Stanford Medicine to collaborate on Apple Heart Study

Stanford Medicine to collaborate on Apple Heart Study

Stanford Medicine to collaborate on Apple Heart Study

Apple wants to help catch AFib for its watch users before it's too late.

Apple has launched a new app.

What the Apple Heart Study app does is use the Watch's heart sensor to detect irregular heart rhythms, and then notify users who are experiencing atrial fibrillation (AFib). This is hardly the first health study Apple initiated in recent years, but it's definitely one of the most ambitious ones. Apple says that some 130,000 people die in the United States every year because of AFib, and the condition is responsible for some 750,000 hospitalizations annually.
So how will the Apple Watch identify your irregular heartbeat?

You'll need an Apple Watch that's compatible with the study. Apple employs a small staff of medical professionals to develop its health products, and it is reportedly working on a diabetes glucose-monitoring device that won't pierce the skin.

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This study takes all of that a step further: Now Apple itself will be running a study and submitting data to the Food and Drug Administration.

The sensor in the Apple Watch uses LED lights to measure heart rate. The condition kills about 130,000 people per year, according to estimates from the U.S. Centers for Disease Control and Prevention.

If you're interested in signing up, download the "Apple Heart Study" app in the iTunes store.

That trigger provides an immediate opportunity for participants to speak with a doctor, who can assess the data and determine whether the patient needs immediate medical care or a follow-up consultation.

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The partnership, which includes the telemedicine company American Well, was announced by Apple's Chief Operating Officer Jeff Williams during a company event in September. In our initial studies Apple Watch has been effective at surfacing irregular rhythms.

The Apple Watch is key element in Stanford's mHealth research.

He also noted that the Apple Watch has successfully identified arrhythmia in previous third-party studies. Then, they often must visit them in person to collect data. "We look forward to continuing to apply deep machine learning techniques to uncover hidden physiological signals in ECGs to improve heart and overall human health". Since the launch of Apple's open-source ResearchKit in 2015, universities have been able to use the iPhone and Apple Watch in their medical research.

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