Body Mass Index in Human Gait for Building Risk Assessment Using Graph Theory

Sensors (Basel). 2020 May 20;20(10):2899. doi: 10.3390/s20102899.

Abstract

This article presents a comprehensive study of human physiology to determine the impact of body mass index (BMI) on human gait. The approach followed in this study consists of a mathematical model based on the centre of mass of the human body, the inertia of a person in motion and the human gait speed. Moreover, the study includes the representation of a building using graph theory and emulates the presence of a person inside the building when an emergency takes place. The optimal evacuation route is obtained using the breadth-first search (BFS) algorithm, and the evacuation time prediction is calculated using a Gaussian process model. Then, the risk of the building is quantified by using a non-sequential Monte Carlo simulation. The results open up a new horizon for developing a more realistic model for the assessment of civil safety.

Keywords: Monte Carlo simulation; body mass index; breadth-first search; evacuation routes; human gait.

MeSH terms

  • Algorithms*
  • Body Mass Index*
  • Environment Design
  • Female
  • Gait*
  • Humans
  • Male
  • Models, Theoretical
  • Monte Carlo Method
  • Risk Assessment*
  • Safety