Wearable Technology Can Identify Heart Arrhythmias

By HospiMedica International staff writers
Posted on 15 Nov 2018

A new study will evaluate the ability of a smartwatch-based pulse algorithm to identify atrial fibrillation (AF) and guide subsequent clinical evaluation.

Researchers at Stanford University School of Medicine (CA, USA), Apple (Cupertino, Ca, USA) and other institutions have recruited 419,093 participants to a prospective, single arm study with the goal of measuring the proportion of study participants with an irregular pulse detected by the Apple Watch. If a sufficient number of episodes are detected, participant will be asked to undergo ambulatory electrocardiogram (ECG) patch monitoring, which will record their heart rhythms for up to a week. Enrollment, which was conducted through an iPhone app, is now closed.

Image: The Apple Watch may soon detect AF and other arrhythmias (Photo courtesy of Stanford University).

Each participant in the study is required to have an Apple Watch (series 1, 2, or 3) and an iPhone. An app on the phone intermittently checks the heart-rate pulse sensor for measurements of an irregular pulse. The study will determine the percentage of participants receiving irregular pulse notifications that have AF on ECG patch monitoring; determine how many of those who received an irregular pulse notification go on to get medical attention; and to determine the accuracy of irregular-pulse detection by the watch, compared with the simultaneous ECG patch recordings. The study was published on November 1, 2018, in the American Heart Journal.

“The study has entered the final phase of data collection and will be completed early next year,” said senior researcher cardiologist Mintu Turakhia, MD. “We now have access to high-quality sensors that can measure and detect changes in our bodies in entirely new and insightful ways without even needing to go to the doctor, but we need to rigorously evaluate them. There's never really been a study like this done before.”

The Apple Watch’s sensor uses green light emitting diode (LED) lights flashing hundreds of times per second and light-sensitive photodiodes to detect the amount of blood flowing through the wrist. Using a unique optical design, the sensor gathers data from four distinct points on the wrist. Powerful software algorithms isolate actual heart rhythm sounds from other noise.

Related Links:
Stanford University School of Medicine
Apple