Literature DB >> 26679417

Loss of fractal gait harmony in Parkinson's Disease.

Marco Iosa1, Giovanni Morone2, Augusto Fusco2, Fabio Marchetti2, Carlo Caltagirone3, Stefano Paolucci2, Antonella Peppe2.   

Abstract

OBJECTIVE: Recently, an intrinsic fractal harmonic structure was found underlying the rhythm of physiological walking, but it has not yet been investigated in subjects with a neurological disease. The aim of this study was to determine if and how this harmonic structure is altered in patients with Parkinson's Disease.
METHODS: Gait analysis of 70 patients with Parkinson's Disease in pharmacological phase on was performed, the findings of which we compared with reference data of age-matched healthy subjects. Fifteen patients were retested after a washout period of 12 h.
RESULTS: Alterations in all spatio-temporal gait parameters and gait indices with regard to symmetry, coordination, and harmony were noted, but after correction for multicollinearity bias, only the latter correlated significantly with Unified Parkinson's Disease Rating Scale motor score (p=0.001). The fractal gait structure underwent even more extensive alterations in pharmacological off phase (p<0.05).
CONCLUSIONS: The intrinsic gait harmony was altered in patients with Parkinson's Disease and significantly correlated to motor severity. It could be partially recovered by assumption of L-dopa. SIGNIFICANCE: Loss of harmony is a quantitatively assessable gait benchmark in Parkinson's Disease. It seems to be dependent on dopaminergic but also on non-dopaminergic networks.
Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Gait analysis; Locomotion; Neurorehabilitation; Parkinson’s Disease; Walking

Mesh:

Year:  2015        PMID: 26679417     DOI: 10.1016/j.clinph.2015.11.016

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  11 in total

1.  Effect of different music genres on gait patterns in Parkinson's disease.

Authors:  D De Bartolo; G Morone; G Giordani; G Antonucci; V Russo; A Fusco; F Marinozzi; F Bini; G F Spitoni; S Paolucci; M Iosa
Journal:  Neurol Sci       Date:  2019-11-12       Impact factor: 3.307

2.  The Role of Walking Experience in the Emergence of Gait Harmony in Typically Developing Toddlers.

Authors:  Daniela De Bartolo; Coen S Zandvoort; Marije Goudriaan; Jennifer N Kerkman; Marco Iosa; Nadia Dominici
Journal:  Brain Sci       Date:  2022-01-24

3.  Stability and Harmony of Gait in Patients with Subacute Stroke.

Authors:  Marco Iosa; Fabiano Bini; Franco Marinozzi; Augusto Fusco; Giovanni Morone; Giacomo Koch; Alex Martino Cinnera; Sonia Bonnì; Stefano Paolucci
Journal:  J Med Biol Eng       Date:  2016-10-07       Impact factor: 1.553

4.  Golden Gait: An Optimization Theory Perspective on Human and Humanoid Walking.

Authors:  Marco Iosa; Giovanni Morone; Stefano Paolucci
Journal:  Front Neurorobot       Date:  2017-12-19       Impact factor: 2.650

5.  Brain lesions affecting gait recovery in stroke patients.

Authors:  Kyoung Bo Lee; Joon Sung Kim; Bo Young Hong; Bomi Sul; Seojin Song; Won Jin Sung; Byong Yong Hwang; Seong Hoon Lim
Journal:  Brain Behav       Date:  2017-10-25       Impact factor: 2.708

6.  Testing the Performance of an Innovative Markerless Technique for Quantitative and Qualitative Gait Analysis.

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Journal:  Sensors (Basel)       Date:  2020-11-20       Impact factor: 3.576

7.  Auditory Cue Based on the Golden Ratio Can Improve Gait Patterns in People with Parkinson's Disease.

Authors:  Valeria Belluscio; Marco Iosa; Giuseppe Vannozzi; Stefano Paravati; Antonella Peppe
Journal:  Sensors (Basel)       Date:  2021-01-29       Impact factor: 3.576

8.  A synthetic kinematic index of trunk displacement conveying the overall motor condition in Parkinson's disease.

Authors:  Emahnuel Troisi Lopez; Roberta Minino; Pierpaolo Sorrentino; Rosaria Rucco; Anna Carotenuto; Valeria Agosti; Domenico Tafuri; Valentino Manzo; Marianna Liparoti; Giuseppe Sorrentino
Journal:  Sci Rep       Date:  2021-02-02       Impact factor: 4.379

9.  Artificial Neural Network Detects Hip Muscle Forces as Determinant for Harmonic Walking in People after Stroke.

Authors:  Marco Iosa; Maria Grazia Benedetti; Gabriella Antonucci; Stefano Paolucci; Giovanni Morone
Journal:  Sensors (Basel)       Date:  2022-02-11       Impact factor: 3.576

10.  Artificial Neural Network Analyzing Wearable Device Gait Data for Identifying Patients With Stroke Unable to Return to Work.

Authors:  Marco Iosa; Edda Capodaglio; Silvia Pelà; Benedetta Persechino; Giovanni Morone; Gabriella Antonucci; Stefano Paolucci; Monica Panigazzi
Journal:  Front Neurol       Date:  2021-05-19       Impact factor: 4.003

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