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Open AccessArticle

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

1
Escuela Superior Politécnica del Litoral, Campus Gustavo Galindo Km 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil EC090112, Ecuador
2
Departamento de Ingeniería de Sistemas Telemáticos, ETSI Telecomunicación, Universidad Politécnica de Madrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(10), 2899; https://doi.org/10.3390/s20102899
Received: 3 April 2020 / Revised: 27 April 2020 / Accepted: 1 May 2020 / Published: 20 May 2020
(This article belongs to the Special Issue Sensors for Gait, Posture and Health Monitoring)
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. View Full-Text
Keywords: body mass index; breadth-first search; evacuation routes; human gait; Monte Carlo simulation body mass index; breadth-first search; evacuation routes; human gait; Monte Carlo simulation
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Velásquez, W.; Alvarez-Alvarado, M.S.; Munoz-Arcentales, A.; López-Pernas, S.; Salvachúa, J. Body Mass Index in Human Gait for Building Risk Assessment Using Graph Theory. Sensors 2020, 20, 2899.

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