Case Study: Halterix
What If Your Smartwatch Could Help Improve Your Approach To Physical Therapy?
While conducting his PhD research, Halterix founder Dr. David Burns discovered a breakthrough in motion recognition technology that recognized and evaluated human motion using the signals collected from sensors in a smartwatch.
As an orthopedic surgeon, Dr. Burns realized so many surgeries were being done that could have been avoided with more effective physical therapy (PT). But what do healthcare providers know about how much PT people actually do on their own – or how properly they do it?
Up until now, gaining these types of measurements typically required at least three wearable sensors. But by using a powerful AI engine and data capture technology, we helped Halterix begin development of a first-of-its-kind app that measures, evaluates, and shares real-time performance using just a smartwatch.
Flexing our research muscles
Excited by the idea of designing a motion data smartwatch solution, we visited various PT sites to observe how people actually function, ask them questions, and make sense of how this app could work best for them. We realized we’d have to address the following key items in order to fully engage users in their physical therapy journey and help them
Discover the problems being solved
Before getting started, we wanted to make sure that we identified actual problems while understanding how they stood in the way of the users.
Determine the most appropriate and effective approach for the end user
With an understanding of the problems to solve and why, we explored and tested multiple possible solutions to identify which ones had the greatest positive affect for our users.
Build an integrated technology solution
Build an integrated technology solution connecting a smartwatch app, a patient app, a practitioner app and a server with the existing AI
What about data privacy?
At MindSea, we stay on top of data privacy and security guidelines. It’s a formal step of our internal design process. For this project, we thought, not so formally, “Would people be creeped out using this app?”
A smartwatch is telling you if you’re doing an exercise the right or wrong way and it’s sharing that data with a practitioner. Would that bother people that their potential poor performance was being seen by their doctor or physical therapist? So, we asked around. And research showed the answer was “No.” It’d be different if this data was shared with an insurance company, but they didn’t mind if it was being used for the benefit and progress of their own healing.
Presenting actionable data
The interesting challenge as we approached design was around complex functionality. How do we best present user scores and make the data actionable, so users stay engaged?
Original beta testing done by Halterix had revealed that there simply wasn’t enough information to be actionable. An overall score didn’t do much for users, but telling them if an exercise was good, not so good, or great and why, would.
So during our design phase, we explored creative ways to facilitate communication of the motion data being shared between a smartwatch, patient, and practitioner.
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