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Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson’s Disease

In patients with Parkinson’s disease (PD), arm swing changes are common, even in the early stages, and these changes are usually evaluated subjectively by an expert. In this article, hypothesize that arm swing changes can be detected using a low-cost, cloud-based, wearable, sensor system that incorp...

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Autores principales: Rincón, Domiciano, Valderrama, Jaime, González, Maria Camila, Muñoz, Beatriz, Orozco, Jorge, Montilla, Linda, Castaño, Yor, Navarro, Andrés
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436032/
https://www.ncbi.nlm.nih.gov/pubmed/32759667
http://dx.doi.org/10.3390/s20154339
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author Rincón, Domiciano
Valderrama, Jaime
González, Maria Camila
Muñoz, Beatriz
Orozco, Jorge
Montilla, Linda
Castaño, Yor
Navarro, Andrés
author_facet Rincón, Domiciano
Valderrama, Jaime
González, Maria Camila
Muñoz, Beatriz
Orozco, Jorge
Montilla, Linda
Castaño, Yor
Navarro, Andrés
author_sort Rincón, Domiciano
collection PubMed
description In patients with Parkinson’s disease (PD), arm swing changes are common, even in the early stages, and these changes are usually evaluated subjectively by an expert. In this article, hypothesize that arm swing changes can be detected using a low-cost, cloud-based, wearable, sensor system that incorporates triaxial accelerometers. The aim of this work is to develop a low-cost, assistive diagnostic tool for use in quantifying the arm swing kinematics of patients with PD. Ten patients with PD and 11 age-matched, healthy subjects are included in the study. Four feature extraction techniques were applied: (i) Asymmetry estimation based on root mean square (RMS) differences between arm movements; (ii) posterior–anterior phase and cycle regularity through autocorrelation; (iii) tremor energy, established using Fourier transform analysis; and (iv) signal complexity through the fractal dimension by wavelet analysis. The PD group showed significant (p < 0.05) reductions in arm swing RMS values, higher arm swing asymmetry, higher anterior–posterior phase regularities, greater “high energy frequency” signals, and higher complexity in their XZ plane signals. Therefore, the novel, portable system provides a reliable means to support clinical practice in PD assessment.
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spelling pubmed-74360322020-08-24 Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson’s Disease Rincón, Domiciano Valderrama, Jaime González, Maria Camila Muñoz, Beatriz Orozco, Jorge Montilla, Linda Castaño, Yor Navarro, Andrés Sensors (Basel) Article In patients with Parkinson’s disease (PD), arm swing changes are common, even in the early stages, and these changes are usually evaluated subjectively by an expert. In this article, hypothesize that arm swing changes can be detected using a low-cost, cloud-based, wearable, sensor system that incorporates triaxial accelerometers. The aim of this work is to develop a low-cost, assistive diagnostic tool for use in quantifying the arm swing kinematics of patients with PD. Ten patients with PD and 11 age-matched, healthy subjects are included in the study. Four feature extraction techniques were applied: (i) Asymmetry estimation based on root mean square (RMS) differences between arm movements; (ii) posterior–anterior phase and cycle regularity through autocorrelation; (iii) tremor energy, established using Fourier transform analysis; and (iv) signal complexity through the fractal dimension by wavelet analysis. The PD group showed significant (p < 0.05) reductions in arm swing RMS values, higher arm swing asymmetry, higher anterior–posterior phase regularities, greater “high energy frequency” signals, and higher complexity in their XZ plane signals. Therefore, the novel, portable system provides a reliable means to support clinical practice in PD assessment. MDPI 2020-08-04 /pmc/articles/PMC7436032/ /pubmed/32759667 http://dx.doi.org/10.3390/s20154339 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rincón, Domiciano
Valderrama, Jaime
González, Maria Camila
Muñoz, Beatriz
Orozco, Jorge
Montilla, Linda
Castaño, Yor
Navarro, Andrés
Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson’s Disease
title Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson’s Disease
title_full Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson’s Disease
title_fullStr Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson’s Disease
title_full_unstemmed Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson’s Disease
title_short Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson’s Disease
title_sort wristbands containing accelerometers for objective arm swing analysis in patients with parkinson’s disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436032/
https://www.ncbi.nlm.nih.gov/pubmed/32759667
http://dx.doi.org/10.3390/s20154339
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