A dual-task paradigm is a method in which an individual executes two tasks, cognitive and motor tasks, at the same time. Typically, when an individual undertakes dual tasks, the performance of both tasks tends to deteriorate compared to when they are performed separately, which phenomenon is known as cognitive-motor interference (CMI). The MOVE lab explores CMI under various conditions of dual-tasking in a virtual reality environment.

Leveraging the power of new technologies, eye tracker, fNIRS, and motion sensor systems, the MOVE lab investigates brain activities during real-life tasks. We focus on discerning the differences in these activities across different populations from healthy adults to the elderly population as well as individuals with neurological impairments. 

Machine learning excels in dissecting complex data. In our laboratory, we try to implement machine learning algorithms for the analysis of the vast amount of data generated from diverse research projects. We aim to uncover hidden insights that may not be discernible through traditional data analysis methods.