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Parkinson’s Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis

Introduction: Gait features differ between Parkinson’s disease (PD) and healthy subjects (HS). Kinematic alterations of gait include reduced gait speed, swing time, and stride length between PD patients and HS. Stride time and swing time variability are increased in PD patients with respect to HS. A...

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Autores principales: di Biase, Lazzaro, Raiano, Luigi, Caminiti, Maria Letizia, Pecoraro, Pasquale Maria, Di Lazzaro, Vincenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9693970/
https://www.ncbi.nlm.nih.gov/pubmed/36433372
http://dx.doi.org/10.3390/s22228773
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author di Biase, Lazzaro
Raiano, Luigi
Caminiti, Maria Letizia
Pecoraro, Pasquale Maria
Di Lazzaro, Vincenzo
author_facet di Biase, Lazzaro
Raiano, Luigi
Caminiti, Maria Letizia
Pecoraro, Pasquale Maria
Di Lazzaro, Vincenzo
author_sort di Biase, Lazzaro
collection PubMed
description Introduction: Gait features differ between Parkinson’s disease (PD) and healthy subjects (HS). Kinematic alterations of gait include reduced gait speed, swing time, and stride length between PD patients and HS. Stride time and swing time variability are increased in PD patients with respect to HS. Additionally, dynamic parameters of asymmetry of gait are significantly different among the two groups. The aim of the present study is to evaluate which kind of gait analysis (dynamic or kinematic) is more informative to discriminate PD and HS gait features. Methods: In the present study, we analyzed gait dynamic and kinematic features of 108 PD patients and 88 HS from four cohorts of two datasets. Results: Kinematic features showed statistically significant differences among PD patients and HS for gait speed and time Up and Go test and for selected kinematic dispersion indices (standard deviation and interquartile range of swing, stance, and double support time). Dynamic features did not show any statistically significant difference between PD patients and HS. Discussion: Despite kinematics features like acceleration being directly proportional to dynamic features like ground reaction force, the results of this study showed the so-called force/rhythm dichotomy since kinematic features were more informative than dynamic ones.
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spelling pubmed-96939702022-11-26 Parkinson’s Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis di Biase, Lazzaro Raiano, Luigi Caminiti, Maria Letizia Pecoraro, Pasquale Maria Di Lazzaro, Vincenzo Sensors (Basel) Article Introduction: Gait features differ between Parkinson’s disease (PD) and healthy subjects (HS). Kinematic alterations of gait include reduced gait speed, swing time, and stride length between PD patients and HS. Stride time and swing time variability are increased in PD patients with respect to HS. Additionally, dynamic parameters of asymmetry of gait are significantly different among the two groups. The aim of the present study is to evaluate which kind of gait analysis (dynamic or kinematic) is more informative to discriminate PD and HS gait features. Methods: In the present study, we analyzed gait dynamic and kinematic features of 108 PD patients and 88 HS from four cohorts of two datasets. Results: Kinematic features showed statistically significant differences among PD patients and HS for gait speed and time Up and Go test and for selected kinematic dispersion indices (standard deviation and interquartile range of swing, stance, and double support time). Dynamic features did not show any statistically significant difference between PD patients and HS. Discussion: Despite kinematics features like acceleration being directly proportional to dynamic features like ground reaction force, the results of this study showed the so-called force/rhythm dichotomy since kinematic features were more informative than dynamic ones. MDPI 2022-11-13 /pmc/articles/PMC9693970/ /pubmed/36433372 http://dx.doi.org/10.3390/s22228773 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
di Biase, Lazzaro
Raiano, Luigi
Caminiti, Maria Letizia
Pecoraro, Pasquale Maria
Di Lazzaro, Vincenzo
Parkinson’s Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis
title Parkinson’s Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis
title_full Parkinson’s Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis
title_fullStr Parkinson’s Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis
title_full_unstemmed Parkinson’s Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis
title_short Parkinson’s Disease Wearable Gait Analysis: Kinematic and Dynamic Markers for Diagnosis
title_sort parkinson’s disease wearable gait analysis: kinematic and dynamic markers for diagnosis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9693970/
https://www.ncbi.nlm.nih.gov/pubmed/36433372
http://dx.doi.org/10.3390/s22228773
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