Complexity of human walking: the attractor complexity index is sensitive to gait synchronization with visual and auditory cues

Terrier, Philippe (Haute Ecole Arc Santé, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale ; Clinique romande de réadaptation, Sion, Suisse ; Department of Thoracic and Endocrine Surgery, University of Geneva, Geneva, Switzerland)

Background. During steady walking, gait parameters fluctuate from one stride to another with complex fractal patterns and long-range statistical persistence. When a metronome is used to pace the gait (sensorimotor synchronization), long-range persistence is replaced by stochastic oscillations (anti-persistence). Fractal patterns present in gait fluctuations are most often analyzed using detrended fluctuation analysis (DFA). This method requires the use of a discrete times series, such as intervals between consecutive heel strikes, as an input. Recently, a new nonlinear method, the attractor complexity index (ACI), has been shown to respond to complexity changes like DFA, while being computed from continuous signals without preliminary discretization. Its use would facilitate complexity analysis from a larger variety of gait measures, such as body accelerations. The aim of this study was to further compare DFA and ACI in a treadmill experiment that induced complexity changes through sensorimotor synchronization.


Keywords:
Article Type:
scientifique
Faculty:
Santé
Branch:
Soins infirmiers
School:
HE-Arc Santé
Institute:
Recherche appliquée et développement de la HE-ARC Santé
Subject(s):
Santé
Date:
2019-08
Pagination:
18
Published in:
PeerJ
Numeration (vol. no.):
7
DOI:
ISSN:
2167-8359
Appears in Collection:



 Record created 2019-08-26, last modified 2019-09-05

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