About
Pengjie Li is a rising researcher in the field of wearable robotics and human motion sensing, with a focus on developing intelligent systems for rehabilitation and assistive technologies. Their work bridges the gap between sensor design and practical applications in exoskeletons and rehabilitation robots. Li’s key contributions include the design of a wireless, fully flexible insole equipped with highly sensitive pressure sensors for precise gait event detection—a crucial component for clinical diagnostics and control strategies in power exoskeletons. This work, cited 24 times, addresses longstanding issues of comfort and accuracy in wearable gait analysis tools. Additionally, Li has pioneered the use of mechanomyography (MMG) for human joint torque estimation in upper extremity exosuits, enabling more intuitive human-robot interaction by decoding muscle activity to predict intended movements. This research, with 22 citations, offers a non-invasive alternative to electromyography, enhancing the responsiveness of rehabilitation devices. Li’s innovative sensor integration and intention-recognition algorithms are paving the way for more adaptive, user-friendly assistive technologies, making significant strides in improving mobility and quality of life for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
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