Characterization and early detection of Paroxysmal Sympathetic Hyperactivity among neurocritical patients
Paroxysmal Sympathetic Hyperactivity (PSH) is the prototypical example of clinically relevant dysautonomia among neurocritical patients. PSH is observed in about one-third of Traumatic Brain Injury (TBI) patients and has been associated with poor outcomes. It is thus of clinical interest to monitor PSH symptoms for early detection and proactive treatment. We are exploring a suite of data analytics/machine learning models to develop deep insights into the temporal dynamics of PSH and related physiological processes. We are also developing a human-in-the-loop framework that integrates experts’ implicit knowledge of PSH into the explicit machine learning framework for automatically detecting PSH from physiological signals.
Collaborators: Dr. Jamie Podell & Teams, University of Maryland Baltimore, School of Medicine
Funding sources: ATIP 2022-2023
- Sancharee Chowdhury (IS Ph.D. student, Fall 2021 – present)
- Sean Kong (IS Ph.D. student, Summer 2022 – present)
- Rohan Salvi (IS master student, Fall 2021 – present)
- Md Fourkanul Islam (IS master student, Spring 2022 – present)