A recent study by Cardiogram in collaboration with the University of California San Francisco (UCSF) has found that wearables like the Apple Watch, Fitbit and others can accurately detect common but serious conditions such as hypertension and sleep apnea.
The study demonstrates the ability of the Apple Watch to detect abnormal heart rhythms with 97% accuracy. This new study shows the Watch can detect sleep apnea with a 90% accuracy and hypertension with an 82% accuracy.
Sleep apnea affects around 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. This is a serious condition where the person affected stops breathing in their sleep, putting them at risk for death.
An additional 75 million Americans have high blood pressure (hypertension), as per the Centers for Disease Control and Prevention. Hypertension puts them at risk of heart disease and stroke, the leading causes of death in the US.
Being able to detect sleep apnea and hypertension from the comfort of our homes with just a simple wearable device could be a game-changer in healthcare. Currently, most patients must visit their doctor and wait for testing intervals that are sporadic, making it hard to diagnose if there’s an increase in blood pressure at critical moments. It is even harder to detect sleep apnea as it occurs while the person is asleep.
The new study recruited 6,158 participants through the Cardiogram app and tested their Apple Watch usage over a period of time. Study leads detected sleep apnea in 1,016 of the participants using DeepHeart, a trained deep learning algorithm developed by UCSF. They also identified hypertension in 2,230 subjects during the study.
The Cardiogram app offers users a glimpse into their heart health and has over 5 million downloads. It encourages people to monitor their heart rate continuously, which could identify individuals with hypertension who might not know they have it. The study’s lead figures believe this can help guide patients through the appropriate diagnosis process.
This marks the third major deep learning study in medicine, following Google Brain’s results on diabetic eye disease in December 2016 and a Stanford study on skin cancer in January 2017.
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