To help me in my perpetual quest to lose weight and get fit, a friend recently introduced me to an innovative fitness tracker used by professional athletes such as Michael Phelps and LeBron James.

WHOOP is a fitness tracker with sophisticated sensors that’s worn around the wrist. It measures heartbeats per minute, heart-rate variability, electrodermal activity, ambient temperature and 3D acceleration.

The first thing I noticed is that WHOOP doesn’t have a display or buttons. You can’t interact with the device other than tapping it to check the remaining battery life. I still find myself fruitlessly checking it for the time.

WHOOP Fitness Tracker

(Source: WHOOP)

The main difference between WHOOP and the Apple Watch is that the sensors collect data 100 times per second whenever you’re wearing the strap. In comparison, the Apple Watch samples your heart rate every few minutes and only collects heart-rate data at a high frequency during workouts.

And it reminds me of the Big Data gold mine that’s ripe for the picking in the $3.5 trillion U.S. health care market.

Your Individual Physiology

By tracking an incredible amount of data, WHOOP is able to detect minuscule changes in how your body responds to exercise, rest and other stimuli throughout the day and overnight.

It provides a more accurate look into your individual physiology than any other fitness tracker.

When you pair the sensor with a smartphone app, WHOOP provides proprietary metrics such as “day strain,” which is how much you exerted on a given day, and “recovery,” which uses your resting heart rate to determine how rested you are.

Your fitness data is ripe for the picking in the $3.5 trillion U.S. health care market.

Wearing the band in bed allows you to track your sleep, and the app suggests how much sleep you need to be fully rested.

I typically get less than seven hours of sleep, so any device that recommends I sleep longer is something my sleep-enthusiast wife supports.

Your fitness data is ripe for the picking in the $3.5 trillion U.S. health care market.

Keeping track of this data has led to a competition among my friends to see who can get the most rest on a given night.

Joe still leads the pack with 11 hours and 15 minutes of sleep last weekend. I managed to get eight and a half hours of sleep one night last week, which might be my adult record.

After a few weeks wearing the band, I felt like I was getting a better understanding of my body.

On days when the app said I was well rested, I pushed my runs a little harder.

On days when the app told me I need a rest day, I took it.

And on nights when it advised I needed more sleep, I would get to bed early.

Old Businesses Meet New Tech

The biggest companies in the world know how to collect user data, analyze it and use it to boost their bottom line.

Facebook and Google are data companies with user-friendly products.

Amazon is a data company that sells products online.

Even Apple, as service revenue has increased 19% year over year, is focusing more on data.

In the next decade, the most disruptive trends in tech will converge. And the most successful companies will be the ones that pair Big Data with artificial intelligence and blockchain to better understand their markets, assess risk and crush the competition.

There is no bigger market ripe for disruption than the $3.5 trillion U.S. health care market, which accounted for 17.8% of the gross domestic product in 2018.

And we’re already starting to see the impact of new technology.

Fitness Data for Sale

In 2018, almost 6 million workers worldwide wore wearable fitness trackers as part of workplace wellness programs. According to ABI Research, that’s triple the 2 million participants in 2016.

Depending on the company, these voluntary programs offer workers free or discounted wearable trackers and annual financial incentives that range from $100 to more than $2,000.

For instance, UnitedHealthcare offers employer-sponsored plans that promote walking goals with an easy-to-remember acronym: FIT (for frequency, intensity and tenacity).

It pays $1,000 a year toward health care spending for active people who are able to walk with moderate intensity and log 10,000 steps each day.

The program is a win-win. Healthy workers should cost the insurer less and can be more productive at the office.

Of course, there is a downside to the collection of vital health information.

Insurers will know more about you than you might want to tell them. And if Congress ever repeals the Affordable Care Act, insurers could deny coverage based on a medical condition that your fitness tracker detects.

Health Care on the Blockchain

This is where the blockchain becomes a vital piece of storing health and fitness records.

With a blockchain, there’s no centralized location where the data is held. You can think of it as a decentralized ledger where your info can be stored, but it can only be accessed with a unique private key.

This would allow people to control ownership of their individual medical and fitness history. You won’t have to rely on the doctor’s office or hospital to keep track of your records. It also permits you to choose who you want to share that information with.

One of the main issues with health care data is that each doctor or hospital has to maintain a local copy, and health care privacy laws make it difficult to share or coordinate that information between care centers.

Using the blockchain to store health care data changes that. They allow for one source of truth for your medical records and other relevant health care data.

And distribution across multiple ledgers means access can be granted to additional health care professionals as needed.

Since the blockchain is a shared database, any changes to health records in one ledger changes all of them. This permits more collaboration and cooperation between doctors and improves health care results.

If there’s one thing that will help me sleep better at night, it’s knowing that my personal data will be safely stored on a decentralized blockchain.

Kind regards,

Ian King

Editor, Crypto Profit Trader