Gait processing and performance using angular velocity and leaping angle parameters

Abstract

Gait analysis is a process of learning the motion of human and animal by wearable sensor approach or/and vision approach. This analysis mainly used in medical and sports field where the study of body parts is crucial. 3-space sensor consists of accelerometer, gyroscope and compass sensors, built in one device. In this project, 3-space sensor was used to collect the data of walking and jogging motion, from test subjects performing those activities on a treadmill. Two components of motion, the angular velocity of the test subjects’ arm and the angle of leaping motion were selected and investigated. The data were then analyzed and processed using MATLAB using Principal of Component Analysis (PCA). PCA was used in gait analysis due to its ability to combine and reduce the number of variables of the obtained data. This method able to ease the flow of analysis since the variables had been reduced. The function called “Quiver” was used in order to generate the vector for each point plotted in the graph for both motions. Lastly, the accuracy of the analyzing process (70 % for walking and 100 % for jogging motions) will be used to create a system that can recognize the motion on any given data.