Document Type
Article
Abstract
Localization of human activity using floor vibrations has gained attention in recent years. In human health technologies, floor vibrations have been recently used to estimate gait parameters to predict a patients’ health status. Various methodologies such as using the characteristics of wave traveling (algorithms based on time of arrival) or the properties of structures (Force Estimation and Event Localization, FEEL, algorithm) have been investigated to localize the impact, fall, or step events. This paper presents a probabilistic approach that builds upon the FEEL algorithm to offer the advantage of eliminating the need for a robust experimental setup. The proposed Probabilistic Force Estimation and Event Localization (PFEEL) algorithm provides a probabilistic measure to an event’s force estimation and localization using random variables associated with the floor’s dynamics. The algorithm can also guide calibration by identifying calibration points that provide the maximum information. This reduces the number of calibration points needed, which has practical benefits during the implementation. In this manuscript, we presented the design, development, and validation of the algorithm.
Digital Object Identifier (DOI)
Publication Info
Published in Engineering Structures, Volume 252, 2022.
Rights
© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
APA Citation
Yohanna MejiaCruz, Jiang, Z., Caicedo, J. M., & Franco, J. M. (2022). Probabilistic Force Estimation and Event Localization (PFEEL) algorithm. Engineering Structures, 252, 113535–113535. https://doi.org/10.1016/j.engstruct.2021.113535