Employment Of In Vivo Biosignal Dynamics As Biomarkers Of Sudep

This research seeks to identify novel biological signal patterns that can be used as reliable markers to predict SUDEP risk. We will identify these biosignal patterns by performing innovative mathematical analyses of simultaneous recordings of brain, heart, and lung activity in a two gene model of human SUDEP (Scn2a, Kcna1 double mutant mouse). Currently, utilization of biosignal analyses for the study of SUDEP is very limited and mainly restricted to individual EEG analysis. The envisioned project has the potential to widen this field by applying bioengineering analytical principles to identify interactions and associations between biosignals that can be used to predict SUDEP risk.