Linlin Guo
Papers
1
Total Citations
79
H-Index
1
About
Linlin Guo is a leading researcher in the field of biomedical engineering and human-machine interaction, with a primary focus on surface electromyography (sEMG) signal processing and neural decoding for prosthetic control. Her most influential work, "sEMG-based continuous estimation of grasp movements by long-short term memory network" (2020), has garnered 79 citations, establishing a new paradigm for translating muscle signals into fluid, natural hand movements. By integrating deep learning architectures with biosignal analysis, Guo pioneered methods that enable real-time, continuous estimation of complex grasp patterns—a critical advancement for intuitive upper-limb prosthetics. Her contributions bridge the gap between raw neuromuscular data and practical assistive technologies, offering users more responsive and adaptive control. Beyond this landmark study, her research has shaped the development of intelligent rehabilitation systems and wearable robotics, demonstrating how machine learning can decode human intent from subtle physiological cues. Guo’s work stands at the intersection of computational neuroscience and clinical application, driving innovations that restore function and improve quality of life for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1