A study on human gait dynamics: modeling and simulations on OpenSim platform

Abstract

The analysis of human gait dynamics allows an individual to obtain interesting biometric features through which gait disturbances can be observed from normal and abnormal gait patterns. The musculo-skeletal modeling of human movement helps to study the gait dynamics with expected simulations. It encourages the clinicians to identify the pathological gait for proper treatment. We have created a vision-based human locomotion laboratory to capture the healthy and non-healthy gait patterns. A low cost black uniform is taken to capture different person’s gait data. This dress is made up with a piece of multiple color ribbon to identify different locations of body joints. It provides an added advantage during separation of different joint locations through color-based segmentation method. The demographic information of each subject helps to understand their gait dynamics. It instigates us to build a musculo-skeletal gait model on OpenSim simulation framework. The Regression Analysis (RA) technique is applied on crouch and healthy gait feature to measure the generalization ability and to uncover the gait profiles which are estimated by different error metrics such as, Root Mean Square Error (RMSE), Standard Deviation of Error (SDE), and Mean Error (ME). A computational method based on Normalized Auto Correlation (NAC) is computed to measure the gait disturbances in training subjects. The performance analysis of regression model on motion captured data has been validated with subject specific musculo-skeletal gait model on OpenSim platform.