Engineering Minute

Engineering Minute – Smart Speaker Can Monitor Your Heart

Researchers at the University of Washington have developed a way to monitor a person for cardiac arrest, while they sleep, without using any attached monitoring device. To do so, they use smart phones or speakers, such as Google Home or Amazon Alexa, to detect agonal breathing. Agonal breathing, or gasping for air, is an indicator that a person is experience a heart attack. If the smart device detects agonal breathing, it will call 911. 

 

“A lot of people have smart speakers in their homes, and these devices have amazing capabilities that we can take advantage of,” says co-author Shyam Gollakota, associate professor in the University of Washington’s Paul G. Allen School of Computer Science & Engineering. “We envision a contactless system that works by continuously and passively monitoring the bedroom for an agonal breathing event, and alerts anyone nearby to come provide CPR. And then if there’s no response, the device can automatically call 911.”

 

UW researchers have developed a new tool to monitor people for cardiac arrest while they’re asleep — all without touching them. The tool is essentially an app for a smart speaker or a smartphone that allows it to detect the signature sounds of cardiac arrest and call for help.
UW researchers have developed a new tool to monitor people for cardiac arrest while they’re asleep — all without touching them. The tool is essentially an app for a smart speaker or a smartphone that allows it to detect the signature sounds of cardiac arrest and call for help. Credit: University of Washington

From the University of Washington article: "The researchers gathered sounds of agonal breathing from real 911 calls to Seattle’s Emergency Medical Services. Because cardiac arrest patients are often unconscious, bystanders recorded the agonal breathing sounds by putting their phones up to the patient’s mouth so that the dispatcher could determine whether the patient needed immediate CPR. The team collected 162 calls between 2009 and 2017 and extracted 2.5 seconds of audio at the start of each agonal breath to come up with a total of 236 clips. The team captured the recordings on different smart devices — an Amazon Alexa, an iPhone 5s and a Samsung Galaxy S4 — and used various machine learning techniques to boost the dataset to 7,316 positive clips.

For the negative dataset, the team used 83 hours of audio data collected during sleep studies, yielding 7,305 sound samples. These clips contained typical sounds that people make in their sleep, such as snoring or obstructive sleep apnea.

From these datasets, the team used machine learning to create a tool that could detect agonal breathing 97% of the time when the smart device was placed up to 6 meters away from a speaker generating the sounds."

 

Read more about using your smart speaker to monitor your heart at the University of Washington