Analyzing Transitions in Anesthesia by Multimodal Characterization of Autonomic State

While we have extensively studied the brain dynamics of anesthesia, our understanding of the autonomic dynamics is limited. In this study, we rely solely on a multimodal characterization of autonomic state derived from physiologically accurate models to show three classification results pertaining to autonomic dynamics during propofol sedation: that induction can be separated from emergence, that taking into account history of dynamics improves performance, and that baseline after propofol sedation is distinguishable from baseline before. These results suggest that further investigation into autonomic dynamics before, during, and after anesthesia is warranted.