In my project, Flat Foot Fixer, I developed a mobile biofeedback system designed to help people correct flexible flat feet by analyzing their gait. The system uses mobile, wireless IMU (Inertial Measurement Unit) sensors that easily attach to any footwear to detect fine changes in gait movement due to arch collapse. The application is designed for Android and built using Kotlin language in Android Studio.

How It Works

Once the app is set up and connected to the sensors, it starts collecting gait data. Users have two options: one for collecting data with the arch collapsed and another with the arch activated. The data is then processed and stored on-board, making the system more robust against unstable Bluetooth connections.

The app uses machine learning to train a Naive Bayes classifier model, which is then used to analyze the user's gait in real-time. If the app detects that the user is walking with collapsed arches, it vibrates the phone and displays visual cues to alert the user to correct their posture.

The app also includes daily tracking of arch collapses and can display this data in graphical form, helping users to track their progress over time.

Overall, Flat Foot Fixer aims to leverage mobile computing and machine learning to provide an effective and convenient solution for correcting flexible flat feet, thereby improving long-term joint health.