A Preliminary Study on Gait and Motion Analysis for Rehabilitation Applications

Abstract

Human gait analysis is an extensively studied research area since it provides important information for various health related and rehabilitation applications. Application of gait analysis ranges from diagnosis, monitoring, sports activities and early detection of potential hazards such as human fall. There are various types of approaches used in gait analysis including wearable, ambient and vision based devices. Among them wearable based devices is an inexpensive approach, though it requires additional resources and time for setup each time a gait analysis is required. A non-invasive approach could save lot of nursing and additional resources and indeed give more accurate useful information for gait analysis such as using Microsoft Kinect sensor since it can give depth and normal color images as well. This paper presents a preliminary study on gait analysis which can be applied to various rehabilitation application. The measurements taken includes step width, step lengths, stride lengths, arm spread, trunk sway and angles of knee with respective to hip and ankle while walking. The preliminary results showed that the approach could compute the same parameters as that of the wearable based devices with low error rates.