We are on the threshold of the age of wearables. Google, Samsung and Apple are all looking to stake their claim in this budding market, while smaller companies like Fitbit and Jawbone have already carved out a place on many consumers’ wrists. If you own one of the many wearable fitness trackers on the market today, you’ve probably already come to terms with the fact that what you envisioned as your perfect, straight-out-of-scifi device hasn’t actually aligned with what is available on the market today.
We all have this notion that fitness trackers will alter our behavior by showing us exactly how we workout or sleep each night, but as many of us have found out—and as The Push has written about extensively—the wearable tech revolution still has a ways to go. One possible direction these life companions could be heading is educated predictions.
If you’ve never heard of predictive wearables, don’t feel bad; you’re not behind—yet. Although predictions have been around since before the Mayan calendar, predictive technology as a whole is still relatively new. Some popular examples of predictive technology include Amazon’s product suggestions, Netflix’s movie and TV show recommendations and the Spotify Discover tab. What’s the driving force behind all of these services? Data.
Amazon, Netflix and Spotify have troves of information regarding your browsing and consumption habits. By seeing what you’ve enjoyed or disliked in the past, they have a good idea of what you’ll want in the future. Predictive essentially means that in the normal cycle of input-output, after a certain number of cycles are complete, the device makes guesses for output without receiving input. You know what else has a lot of information about your lifestyle choices? Mobile devices.
Siri, Google Now and Cortana are already starting to bring predictive software to your hand, and with any luck, wearable manufacturers will soon be bringing it to your head, wrists and any body part that can hold their products. While this is a hugely promising area for advancement, the problem with predictive wearables is that predicting things like human movement is a little harder than entertainment preferences. Be that as it may, there are still companies bound and determined to turn your data-gathering activity tracker into a 24/7 personal trainer.
One wearable-tech manufacturer that’s getting it right is Atlas Wearables. This Austin, TX startup is on the cusp of a wrist-worn workout revolution. After making a splash at CES 2014, their Indiegogo campaign reached its fundraising mark five times over. So why are so many people throwing their money at this relatively untested preorder?
The Atlas wristband promises to do much more than count steps and track sleep. One major feature that sets it apart from the competition is its ability to detect a variety of movements, including push-ups, pull-ups and a variety of other physical activities your standard Fitbit fails to recognize. Sure, you can manually input that kind of information into most fitness trackers, but we’ve yet to see a general-market wearable with those capabilities—until now.
The other main feature of the Atlas fitness band is its ability to learn the user’s different movements over time. This learning allows the user to track their workouts effectively and without the traditional delay of jotting down sets and reps. The Atlas also records the amount of weight you lift to give you an idea of how you’re progressing and what your next goal should be.
The Atlas fitness band also gives you feedback on your form as you workout. Any trainer will tell you that an exercise is less effective, and downright dangerous, if executed improperly. By monitoring dips in form, the Atlas fitness band gives you a safer and more efficient gym experience. If the wearable starts detecting that you’re bending your back during squats or overextending elbows during curls, it will suggest you reduce the weight in order to prevent injury and maximize your gains. Conversely, if it sees that you’re not exerting yourself enough, the band will encourage you to increase the weight and utilize your full potential. It’s just like a personal trainer, minus the $90 an hour.
Atlas may have the early jump on the predictive-fitness market, but they won’t be alone for long. The Rithmio fitness tracker is hot on their heels, thanks to the backing of EnterpriseWorks incubator at the University of Illinois. The Rithmio fitness tracker, invented by doctoral student Adam Tilton, uses gesture-recognition research originally used by the US Air Force to track user movements. According to East Central Illinois’s The News-Gazette:
Algorithms in Rithmio’s data analytics software were initially intended to be used for missile tracking and guidance. But along the way, Tilton realized they could also be used to recognize athletes’ movements. Equipped with accelerometer and gyroscope functions, the device can recognize motions in three dimensions. Using a sensor, the software can extract patterns of movements and recognize different motions of the arm — up and down, left and right and clockwise and counterclockwise rotations.
The Rithmio fitness band is as humanistic as it is scientific. As a matter of fact, the entire idea stemmed from a National Science Foundation Innovation Corps training course Adam and his adviser, Prashant Mehta, attended in San Francisco last summer. One of their assignments during the course was to interview 100 potential customers over eight weeks and find out where the technologies in their lives excel and fall short. After interviewing over 150 people, Adam combined his insights and US Air Force technology to create what he says is a “more accurate, specific and personalized” wearable than anything currently on the market.
While these devices represent a leap forward from pedometers and basic accelerometer function, they still only track and repurpose data. Many of the features found in the Atlas Wearables and Rithmio fitness bands are things that humans do and perceive pretty easily on their own. At the end of the day, they don’t amount to much more than an easier means of documentation. Documentation is important, but how does it translate to the gym? On the golf course, players and caddies review extensive notes on the contour of the greens and the play of different pin locations before every shot, but how often does the same occur in weight rooms? The power of data is (or should be) measured by how it is leveraged, not the novelty of its harvest.
Jeremy Hintz is an undergraduate student at the University of Texas at Austin pursuing a degree in Computer Science. He’s also the creator of the Longhorn Game Plan App, a crucial download for any UT sports enthusiast.