September 22, 2014
By combining heart rate data from real athletes with a branch of mathematics called control theory, John Doyle, Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and Bioengineering and colleagues have devised a way to better understand the relationship between reduced heart rate variability (HRV) and health.
"A familiar related problem is in driving," Doyle says. "To get to a destination despite varying weather and traffic conditions, any driver—even a robotic one—will change factors such as acceleration, braking, steering, and wipers. If these factors suddenly became frozen and unchangeable while the car was still moving, it would be a nearly certain predictor that a crash was imminent. Similarly, loss of heart rate variability predicts some kind of malfunction or 'crash,' often before there are any other indications," he says. [Caltech Release] [Read the Paper]