Electronic ArticlesEngineering control into medicine☆
Section snippets
Systems and control loops
The term system is often loosely applied. Using an engineering perspective, we define a system as a functional entity of interacting components that accepts and analyzes inputs, and produces outputs. The systems of interest in medicine are generally dynamic, that is, systems with changing inputs and outputs (often widely varying) over time. Control systems are all around us, but largely invisible when they work well: engineered controls maintain the output of our technologies within tolerable
Heart rate control
Heart rate (HR) is an example of an output of a physiologically controlled system that we have studied in the control context [3]. The system requirement in this case is to maintain (control) acceptably small errors in the critical provision of nutrient and oxygen delivery to vital organs, including muscle oxygen delivery in response to both external and internal (eg, inspiratory and expiratory intrathoracic pressure changes) workload disturbances (Fig. 2). Control is accomplished via autonomic
Control systems and disease
Physiologic systems control is dominated by control loops (glucose regulation, circadian rhythms, menstrual cycles, osmoregulation). Degradation in function of a controlled system may occur on the basis of failure of any of the system components, but loss of the controller invariably leads to systems failure (overt disease). As such, many disorders can be considered “loopopathies,” reflecting the importance of the controller (rather than its elements) in pathophysiology (Table 2). Diseases may
Conclusion
Control engineers are experts at designing and analyzing complex systems but have traditionally had little contact with clinicians. Clinicians generally do not consider the control strategies that fail in pathologies they face daily. We maintain that collaboration between engineers and clinicians is now required for the achievement of selected significant advances in medicine. For example, the collaboration of data engineers and clinicians will be required for the design and production of
Acknowledgment
The authors would like to thank Professor John C. Doyle of Caltech for his insightful comments and discussion, and Yuan Lai for his assistance with the figures. Leo Anthony Celi is funded through Grant R01 EB017205-01A1 from the National Institutes of Health.
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Conflict of interest: The authors report no potential conflict of interest that exists with any companies/organizations whose products or services may be discussed in this manuscript.