Wenwen Chang

Papers

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About

Wenwen Chang’s research lies at the intersection of cognitive neuroscience and brain-computer interfaces (BCI), with a particular focus on decoding human intention and social cognition from EEG signals. Her work explores how brain dynamics reveal our empathy toward non-human agents—such as robots—and how neural complexity can predict basic motor intentions. In her most cited study (2020, 15 citations), Chang investigated EEG-based functional connectivity during pain empathy, comparing neural responses to humans versus robots, offering insights into human-robot interaction and social neuroscience. More recently, she has advanced BCI-driven rehabilitation systems by developing methods to detect sitting and standing intentions from EEG signals. Her 2023 study (4 citations) introduced dynamical region connectivity and entropy-based features to improve action intention prediction, while her 2022 work (2 citations) focused on EEG complexity measures for the same purpose. Together, these contributions support the development of intelligent walking aid robots and hybrid rehabilitation systems that respond to users’ neural cues. Chang’s work is notable for bridging affective neuroscience with practical BCI applications, making her a rising voice in neurorehabilitation and human-robot interaction.