Apple Watch can detect sleep apnea and hypertension, study shows

The Apple Watch on display

Hypertension - also known as high blood pressure - was detected by the Apple wearable with an accuracy of 82 percent.

Researchers have found the Apple watch can be successfully used for precise detection of hypertension and sleep apnea. Cardiogram is a company that has an app that breaks down the heart rate data that is collected by the Apple Watch. This new study will have a big impact in medicine by somehow eliminating all the need of physical check-up for the diagnosis of hypertension and sleep apnea [which are both common but serious medical conditions by the way] using a simple device.

The study proved accurate enough in its diagnosis of these conditions that Cardiogram believes with additional research, wearables like the Apple Watch could be used as a cheap way to diagnose these conditions.

The study was conducted by health startup Cardiogram and UCSF and followed more than 6,000 subjects, some of whom had diagnosed hypertension and sleep apnea.

Sleep apnea affects an estimated 22 million adults in the US, with another 80 percent of cases of moderate and severe obstructive sleep apnea undiagnosed, according to the American Sleep Apnea Association.

At first glance, the association between heart rate, high blood pressure, and sleep apnea may seem surprising.

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Sleep apnea is a potentially serious sleep disorder largely associated with heavy snoring in which breathing repeatedly stops.

According to the Centers for Disease Control (CDC), 75 million USA adults suffer from hypertension.

This study recruited participants for a Health eHeart study and trained the DeepHeart neural network to detect new variables with heart rate.

According to Brandon Ballinger, Cardiogram co-founder, DeepHeart was trained on data gathered from 70 percent of total participants and then tested again on the remaining 30 percent data that were not used in the previous training.

The research claims that data from wearable heart rate sensors, when combined with machine learning algorithms, can surface hidden patterns that predict whether a person is at risk for certain health problems.

"The idea here is that by screening continuously you would identify people with hypertension who might not know they have it", Cardiogram's Johnson Hsieh, who lead the study, told TechCrunch.

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