Mengfan Li

Papers

Total Citations

H-Index

About

Mengfan Li is a researcher working at the intersection of brain-computer interfaces (BCI) and robotics, with a focus on leveraging neural signals to enable intuitive human-machine interaction. Their most notable contribution, "Control of a humanoid robot via N200 potentials" (2014), demonstrates pioneering work in harnessing motion visual evoked potentials (mVEP) — specifically the N200 neural component — to decode user intention and translate it into real-time robotic control. This research addresses a fundamental challenge in assistive robotics: enabling individuals to operate complex systems like humanoid robots through thought alone, without physical input. By designing a specialized visual stimulus interface capable of reliably eliciting and detecting N200 signals, Li's work advances the practical feasibility of mind-controlled robotics. Though still building its citation footprint with 3 citations, this research sits within a rapidly growing field where BCI-driven robotics holds transformative promise for individuals with motor disabilities. Li's contributions reflect a commitment to bridging neuroscience and engineering, pushing the boundaries of how humans can interact with intelligent machines through non-invasive neural decoding techniques.