It’s been a year since Stanford Medicine and Apple Inc. embarked on one of the biggest mobile healthcare projects to date by researching if the use of wearables and apps can help to detect patients at risk for heart disease.

In November, 2017,  Stanford and Apple launched a research study to determine whether the Apple watch’s heart-rate sensor can identify irregular heart rhythms associated with atrial fibrillation, which can lead to blood clots and is a leading cause of stroke. Each year in the U.S., atrial fibrillation causes 130,000 deaths and 750,000 hospitalizations.

With the study, Apple and Stanford want to see if the sensor in the Apple watch, which uses LED lights to measure heart rate, can also monitor heartbeat patterns. When used in combination with a mobile device and app, Stanford and Apple are studying to see if mobile technology combined with software algorithms can identify an irregular heart rhythm.

“Through the study, Stanford Medicine will explore how technology like Apple watch’s heart-rate sensor can help usher in a new era of proactive healthcare central to our precision health approach,” says Lloyd Minor, dean of the Stanford School of Medicine.

So far, Stanford has enrolled about 400,000 participants in a clinical trial. The trial is nearing an end and researchers from Stanford and Apple expect to make the results public early next year, though Stanford has yet to release a specific date.

For the study, participants were equipped with an Apple watch and an iPhone. An iPhone app intermittently checks the patient’s heart-rate pulse sensor for measurements of an irregular pulse. If sufficient episodes of an irregular pulse are detected, then the participant receives a notification and is asked to schedule a visit with a doctor involved in the study. Participants are then sent electrocardiography patches, which record the electrical rhythm of their hearts for up to a week.

“This study will help us better understand how wearable technologies can inform health, “Minor says. “These new tools, which have the potential to predict, prevent and manage disease, are finally within our reach.”

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