Tan Jeffrey Too Chuan

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About

Tan Jeffrey Too Chuan is a researcher whose work sits at the intersection of brain-computer interfaces (BCIs) and human-robot collaboration, with a particular focus on assistive and manufacturing technologies. His key research areas include SSVEP-based BCI systems for device control, human-robot interaction in assembly tasks, and the design of collaborative workspaces. Among his notable contributions is the development of an online BCI system that leverages canonical correlation analysis (CCA) for detecting steady-state visual evoked potentials, enabling more reliable and real-time control of external devices such as robots and wheelchairs. This work, published in 2015, has garnered 5 citations and represents an important step toward practical, non-invasive neural interfaces. In earlier work from 2010, Tan explored information support systems for assembly in cell production environments involving human-robot collaboration, a study that has received 2 citations and highlights his interest in optimizing cooperative workflows. While his citation counts are modest, Tan’s research contributes meaningfully to the growing fields of neural engineering and collaborative robotics, offering insights that could enhance accessibility and efficiency in both clinical and industrial settings.