Sammendrag
In later years wearable sensors have been used to determine if they can detect small nuances within walking mobility in people with neurological diseases, such as Multiple Sclerosis (MS). The Six Spot Step Test (SSST) is a clinical performance test used to assess gait speed, balance, and coordination. Within the test, the participant walks and kicks.\\ I used data from wearable sensors to investigate the data from patients with MS doing the SSST. I started with raw sensor data from a collection of many different tests and wanted to detect the SSST and the different kicks within the SSST. Finding the tests was easy, but identifying all kicks for all patients and controls turned out to be challenging. As a solution, I ended up using the raw data from the sensors with a video of the test being performed to find different time stamps within the tests to analyze. \\ I analyzed the time segments from the SSSTs for patients and controls to determine whether the time segments can be used to differentiate patients from healthy controls. I also wanted to see if one could detect progression after a rehabilitation stay and see if there is a learning effect from walking through the test one time. What I found is that there is a difference in the time used between the healthy controls and the patients with MS, but that this difference is small. I also found that one can see an improvement in the times used on the tests after a rehabilitation stay, but what this comes from, I could not say. Finally, I found that there is some learning effect from walking through the test one time.