title: Robust efficiency and actuator saturation explain healthy heart rate control and variability.
abstract: The correlation of healthy states with heart rate variability (HRV) using time series analyses is well documented. Whereas these studies note the accepted proximal role of autonomic nervous system balance in HRV patterns, the responsible deeper physiological, clinically relevant mechanisms have not been fully explained. Using mathematical tools from control theory, we combine mechanistic models of basic physiology with experimental exercise data from healthy human subjects to explain causal relationships among states of stress vs. health, HR control, and HRV, and more importantly, the physiologic requirements and constraints underlying these relationships. Nonlinear dynamics play an important explanatory role--most fundamentally in the actuator saturations arising from unavoidable tradeoffs in robust homeostasis and metabolic efficiency. These results are grounded in domain-specific mechanisms, tradeoffs, and constraints, but they also illustrate important, universal properties of complex systems. We show that the study of complex biological phenomena like HRV requires a framework which facilitates inclusion of diverse domain specifics (e.g., due to physiology, evolution, and measurement technology) in addition to general theories of efficiency, robustness, feedback, dynamics, and supporting mathematical tools.
authors.affiliation: School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138;
authors.forename: Na
authors.initials: N
authors.lastname: Li
authors.affiliation: Department of Computing and Mathematical Science, California Institute of Technology, Pasadena, CA 91125;
authors.forename: Jerry
authors.initials: J
authors.lastname: Cruz
authors.affiliation: Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125;Advanced Algorithm Research Center, Philips Healthcare, Thousand Oaks, CA 91320;
authors.forename: Chenghao Simon
authors.initials: CS
authors.lastname: Chien
authors.affiliation: Department of Neurology, New York University Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY 10016;
authors.forename: Somayeh
authors.initials: S
authors.lastname: Sojoudi
authors.affiliation: Department of Electrical Engineering and Computer Sciences and Department of Statistics, University of California, Berkeley, CA 94720;
authors.forename: Benjamin
authors.initials: B
authors.lastname: Recht
authors.affiliation: Departments of Anesthesiology and Neurosurgery and the Center for Wireless Health, University of Virginia School of Medicine, Charlottesville, VA 22908;
authors.forename: David
authors.initials: D
authors.lastname: Stone
authors.affiliation: Huntington Medical Research Institutes, Pasadena, CA 91101; and.
authors.forename: Marie
authors.initials: M
authors.lastname: Csete
authors.affiliation: Department of Computing and Mathematical Science, California Institute of Technology, Pasadena, CA 91125;
authors.forename: Daniel
authors.initials: D
authors.lastname: Bahmiller
authors.affiliation: Department of Computing and Mathematical Science, California Institute of Technology, Pasadena, CA 91125;Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125;Department of BioEngineering, California Institute of Technology, Pasadena, CA 91125 doyle@caltech.edu.
authors.forename: John C
authors.initials: JC
authors.lastname: Doyle
mesh_terms: D000328:Adult; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006706:Homeostasis; D006801:Humans; D008297:Male; D008954:Models, Biological
keywords: optimal control; respiratory sinus arrhythmia; system identification
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