Apple Watch, a wearable doctor
“These machine learning tools are a key enabling technology, because with something like hypertension, the way it manifests in our signals is extremely subtle,” said Kumar. “It’s really subtle features of the actual shape of the signal that we get off the sensors…. We’re looking at much more subtle signals that correlate with high blood pressure, because those signals tell us something about how your blood vessels respond every time your heart beats. So, we apply these machine learning techniques to millions of data segments.”
“I’ve been at Apple for 13 years, so I’ve been here along this whole journey,” says Waydo. “And these same kinds of tools make it possible for your watch to track your activity, understand if you’re walking, or swimming in a pool, estimate how long you spend in any sleep stage, identify when you take a fall, so that it can connect you with emergency services. So, we’re using machine learning tools all over the place.”
In each case, Apple finds that it is important to look at how a person’s data evolves over a long period of time, as opposed to just giving a notification based on one moment.
