Measuring Running from the Foot

Posted by Gary Robinson on

What is wrong with measuring running from the wrist anyway?

For almost 20 years runners have been able to get a real time indication of their run performance on their sports watch. This performance data has typically included information on distance, pace, and time, although many runners will also use splits during the run and average values at the end.

In recent times, these watches have becoming increasingly more sophisticated using algorithms and sensors to give further insight during and after the run. As technology has become more accessible, data has, in turn, become important and serious runners often will consider the output from their wearable to be “gospel.” The popular phrase “if it’s not on Strava it didn’t happen!” is case in point of how important performance data has become to the everyday athlete. 

To compound matters when considering the issue of accuracy, one should remember that performance data only shows the “what” of performance (the outcome); the data gives zero information on the “how” or the “why”. For instance, running technique, and how it changes, can play a huge part in the outcome of a workout or race, yet performance data from a GPS watch fails to provide any insight into this key metric. Therefore, runners are often left with an indication of their current performance level, but little direction in terms of how to go about improving it. 

The problem herein lies with the limited accuracy of running watches, particularly those based on GNSS (GPS) technology. This lesser-known issue is discussed and considered in another of our blog posts but concerns the issue that the performance gains of the individual can be, in fact, cancelled out by inaccurate data recorded by the GPS watch.

As mentioned above, several watches have begun to provide the runner with estimations of some relevant technique/form metrics, such as cadence – the number of steps taken per minute. However, its important to remember that cadence is actually a step-based metric – it is a measure of how many times per minute the feet are in contact with the ground; not how many times per minute our arm swings.

While estimating cadence from a wrist-based device may produce a reasonable ball-park value, it will never be a direct measure and thus will be prone to inaccuracy. There are other running metrics that would be of interest to runners but require direct measurement of foot motion to produce values that can be useful. Here we are considering metrics like step length, footstrike, and pronation. It matters what the legs and feet are doing, not what the wrist is doing. Therefore, if we want to give runners accurate information about these aspects of their technique, we need to be measuring from the point of action, the feet.

Precision data: the evolution of NURVV Run Insoles & Coaching App

With NURVV Run we knew we wanted to satisfy a runner’s need for data on both performance and technique. We wanted measurement to be robust to all sorts of real-life environments. We wanted our system to be as unobtrusive as possible - knowing that athletes loathe to carry additional equipment. All of these considerations led us to our chosen technology platform.

To generate real information on foot-based metrics during running - such as footstrike and pronation metrics - we require an array of sensors distributed over the entire foot. This enables us to capture the loading response during each foot-ground contact. This is the guiding principle behind our smart insoles, with each insole containing 16 high-precision sensors and each sensor collecting 1000 readings every second.

The sensors within the insoles have been specially constructed and rigorously tested to ensure they provide an accurate linear response over the range of forces we know they will be exposed them to. What’s more, our sensor platform allows us to record the raw data from which we can apply signal processing techniques and accurately calculate cadence, step length, pronation, and footstrike.

Connecting trackers to our insoles allows us to store our step-based metrics at high data rates and provide power to the insoles for multiple hours of use. The trackers also contain an additional cache of sensors that allow us to monitor running performance outcomes in all environments applying a unique combination of advanced satellite and inertial navigation positioning technologies. These trackers also have all the communication protocols on board to allow the transfer of data to connected devices such as phones and smartwatches to provide that all-important in-run and post-run visual feedback to runners.

Overall, high-fidelity data being recorded from strategically positioned sensors at high data rates allows NURVV Run to calculate running based metrics with confidence. We combine the most relevant data streams and with careful on-board conditioning of the raw data signals we convert the raw data into biomechanical metrics to give the runner the information they want.

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