Experiencing a cardiac event while driving puts everyone at risk, including other passengers and motorists. Recognizing that a large number of traffic incidents are caused by medical conditions while driving, Toyota is funding development of computational systems, in conjunction with physiological patient monitors, which could be implemented into vehicles. The goal: monitor and analyze the physiology of the person driving and predict if they are going to have adverse cardiac events.

University of Michigan researchers are using machine-learning models to analyze data collected from in-hospital and in-vehicle subjects. The research team will then test the system on real-time prediction of cardiac events.

Installing clinical-grade monitoring devices in the vehicle is not feasible. The engineers will have to focus on deigning a high-quality monitoring device that, despite all the in-vehicle noise, could reliably register the driver’s ECG without being large and obtrusive.

“A challenge for vehicle applications is having a system that can detect small changes in heart rhythms but can also separate out the noise and motion that happens inside the vehicle. In an ICU, there are all types of mechanisms in place to ensure that the monitors are not experiencing electronic interference. That’s not as easy inside a vehicle. We’re going to need to have robust and advanced algorithms,” says Pujitha Gunaratne, Ph.D., principal scientist for the Toyota Collaborative Safety Research Center,

The group will now begin gathering physiological data from the driver using heart monitors approved by the U.S. Food and Drug Administration. Such monitors are patches placed on the driver’s chest that analyze physiological data in real time.

Researchers will continue to test and validate algorithmic and hardware options that could be placed inside the vehicle to monitor the driver’s heart. The team hopes to report results in 2020.

(Source: University of Michigan)