ArticleEngineering structures2022
Probabilistic Force Estimation and Event Localization (PFEEL) algorithm.
Article in Engineering structures, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Multimodal gait dataset with floor accelerations, inertial sensor data, and synchronized video from controlled walking trials.Data in brief · 2026Article
- Probabilistic Estimation of Cadence and Walking Speed From Floor Vibrations.IEEE journal of translational engineering in health and medicine · 2024Article
- A Multi-Sensor Stochastic Energy-Based Vibro-Localization Technique with Byzantine Sensor Elimination.Sensors (Basel, Switzerland) · 2023Article
- Probabilistic detection of impacts using the PFEEL algorithm with a Gaussian Process Regression Model.Engineering structures · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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.
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Registered trials
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