As a team we’d decided that we wanted to do a health-related hack before we even arrived at PennApps, and when we saw the Sensoria Fitness smart sock, we got this idea to create a gait and posture analysis app based on the platform. Until now, most smart fitness devices only measured heart rate, blood pressure, and other things in the body. There has never been a consumer device which can measure the pressure on the bottom of your foot (gait). It is also novel because patients can send data abotu their gait/walking data to doctors and it can diagnose walking problems and train/rehabilitate walking problems all through a mobile app.
Posture and the way you walk is important. Very slight variations in walking posture times thousands of steps a day can mean extra stress on various part of your foot, leg, and even the rest of your body. Thus, our target user is anyone interested in analyzing their own walking behavior. Some people may be walking wrong their whole lives without even knowing it.
Our app, Footsies, is currently on the Android platform. Even though Sensoria has developed a suite of frameworks for the smart sock, there has not been any major framework for Android. Thus, the technical difficulty was difficult as we needed to store/interpret all of the data, and manually look at all of the accelerometer data/pressure data and calibrate the app so that we can accurately determine what is a step, and also manually make a visual map of the pressures on the feet in real time. It connects to the Sensoria smart sock via Bluetooth, and allows the user to get a variety of information from the device.
It calibrates to each users' step pressures through a short and easy process, allowing the app to get more a more meaningful measurement. The app has three main modes: diagnosis, monitor, and training. In diagnosis mode, the user is asked to take 10 normal steps, and based on those steps the app attempts to make a diagnosis based on the gait pressures measured. Even if no meaningful conclusion is reached, the app graphs the data to which may help to find correlations. In monitor mode, the user can watch the details of their every step. A "heat" map of pressure is shown, which can show if a user has a habit of leaning in- or out-wards, for example. In training mode, the user can decide on a number of steps as a goal, and the app will count them to that goal while alerting them of any bad posture steps they made along the way. Footsies even has Pebble integration; the smartwatch will alert you via vibrations if you make a bad step.
This app is also good for people who might not even know they have common foot problems to diagnose themselves.