Identifying pathological motion patterns
Description
Due to this multi-factorial nature of walking, a “walking classifier” is important for scientists, clinicians as well as industry partners alike in terms of identifying and understanding motor diseases, developing implants as well as designing rehabilitation programs.
This study brings the concept of “walking classifier” or a walking classification tool into place, by considering techniques such as Principal Components Regression, Support Vector Machines and Neural networks.
Goal
The goal is to develop classification tools based on walking patterns from both healthy as well as pathological or diseased cohorts of human subjects.