Despite a long-standing effort on the automation in the care of critically ill patients, prior automation capabilities have not been suitably mature for real-world use due to a few limitations: (1) the decisions/actions of the automation could not be easily interpreted by clinicians, preventing clinicians' effective interaction with and supervision of the automation for safe patient care; (2) the automation was designed to perform a particular task of interest without accounting for the overall physiological state of the patient; (3) multiple automation functions were not often coordinated to avoid possible conflicts in patient treatment; (4) automation was prone to errors in the medical devices; and (5) regulatory science for evaluation and approval of safety-critical automation capabilities was lacking. This research program seeks to address these fundamental challenges by studying novel methodologies for (1) mathematically representing the patient physiology in a way to facilitate the interpretation of clinicians and (2) designing automation capabilities that can facilitate clinician interaction and supervision, coordination of multiple treatment goals and functions, and resilience to device errors and faults. In addition, this research program will benefit society and Science, Technology, Engineering and Mathematics (STEM) education by creating a wide range of automation systems that can improve the quality of care of critically ill patients, expediting the deployment of new medical devices with advanced automation capabilities, facilitating the evaluation and approval of emerging healthcare automation capabilities, and training STEM workforce especially from underrepresented minorities.

Despite a long-standing effort on the automation in the care of critically ill patients, prior automation capabilities have not been suitably mature for real-world use due to a few limitations: (1) the decisions/actions of the automation could not be easily interpreted by clinicians, preventing clinicians' effective interaction with and supervision of the automation for safe patient care; (2) the automation was designed to perform a particular task of interest without accounting for the overall physiological state of the patient; (3) multiple automation functions were not often coordinated to avoid possible conflicts in patient treatment; (4) automation was prone to errors in the medical devices; and (5) regulatory science for evaluation and approval of safety-critical automation capabilities was lacking. This research program seeks to address these fundamental challenges by studying novel methodologies for (1) mathematically representing the patient physiology in a way to facilitate the interpretation of clinicians and (2) designing automation capabilities that can facilitate clinician interaction and supervision, coordination of multiple treatment goals and functions, and resilience to device errors and faults. In addition, this research program will benefit society and Science, Technology, Engineering and Mathematics (STEM) education by creating a wide range of automation systems that can improve the quality of care of critically ill patients, expediting the deployment of new medical devices with advanced automation capabilities, facilitating the evaluation and approval of emerging healthcare automation capabilities, and training STEM workforce especially from underrepresented minorities. With the long-term vision of enabling interpretable white-box autonomy in healthcare by advancing generalizable methodologies for medical cyber-physical systems (M-CPS), the objective of this CAREER program is to investigate physiological modeling, coordinated and resilient multivariable closed-loop control, and regulatory science methodologies in circulatory resuscitation. An integrated research, education, and outreach program is proposed to achieve this objective. On the research front, physiological modeling and closed-loop control methodologies applicable to white-box autonomy in a wide range of circulatory resuscitation scenarios will be investigated. Specifically, generalizable methodologies for (1) patient physiology and pharmacology modeling and (2) coordinated and resilient multivariable closed-loop control will be developed. The value of these methodologies will be demonstrated by developing interpretable white-box physiological closed-loop control algorithms for circulatory resuscitation. On the education and outreach front, members of the next-generation M-CPS workforce will be trained and regulatory science for evaluating critical care autonomy capabilities will be advanced. Specifically, (1) graduate, undergraduate, and K-12 students will be attracted into STEM and M-CPS, (2) collaboration with the US Food and Drug Administration will be performed to investigate testing methodologies and tools for physiological models and closed-loop M-CPS via its Medical Device Development Tools Program, and (3) newly created knowledge will be disseminated to further advance M-CPS research and education.