Raofen Wang

Shanghai University of Engineering Science

Papers

Total Citations

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About

Raofen Wang is a leading researcher in brain-computer interfaces (BCIs), with a primary focus on steady-state visual evoked potential (SSVEP) systems. Her most cited work, "Filter Bank-Driven Multivariate Synchronization Index for Training-Free SSVEP BCI" (2021, 39 citations), addresses a critical challenge in the field: improving frequency detection without requiring user training. Wang introduced a filter bank approach to the multivariate synchronization index (MSI) algorithm, enabling more robust extraction of SSVEP signals from noisy EEG data. This innovation significantly enhances the practicality of BCIs for real-world applications, such as communication aids for individuals with severe motor disabilities. Her contributions have been recognized for advancing training-free BCI paradigms, reducing setup time while maintaining high accuracy. With her work cited in numerous subsequent studies on signal processing and neural engineering, Wang continues to shape the development of accessible, high-performance brain-computer interfaces.