Wavelet-frequency analysis for the detection of discontinuities in switched system models of human balance

Nema, S, Kowalczyk, P and Loram, I (2017) Wavelet-frequency analysis for the detection of discontinuities in switched system models of human balance. Human Movement Science, 51. pp. 27-40. ISSN 0167-9457

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Official URL: http://www.elsevier.com/locate/issn/01679457

Abstract

This paper is concerned with detecting the presence of switching behavior in experimentally obtained posturographic data sets by means of a novel algorithm that is based on a combination of wavelet analysis and Hilbert transform. As a test-bed for the algorithm, we first use a switched model of human balance control during quiet standing with known switching behavior in four distinct configurations. We obtain a time-frequency representation of a signal generated by our model system. We are then able to detect manifestations of discontinuities (switchings) in the signal as spiking behavior. The frequency of switchings, measured by means of our algorithm and detected in our models systems, agrees with the frequency of spiking behavior found in the experimentally obtained posturographic data.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	17 Feb 2017 15:55
Publisher:	Elsevier
Additional Information:	This is an Author Accepted Manuscript of a paper accepted for publication in Human Movement Science, published by and copyright Elsevier.
Divisions:	Faculties > Science and Engineering
Subject terms:	Discontinuities, Instantaneous frequency, Normalized Hilbert transform, Switched systems, Wavelets, 09 Engineering, 11 Medical And Health Sciences, 17 Psychology And Cognitive Sciences, Experimental Psychology
URI:	https://e-space.mmu.ac.uk/id/eprint/617806
DOI:	https://doi.org/10.1016/j.humov.2016.08.002
ISSN	0167-9457

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