Sleep tracking in consumer hardware products has been around for a while — Fitbit, for instance, has provided it for 15 years. But these tracking and analysis offerings have evolved over time. “We’ve added so much more capability,” says Dr. Conor Heneghan. Conor is a research scientist who works on sleep health at Google across consumer hardware. His team is responsible for developing the helpful new sleep features for Fitbit and Pixel Watch, which uses Fitbit’s health and fitness technology.
A lot of this progress is thanks to AI. “The team I work on relies on various machine learning algorithms to do our work,” Conor says. These algorithms work like this: Your device detects raw sensor signals — like movement or reflected light — and uses algorithms to map these signals to other useful information, such as your heart rate and your steps. Additional algorithms then take this data and map it to even more complicated concepts, like your sleep stage or your stress level, so that you have more helpful information to act on. “We can combine all of these bits of information together to get really detailed information related to sleep,” says Conor.
Here’s a look at how AI powers sleep features on devices like Fitbit, Pixel Watch and Nest Hub (2nd gen), and how they can help you get better rest.
- Sleep Tracking. Fitbit’s sleep technology powers the sleep-tracking capabilities across Pixel Watch and Fitbit devices. Specifically, Fitbit’s sleep-tracking algorithm looks for patterns in your movement and heartbeat intervals to estimate what stage of sleep you’re in and how long you’ve been sleeping. Your device then shares this information to you in a bunch of different ways (more on that in a bit). The sleep-tracking algorithm works by combining multiple algorithms at once. One detects the time between each individual heartbeat by looking at the reflected optical signal from your wrist. Another characterizes your movements by looking at the accelerometers (motion sensors) in your device. This information is sent to the Fitbit cloud site where a machine learning algorithm combines the heartbeat and movement information to estimate what stage of sleep you’re in and when your sleep started and ended.
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