Fitness trackers/wearables have been all the rage for years now. They’ve been hailed as a great new development for fitness, and equally derided as narrowly effective to the affluent only. But as it turns out, they’re not just good for prompting you into consistent athletic motion. They don’t only provide attaboys to you when you’ve worked out that day. They might just save your life. With the right algorithm, medical researchers think they might have done just that.
As is true with so many technologies and companies these days, data reigns supreme. The more data they can collect, the more valuable whatever their offering might happen to be. Some companies have gotten in a lot of trouble recently for how aggressively they pursue (or how carelessly they protect) that data (looking at you Google and Facebook), but the maxim still holds. Data is king and companies want as much of it as they can get. But the best data doesn’t mean anything if you don’t have the tools to make sense of it. That’s where AI has been shining in recent years, and it could be a game changer on so many fronts.
Our particular front of note today is in wearable technology. Wearables have been hailed as the next great technology for years, only for the returns to come back… tepid. The original iterations of so many wearables left a lot to be desired, and many of the studies purporting to their ineffectuality were tinged by the fact the original versions of so many of these devices weren’t sticky enough to engender constant usage.
Well, many of those ‘stickiness’ problems have since been solved. And wearables are proving to be really effective in one thing — data collection. Even if you don’t necessarily act on that data immediately, the devices are collecting loads of valuable data, if you only know where and how to look.
Gregory Marcus, M.D., director of clinical research at the UCSF Division of Cardiology, discovered fitness trackers can be an absolute gold mine of potentially life-changing medical data, but only if you know where to look and how to analyze it. By leveraging an algorithm called DeepHeart, Dr. Marcus parsed through data from thousands of Fit Bit and Apple Watch users to spot signs of atrial fibrillation, a common heart condition that can often be asymptomatic (meaning you don’t see any of the symptoms), but it can sometimes cause the heart to go haywire. Larry Bird, of Boston Celtics fame, famously suffered from the condition.
By using a superior monitoring device, owing to its ‘always on’ nature, these wearables can provide the raw heartbeat data Dr. Marcus’s algorithm needs to better predict atrial fibrillation. It’s not foolproof, obviously, but it’s a massive step forward in medical diagnosis that could potentially be applied to other wearable measurements given the right conditions.
More generally, it’s another step toward machine learning and AI making massive inroads into medical diagnosis, tracking and followup, hopefully improving health outcomes for generations to come.
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