Smart speakers serve as cardiac arrest detection system
Researchers at the University of Washington have developed a tool that monitors people at home for cardiac arrest while they’re sleeping by capturing audio samples.
Researchers at the University of Washington have developed a tool that monitors people at home for cardiac arrest while they’re sleeping by capturing audio samples.
The tool, which uses smart speakers such as Amazon Alexa and Google Home, is trained to detect agonal respiration, an abnormal pattern of breathing associated with about half of people who experience cardiac arrests.
“A lot of people have smart speakers in their homes, and these devices have amazing capabilities that we can take advantage of,” says Shyam Gollakota, an associate professor in the UW’s Paul G. Allen School of Computer Science and 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.”
Gollakota and his colleagues, who plan to commercialize the technology through a UW spinout, published results of a proof-of-concept in the journal npj Digital Medicine.
“We demonstrate that a support vector machine (SVM) can classify agonal breathing instances in real-time within a bedroom environment,” state the authors. “Using real-world labeled 911 audio of cardiac arrests, we train the SVM to accurately classify agonal breathing instances.”
In fact, the tool was able to accurately detect agonal breathing 97 percent of the time. In addition, the algorithm incorrectly categorized a breathing sound as agonal breathing only 0.14 percent of the time.
“This is a good proof of concept using the 911 calls in the Seattle metropolitan area," says Gollakota. “But we need to get access to more 911 calls related to cardiac arrest so that we can improve the accuracy of the algorithm further and ensure that it generalizes across a larger population.”
Ultimately, researchers believe the algorithm could be used as an app or a skill for Alexa that runs passively on a smart speaker.
“The increasing adoption of commodity smart speakers in private residences and hospital environments may provide a wide-reaching means to realize the potential of a contactless cardiac arrest detection system,” conclude the authors.
The tool, which uses smart speakers such as Amazon Alexa and Google Home, is trained to detect agonal respiration, an abnormal pattern of breathing associated with about half of people who experience cardiac arrests.
“A lot of people have smart speakers in their homes, and these devices have amazing capabilities that we can take advantage of,” says Shyam Gollakota, an associate professor in the UW’s Paul G. Allen School of Computer Science and 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.”
Gollakota and his colleagues, who plan to commercialize the technology through a UW spinout, published results of a proof-of-concept in the journal npj Digital Medicine.“We demonstrate that a support vector machine (SVM) can classify agonal breathing instances in real-time within a bedroom environment,” state the authors. “Using real-world labeled 911 audio of cardiac arrests, we train the SVM to accurately classify agonal breathing instances.”
In fact, the tool was able to accurately detect agonal breathing 97 percent of the time. In addition, the algorithm incorrectly categorized a breathing sound as agonal breathing only 0.14 percent of the time.
“This is a good proof of concept using the 911 calls in the Seattle metropolitan area," says Gollakota. “But we need to get access to more 911 calls related to cardiac arrest so that we can improve the accuracy of the algorithm further and ensure that it generalizes across a larger population.”
Ultimately, researchers believe the algorithm could be used as an app or a skill for Alexa that runs passively on a smart speaker.
“The increasing adoption of commodity smart speakers in private residences and hospital environments may provide a wide-reaching means to realize the potential of a contactless cardiac arrest detection system,” conclude the authors.
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