The importance of accurate distance and pace metrics
At some point in almost every seasoned runner’s journey, they decide to upgrade to a GPS watch. And with that purchase comes an expectation that this new ‘gadget’ will provide accurate data about their training. Having dropped the cash, understandably, they place a great deal of faith in the values being shown during the run and the accuracy of the data recorded during. After all, the whole point of buying a GPS watch is to get a better measure of how you have run.
Let us start by looking at the two sides of the argument: accuracy of the wearable device versus the magnitude of improvement. Runners who own a GPS watch typically care about three notable metrics: the distance they cover, the pace they have been running, and the split time. In most situations they can be confident in the timing information being provided by a device. However, pace/speed metrics rely on devices measuring distance accurately and then using a formula [speed = distance/time, or pace = time/distance) to determine these values. And this is where the accuracy of the data begins to break down.
It’s important to remember that a runner who has been running for a decent period of time may be making only modest improvements in performance. However, perhaps more than the less experienced runner, they want these improvements to be tracked accurately and to be able to identify trends in their data. And therein lies the problem. What if the error in their device is as big (or bigger) as the performance changes they are actually making?
What level of accuracy do runners actually need?
Sport scientists have concluded that a meaningful change in endurance running performance for everyday athletes is around 1.5% and for elite athletes it could be at as little as 0.5%. On the other side of the equation, a typical error for even a high-end GPS watch is about 2-3% in distance terms. This equates to around 20-30 metres of error in every km.
Where this starts to get really interesting is when we look at what this actually means for the runner. An athlete who is running at 04:00 min/km will be getting told by their watch that they are running at 04:07 min/km (assuming a distance underestimate). Any seasoned runner will know (and feel) the difference between 04:00 and 04:07 min/km pace. However, by relying on the watch as the benchmark for pace, rather than perceived effort, they increase the chance of working too hard too early and blowing up before the end of the run.
For longer-term analysis, if runners are viewing run data that has 3% or more of (possibly random) error then it is going to be difficult for them to use their data to see trends in their performance. In short, runners need better, more accurate, performance data from their wearable devices.
The limitations of current approaches
Most current running watches rely on GNSS (or GPS) satellite technology to repeatedly locate where a runner is on the earth’s surface at any instant of time and then use the distance between locations and the regular time intervals to reconstruct the runner’s speed/pace.
Even in ideal conditions, GNSS technology has limits to its accuracy which will negatively affect the validity of the data. These inaccuracies are compounded further by factors which disrupt the satellite signals. These include the number and location of available satellites, weather or atmospheric effects and interference from tall buildings and tree cover. If you own a GPS watch you will have, undoubtedly, experienced the effect of the built environment on your run - it’ll be that race or training run with spikes in distance and pace that are massively different to the actual effort.
Adding to the potential limitations of GNSS/GPS technology in challenging outdoor environments it is also essentially impossible to use GNSS tracking to monitor running performance indoors, either at indoor tracks or during treadmill sessions.
The application of inertial sensors
A small number of current devices have eschewed GPS technology for reconstructing distance and pace measures in favour of employing an inertial navigation (INS) approach. These devices benefit from accuracy improvements under most conditions but suffer if they fall back on phone-based GPS traces to show route coverage. Another benefit of an inertial sensors approach is that in theory there is nothing to prevent the INS devices being employed for indoor and treadmill running.
The NURVV solutionThe best current solution for providing runners the accurate performance data they need is a careful fusion of top-line GPS data with an advanced inertial navigation system using complementary on board sensors.
It is important that the technical specification of the sensors collecting the raw data is cutting-edge too – running is a very dynamic activity and the GPS data needs to be collected at a high enough rate to follow the quick changes of direction a runner makes. Also, the inertial sensors need to have high enough sampling rates and dynamic ranges to robustly capture the rapidly changing waveforms and magnitude of impacts that occur during running steps.
During its development NURVV Run has taken all these factors into consideration and arrived at a technical solution which provides market-leading accuracy for running performance data with distance/pace errors of less than 1%. This has been confirmed by internal and external testing.
NURVV Run represents the best choice for the runner who wants to be super-confident in the numbers their device is giving back to them, and who is seeking to monitor those coveted marginal gains that accumulate and lead to meaningful improvements in performance.