Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/141534
Title: Directional statistics approach based on instantaneous rotational parameters of tri-axial trajectories for footstep detection
Authors: Venkatraman, Divya
Khong, Andy Wai Hoong
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2017
Source: Venkatraman, D., & Khong, A. W. H. (2018). Directional statistics approach based on instantaneous rotational parameters of tri-axial trajectories for footstep detection. Circuits, Systems, and Signal Processing, 37(5), 1958-1987. doi:10.1007/s00034-017-0647-x
Journal: Circuits, Systems, and Signal Processing
Abstract: Polarization of tri-axial signals is defined using instantaneous rotational characteristics of the three-dimensional (3D) trajectory. We propose a rotational model to parameterize the time evolution of the 3D trajectory as a sequence of scaled rotations. Using this model, the velocity-to-rotation transform is defined to estimate the eigenangle, eigenaxis and orientation quaternion that quantify the instantaneous rotational parameters of the trajectory. These rotational parameters correspond to p-dimensional directional random vectors (DRVs). We propose two approaches to discriminate between the presence and absence of an elliptically polarized trajectory generated by human footsteps. In the first approach, we fit a von Mises–Fisher probability density function to the DRVs and estimate the concentration parameter. In the second approach, we employ the Kullback–Leibler divergence between the estimated nonparametric hyperspherical probability densities. The detection performance of the proposed metrics is shown to achieve an accuracy of 97 % compared to existing approaches of 82 % for footstep signals.
URI: https://hdl.handle.net/10356/141534
ISSN: 0278-081X
DOI: 10.1007/s00034-017-0647-x
Rights: © 2017 Springer Science+Business Media, LLC. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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