Apple Watch Can Detect Abnormal Heart Rate Rhythm With An Accuracy Of 97 Percent, Confirms Study

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Mar 21, 2018
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The Apple Watch is a very capable device with powerful internals. It packs a boatload of features that extend from calling your contacts to checking the rhythm of your heart. It features fitness tracking capabilities as well which might be its main selling point for some users. However, a new study has confirmed that the Apple Watch features 97 percent accuracy in detecting abnormal heart rhythms. So let’s dive in to see some more details on the matter.

Apple Watch Features 97 Percent Accuracy When It Comes To Detecting Abnormal Heart Rhythms

The study was conducted by the team behind the Cardiogram app for the Apple Watch in collaboration with researchers at the University of California, San Francisco. Over a course of data gathered from 139 million heart rate and counted steps from 9,750 users of Cardiogram app. The users also enrolled in the UC San Francisco Health eHeart Study. The data accumulated can be used to train DeepHeart, Cardiogram’s neural network.

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Once the DeepHeart neural network is trained and able to read heart rate data gathered by the Apple Watch, it can distinguish between a normal heart rhythm and an atrial fibrillation with 97 percent of accuracy. The accuracy applies to both when testing UCSF patients and Cardiogram participants. The study was published in JAMA Cardiology this morning.

97% accuracy refers to the c-statistic, or area under the sensitivity-specificity curve. Surprisingly, both the sensitivity and specificity of DeepHeart were even higher than an FDA-cleared Apple Watch ECG attachment — 98% (vs 93%) sensitivity and 90% (vs 84%) specificity.

Trial Fibrillation is a major health condition which can lead to major health risks and can lead to a stroke and even heart failure. While the Apple Watch will not replace a conventional EKG, it has the potential to alert people much earlier.

This proof-of-concept study found that smartwatch photoplethysmography coupled with a deep neural network can passively detect AF but with some loss of sensitivity and specificity against a criterion-standard ECG. Further studies will help identify the optimal role for smartwatch-guided rhythm assessment.

Cardiogram and UCSF have also been working to determine if the heart rate monitor on the Apple Watch is able to detect hypertension and more diseases. There will be more to the story, so be sure to stay tuned in for more details.

This is all for now, folks. What are your thoughts on the scenario? Let us know in the comments section below.

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