The real wearable revolution in healthcare

Introduction: Why all these heart icons on my phone?
It seems like Silicon Valley isn’t content with its push into the automotive industry, and now has healthcare in its sights. All of the tech titans seem to be developing platforms for collecting and aggregating personal health and fitness information, and Apple has even literally been running a sweatshop to gather data from energetic employees.

The reason for this focus on activity data is that wearable devices are very suited to collecting it. A key point is that the data can be gathered automatically. This means that users don’t need to spend time manually logging their activity, with the all of the drop off in both compliance and reliability that brings. The business goal is to correlate activity data with health outcomes, providing an evidence base from which to prompt the users of those wearable devices to change their behavior in positive ways. The potential benefits for health promotion are undeniable.

The problem: Not all steps are created equal
One of the most significant problems with Silicon Valley’s healthcare project is that the data being collected lacks context. The data shows that my heart rate rose after I passed the 1,000 steps mark. But was this because I started sprinting? Because I started climbing a hill? Because I was ill? Or maybe because I swung my daughter onto my back when she started to grizzle? Your wearable device doesn’t know. And because it doesn’t record this contextual metadata, drawing inferences from the data is dubious.

The solution: Think multidimensional
At Performance Lab we describe the current reports that wearable devices and apps provide as one-dimensional. That is, they basically report what they are measuring (heart rate, steps, altitude, distance travelled and so forth). A multidimensional report produces insights by considering multiple metrics simultaneously. For example, an “effort” metric (such as heart rate or power output) can be considered together with other metrics that shed light on what is actually going on. These include:

Only a multi-dimensional report can reveal what happened in meaningful terms, like “Your legs got fatigued because your effort on the hills was too high.”

The good news is that the same devices that are capturing non-contextualized data also have the potential to capture the extra dimensions that are required to make the former meaningful. Barometers are becoming standard on smart phones. Together with speed, stride length and stride rate we can use this altitude data to provide all kinds of context – and conveniently accelerometers and the algorithms that interpret them are now smart enough to compute precisely those metrics. Heart rate measurement is firmly established on wrist-based devices, which are now set to provide accurate 24/7 heart rate variability data.

Going to the next level: Real time coaching
The upshot of this coming revolution in activity measurement is that our wearable devices will record in meaningful terms what we did and how our bodies responded.

One benefit of this multidimensional approach is that the project of correlating activity with health outcomes will no longer be dubious. But rather than wait for data analysis to provide us with generic health promotion advice, we can receive real time coaching.

If our wearables can know what we are doing, they can also correct this behavior. We can determine, for a given individual, how his or her unique body works to maximize and improve outcome variables such as power output and fatigue or stress levels. So for instance we can discover the optimum stride rate and stride length for a previously sedentary person looking to lose weight through walking, balancing their need for calorie burn with management of their pain and motivation levels. We can help a time poor executive achieve better fitness in half the time. Or we can change a person’s work and activity schedule to manage blood pressure.

Now that is an exciting project.