Duanling Li

Beijing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Duanling Li is a researcher whose work sits at the intersection of human-machine interaction, neural signal processing, and robotic control systems. Li's most recognized contributions focus on brain-computer interface (BCI) technology, particularly the innovative integration of electroencephalogram (EEG) and electromyogram (EMG) signals to create hybrid control systems for robotic arms. Recognizing critical limitations in conventional BCI approaches — including single-source signal inputs, low feature recognition accuracy, and constrained output command sets — Li proposed a brain-muscle mixed signal framework that addresses these shortcomings simultaneously, advancing the practical viability of neural-controlled robotics. This research has attracted notable academic attention, with Li's 2022 publication on robotic arm control garnering 17 citations, reflecting growing community interest in multimodal biosignal-driven automation. The work holds significant implications for assistive robotics and rehabilitation engineering, offering pathways toward more intuitive and accurate prosthetic and assistive devices for individuals with motor disabilities. While Li's citation profile is still developing, the focused and applied nature of this research positions them as an emerging contributor to the rapidly evolving field of neuroprosthetics and intelligent human-robot interaction systems.