Can we use big data to understand functional changes in swallowing, gait and handwriting?
A biomarker is defined as a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In this talk, I will present my efforts to develop computational biomarkers that can characterize temporal and spatial signatures (i.e., the unique patterns of moment-to-moment changes of physiologic variables under normal or pathologic conditions) and their relationship to other variables. Specifically, I will elaborate my efforts to develop computational biomarkers for detecting swallowing difficulties, gait changes and handwriting changes. These computational biomarkers are obtained by mining large data sets in order to characterize changes in the considered functional outcomes under various conditions.