Case Study: Aero2Max

Aero2Max puts laboratory physiology into athletes’ hands with a machine learning based mobile app

The team at Aero2max was looking to bring their vision of fitness efficiency to life with a mobile application that incorporated their developed machine learning protocol. As physicians, they knew that monitoring the oxygen levels of athletes and fitness consumers would give more insight into workout efficiency than the standard of monitoring heart rate. Where oxygen and lung efficiency testing had previously been limited to a medical office, Aero2max was looking to bring it to the consumer wearable space.

When the Aero2max team met Promptworks at a local app development contest, they were eager to take advantage of Promptworks experience in healthcare, IoT, and machine learning to develop a working prototype with a mobile application. Their hope was to use this prototype as a proof of concept that could fuel both fundraising and the next stage of their startup.

Here was our challenge:

While the Aero2max team knew that the science behind their idea was correct, implementing their vision into a real-life product was a different matter. The mobile application prototype needed to incorporate a machine learning framework to distill O2 processing data into consumer-friendly information while also providing insight into exercise efficiency improvements. In addition, the interface needed to quickly and accurately provide complex medical information to non-medical users, often while they were on the go.

Here's how we solved it:

Building a Consumer First Application While Promptworks had the technical expertise to quickly turnaround a prototype, we also wanted to make sure that the product and application were user-friendly. This necessitated a deep dive into the medical nomenclature and terminology that was foundational for the Aero2max team but would be inaccessible to consumers.

Promptworks developers and designers participated in a focused learning session with medical professionals to better understand the science behind the product and incorporate important health updates in layman's terms. This internal discovery helped make the final application more intuitive for non-medical users and lowered the point of entry.

Incorporating Machine Learning Analytics Additionally, the Promptworks team needed to stream data via Bluetooth from the wearable device through a machine learning trained model in real time. Aero2max, in partnership with the University of Pennsylvania developed this model that would accurately predict O2 consumption and ventilation metrics.

Knowing that lag could ruin an athlete’s workout, Promptworks built the final application using Swift, optimizing for a real-time performance.

See the results:

Promptworks was able to deliver a working prototype to the Aero2max team in a matter of months. This mobile application was fully functional from both a scientific standpoint and a consumer product standpoint, making it the perfect proof of concept package that Aero2max needed to continue fundraising against their vision.

Interested in more examples of our work?

See how we helped IQVIA deliver targeted recruitment data with intelligent automation or how Drexel investigated new treatment protocols with a mobile app and integrated algorithm.

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