A Gait Analysis Device to Classify Normal vs. Abnormal Gaits in Flat Feet Patients

Abstract

Walking with flat feet can negatively affect a person’s back and lower extremities. Rehabilitation is the most common treatment, but ways to monitor progress outside of physical therapy sessions are needed. The end goal of this project is to develop a device that can monitor gait progress outside of the therapist’s office. A gait analysis device will be used to record the pressure exerted by the subject on four different parts of the soles of their feet as they walk. The idea is that if we obtain data of normal gaits and abnormal gaits, caused by flat feet, we can use the data to train an algorithm to classify each gait cycle as normal or abnormal. Work on this project focused on improving and troubleshooting an inner sole design that comprises pressure sensors that can provide gait information, and designing experiments to acquire gait data. We simplified the breadboard layout and strengthened and replaced flimsy connections. For visibility testing of the device, we picked two common types of abnormal gaits (hemeplegic and antalgic) for our test subjects to simulate after briefing them on the mechanics of the given gait. While collecting data, we had some technical difficulties with the shoe device. Once we can get the device to work correctly, we can collect and analyze more data and use it to train a classification algorithm.