Health sensors are here, but where are the insights?

Health sensor technology has advanced by leaps and bounds in the past half-decade, finding ways to give us accurate information about everything from our heart rate to our stress levels. But the real challenge is translating this data into useful insights.

Over the past few years, I’ve tried out a bunch health sensors and their associated software, each of which offers impressive data but struggles to provide meaningful, integrated insights.

Here’s what I’ve been playing with:

• Levels: Uses a continuous glucose monitor (CGM) paired with an app to track glucose over time, helping adjust your diet for better metabolic health.

• Lumen: A breath analysis device measuring fat burn to support keto, or other custom diets.

• FullPower AI: Sleep sensors under your mattress, tracking REM, deep, light sleep stages.

• ShapeScale: A 3D body scanner that tracks changes in body shape, fat percentage, and volume over time.

• Apple Watch: Equipped with sensors for heart rate, blood oxygen saturation, and more.

• Garmin Fenix 7S Pro Sapphire: Offers detailed health tracking and GPS. When paired with a Garmin heart rate chest strap, great at ECG and heart rate tracking.

I’ve tried using Apple Health to centralize my health data. Despite the fact that it's easy to import everything to Apple Health, getting anything useful back out from Apple's interface has been a challenge.

This challenge isn’t unique to Apple Health. Most of these products offer specific feedback loops—Levels for diet adjustments, Lumen for keto adherence, ShapeScale for workout tracking, and so forth. But the broader question remains: when you put all these sensors together, what new and useful things can we do with the data?

There’s a new app I’ve been playing with called Context by Fulcra. The app allows you to plug in a myriad of health data sources and construct your own dashboards from the data — but it’s a work in progress, and at the end of the day, I’m looking for more than charts.

The ultimate value of these sensors lies in driving behavior change — in other words, the part that comes before detection of disease. Minor habit adjustments, such as daily walks, can profoundly impact how much time you get to live in good health. Given the power of software to influence behavior through dopamine responses and other design tricks, the right integration of health data could motivate significant, impactful changes.

This isn’t a secret, and apps like Levels are already targeting behavior changes beyond their initial scope of meals through new features like “habit loops.” But these features are not sticky yet.

The sensors are here, and only getting better. But figuring out how to build software that delivers real insight is a difficult thing to do and is going to lag behind the hardware.