Artificial Intelligence and Knowledge Processing: Methods and Applications

Analysis of Human Gait by Selecting Anthropometric Data Based on Machine Learning Regression Approach

Author(s): Nitesh Singh Malan* and Mukul Kumar Gupta * .

Pp: 209-219 (11)

DOI: 10.2174/9789815165739123010017

* (Excluding Mailing and Handling)

Abstract

This paper aims to elucidate a method to simulate human gait, which can help design a fully functional exoskeleton to rehabilitate the human lower limb. We present a method to calculate the forces and moments of each lower limb joint using human anthropometric parameters and free body diagrams. Various forces and moment of forces of lower limb joints have been calculated. The anthropometric data is evaluated using the linear regression approach. Also, in this work, we have simulated the normal human walking pattern. The forces and moments acting on lower limb joints are calculated in horizontal and vertical directions, and the human gait was simulated for a speed of 1.8m/s. The estimated results can be used as input parameters for the development of an exoskeleton for the rehabilitation of the human lower limb.

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