SABEL Labs

Lab based technologies (ambulatory or xed) have a signi cantly higher cost, both the capital required to purchase and the more hidden cost, that of having a user suitably experienced to use it. Thus they are suited to high accuracy studies of not too many participants. Commercial wearables on the other hand are at least an order of magnitude cheaper to purchase and can be used widely. They represent an opportunity to do larger scale studies of more participants and don’t require a sophisticated operator. These products, driven by the desire for social engagement (consumers like this interaction and are more likely to continue to use and purchase in the future) over data aggregation opportunities across whole communities. Therefore commercially popular devices can possibly be an option for researchers to consider using.

Research quality monitoring platforms, typically use high rate sensors, today in the order of 1000 Hz. In addition they may also have other sensors, modularity and to accommodate for long periods of operation large capacity batteries. All data is collected and stored in raw form with the minimum of ltering, to allow for the most robust of analysis later on8. Fitbits and other commercial wearables need to make substantial compromises to achieve their small form factor and lower cost, so available computational power, sensor sets and batteries all must be substantially smaller. These compromises necessitate much lower sample rates, typically around 10Hz, or interrupt driven footfall events. Raw data is stored in aggregate form, usually in epochs that provide enough accuracy for a user and reduce the required amount to be stored, for example a 1 minute epoch of 10 Hz data is a 600 times reduction in data, but the trade off is resolution and accuracy.

As these consumer products continue to create a market appetite for such technologies, so too the market eventually becomes more sophisticated and the appetite for greater accuracy grows. Coupled with

technology trends we will increasingly see products like the Fitbit grow ever closer to their research quality cousins. Consider this, rather than doing studies of n=20 for statistical signi cant that n=2M is well within the realms of possibility…how exciting.

For now though they each have a role and a place. Understanding both of these in conjunction with either accepting an accuracy compromise, or that accuracy is paramount, for a sports scientist. Therefore, the sports scientist has to not only understand his or her objective, but needs to have considerable knowledge in the technology to be able to make an informed choice. In comparing apples with oranges it is perhaps helpful to see them as a fruit salad for the consumption of the discerning fitness professional.