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This Pro-Athlete Approved Fitness App Uses Medical Tech to Help You Reach ‘Superman Mode’

RocketBody, a#nbsp;fitness tracking Apple Watch app that utilizes ECG technology, was originally developed for professional athletes to#nbsp;help them find what’s called peak performance—or "Superman mode." Pexels

As#nbsp;one of#nbsp;the 25 companies chosen for a#nbsp;60-second flash pitch at TechCrunch Disrupt in#nbsp;San Francisco this month, RocketBody is#nbsp;currently leading the electrocardiography (ECG)-based fitness pack. By#nbsp;processing ECG data through the wrist using machine learning, the subscription training service can customize workouts based on#nbsp;the user’s fitness condition, recovery level and "optimal load level."

It#nbsp;all began four years ago, when former professional wrestler Tim Lipsky began work on#nbsp;fitness tracking technology aimed at#nbsp;helping athletes train safely. Eventually, he#nbsp;and his team ended up#nbsp;working with what’s now known as#nbsp;ECG signal processing, which Apple launched beginning with its Series 4 watch. What began as#nbsp;a#nbsp;proprietary wearable, mainly sold to#nbsp;professional sports players, has become one of#nbsp;the earliest examples of#nbsp;ECG use in#nbsp;consumer health tech.

SEE ALSO: Here’s What Peloton’s IPO Could Mean for the Digital Fitness Industry

Following RocketBody’s pre-seed investment round in#nbsp;2017, the team went on#nbsp;to a#nbsp;successful Kickstarter campaign and the launch of#nbsp;RocketBody’s official Apple Watch app in#nbsp;2018. They also closed a $#nbsp;1 million Series A#nbsp;round in#nbsp;September, led by#nbsp;Gagarin Capital Partners. Observer recently spoke with founder and CEO Lipsky, who described how an#nbsp;injury inspired RocketBody’s sophisticated data-driven fitness features.

RocketBody CEO Tim Lipsky discusses ECG’s impact on#nbsp;digital fitness tracking.

How did the idea for RocketBody originally come about? The inspiration came from when I#nbsp;was a#nbsp;professional athlete for 10 years and ended up#nbsp;with an#nbsp;injured spine and knee. At#nbsp;the time, my#nbsp;goal for building a health tracker was to#nbsp;get myself out of#nbsp;bed. What I#nbsp;wanted was to#nbsp;come back to#nbsp;sports. During that time, I#nbsp;founded a#nbsp;sports supplement company catering to#nbsp;consumers in#nbsp;Russia, Ukraine and Belarus.

Our original mission during the pre-research phase of#nbsp;the RocketBody app was to#nbsp;prevent athletes from overtraining or#nbsp;overworking. The reason for this is#nbsp;because we#nbsp;actually end up#nbsp;feeling more tired if#nbsp;we#nbsp;do fitness when our body isn’t ready. This is#nbsp;how the idea was born four years ago, when I#nbsp;started RocketBody.

Explain to#nbsp;us#nbsp;how electrocardiography (ECG) technology was eventually developed and began being used by#nbsp;RocketBody on#nbsp;its original device. We#nbsp;began by#nbsp;working Paul Bulai, a#nbsp;biophysicist, neuroscientist and associate professor at#nbsp;Belarusian State University, to#nbsp;develop a#nbsp;consumer-friendly product that does blood analysis. Most people don’t get their blood tested often for practical reasons, but we#nbsp;know it’s helpful for fitness training because it#nbsp;provides an#nbsp;understanding of#nbsp;muscle activity and heart rate, not just calories and steps.

This is#nbsp;how we#nbsp;started investigating electrocardiography (ECG), which records the rhythm of#nbsp;the heart’s electrical signals, spending a#nbsp;year studying how ECG’s focus on#nbsp;the combination of#nbsp;blood work and heart rate could help us#nbsp;build our device.

The original wrist tracker was comparable to#nbsp;athletes collecting exercise data while wearing a#nbsp;training mask to#nbsp;achieve VO2 max (maximum oxygen uptake). This combination hardware and software device also included machine learning, and professional athletes began ordering a#nbsp;lot of#nbsp;our devices.

RocketBody pitched its Apple Watch app during TechCrunch Disrupt 2019 in#nbsp;San Francisco.

Tell us#nbsp;how you decided to#nbsp;pivot to#nbsp;software with the launch of#nbsp;the RocketBody Apple Watch app. When we#nbsp;were developing our technology, measuring ECG through the wrist was still strictly a#nbsp;medical process. First, we#nbsp;worked on#nbsp;our own devices and launched it#nbsp;to#nbsp;several markets in#nbsp;Europe, operating as#nbsp;B2B because professional athletes were our market. We#nbsp;helped them find what’s called peak performance, or "Superman mode," in#nbsp;which they can do#nbsp;more than they usually do.

Around 2017, we#nbsp;knew that the Apple Watch 4 would also come up#nbsp;with ECG, which prompted us#nbsp;to#nbsp;pivot to#nbsp;B2C and create our own consumer app. Over the next several months, the team developed and submitted two patent applications, which allowed the company to#nbsp;launch all algorithms two weeks after the release of#nbsp;the ECG function on#nbsp;Apple Watch in#nbsp;2018. The company then uploaded the first version of#nbsp;RocketBody to#nbsp;the App Store and partnered with professional speed skating athletes and the [Belarusian] Biathlon Federation.

ECG is#nbsp;currently at#nbsp;the cutting edge of#nbsp;the wildly popular "digital fitness" category. Describe RocketBody’s value for serious fitness-focused consumers and how it#nbsp;differs from say, Fitbit’s new monthly subscription service.When we#nbsp;compare our app with others out there, we’re also speaking about how ECG is#nbsp;helping us#nbsp;understand our bodies better since it#nbsp;provides more info than just standard heart rate. For example, after just one 30-second monitoring session, RocketBody’s software will provide you with a#nbsp;workout based on#nbsp;your current body’s state, including muscle energy and restfulness. The use of#nbsp;ECG technology reflects the same reliable results as#nbsp;blood testing or#nbsp;mask training, making it#nbsp;a#nbsp;reliable indicator of#nbsp;your body’s physical needs at#nbsp;the moment.

Today, we#nbsp;all know we#nbsp;need to#nbsp;be#nbsp;healthy and proactive when it#nbsp;comes to#nbsp;fitness, but with machine learning there are ways to#nbsp;be#nbsp;highly precise about it.

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2019-09-10 17:54 News