Soon, cars may predict if you are having a heart attack
Researchers are using machine-learning models to analyse the data collected from in-hospital and in-vehicle subjects. The research team will then test the system on real-time prediction of cardiac events.
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Washington: Scientists are developing a new system that can predict if a car driver is about to have a heart attack, a feature that would help avoid road accidents due to an unexpected cardiac event.
When a person has a medical emergency behind the wheel, fellow passengers and motorists also face risk of death or serious injury.
"A large number of traffic incidents are caused by medical conditions while driving, specifically cardiovascular events, such as myocardial infraction and myocardial ischemia," said Kayvan Najarian, from University of Michigan in the US.
"The medical event interferes with the driver's ability to safely drive and operate the car, causing the accident," said Najarian.
Researchers, in collaboration with Japanese automotive manufacturer Toyota, wanted to move towards technology that can monitor and analyse the physiology of the person driving and predict if they are going to have adverse cardiac events.
"We identified the challenges, potential solutions, hardware options and algorithmic approaches that could be potentially used," Najarian said.
"We concluded that cardiac events were conditions that are more feasible to detect with technology in the vehicle," he added.
Researchers are creating a system that could be placed in the vehicle to monitor and predict an adverse cardiac event.
"We would like to test hardware we had previously identified, and improve and validate our algorithmic solutions to see what it will take to generate a system that could look at the physiology of a person, provided by high-density electrocardiogram (ECG) measurements, as well as other medical measurements," Najarian said.
Their goal is to come up with a system that would predict the occurrence of adverse cardiac events in real time.
Researchers are using machine-learning models to analyse the data collected from in-hospital and in-vehicle subjects. The research team will then test the system on real-time prediction of cardiac events.
"There are actually quite a few obstacles that were identified," Najarian said.
"You can't have clinical-grade monitoring devices in the vehicle. You need to use a high-quality monitoring device in the vehicle that, despite all the in-vehicle noise, could reliably register the driver's ECG without being large and obtrusive," he added.
The research team will begin gathering the physiological data from the driver using heart monitors approved by the US Food and Drug Administration.
Such monitors are patches placed on the driver's chest that analyse 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.
"When we analysed crash statistics already reported by different agencies, we found that drivers 65 years of age and older have a lot of medical-related issues that are related to vehicle crashes," Najarian said.
"We can infer from that information that there could be a higher number of crashes in the future as the population is ageing," he added.
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