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Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review

Assessing the progression of movement disorders such as Parkinson's Disease (PD) is key in adjusting therapeutic interventions. However, current methods are still based on subjective factors such as visual observation, resulting in significant inter-rater variability on clinical scales such as...

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Detalles Bibliográficos
Autores principales: Garcia-Agundez, Augusto, Eickhoff, Carsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8572888/
https://www.ncbi.nlm.nih.gov/pubmed/34759810
http://dx.doi.org/10.3389/fnagi.2021.716102
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author Garcia-Agundez, Augusto
Eickhoff, Carsten
author_facet Garcia-Agundez, Augusto
Eickhoff, Carsten
author_sort Garcia-Agundez, Augusto
collection PubMed
description Assessing the progression of movement disorders such as Parkinson's Disease (PD) is key in adjusting therapeutic interventions. However, current methods are still based on subjective factors such as visual observation, resulting in significant inter-rater variability on clinical scales such as UPDRS. Recent studies show the potential of sensor-based methods to address this limitation. The goal of this systematic review is to provide an up-to-date analysis of contactless sensor-based methods to estimate hand dexterity UPDRS scores in PD patients. Two hundred and twenty-four abstracts were screened and nine articles selected for analysis. Evidence obtained in a cumulative cohort of n = 187 patients and 1, 385 samples indicates that contactless sensors, particularly the Leap Motion Controller (LMC), can be used to assess UPDRS hand motor tasks 3.4, 3.5, 3.6, 3.15, and 3.17, although accuracy varies. Early evidence shows that sensor-based methods have clinical potential and might, after refinement, complement, or serve as a support to subjective assessment procedures. Given the nature of UPDRS assessment, future studies should observe whether LMC classification error falls within inter-rater variability for clinician-measured UPDRS scores to validate its clinical utility. Conversely, variables relevant to LMC classification such as power spectral densities or movement opening and closing speeds could set the basis for the design of more objective expert systems to assess hand dexterity in PD.
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spelling pubmed-85728882021-11-09 Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review Garcia-Agundez, Augusto Eickhoff, Carsten Front Aging Neurosci Neuroscience Assessing the progression of movement disorders such as Parkinson's Disease (PD) is key in adjusting therapeutic interventions. However, current methods are still based on subjective factors such as visual observation, resulting in significant inter-rater variability on clinical scales such as UPDRS. Recent studies show the potential of sensor-based methods to address this limitation. The goal of this systematic review is to provide an up-to-date analysis of contactless sensor-based methods to estimate hand dexterity UPDRS scores in PD patients. Two hundred and twenty-four abstracts were screened and nine articles selected for analysis. Evidence obtained in a cumulative cohort of n = 187 patients and 1, 385 samples indicates that contactless sensors, particularly the Leap Motion Controller (LMC), can be used to assess UPDRS hand motor tasks 3.4, 3.5, 3.6, 3.15, and 3.17, although accuracy varies. Early evidence shows that sensor-based methods have clinical potential and might, after refinement, complement, or serve as a support to subjective assessment procedures. Given the nature of UPDRS assessment, future studies should observe whether LMC classification error falls within inter-rater variability for clinician-measured UPDRS scores to validate its clinical utility. Conversely, variables relevant to LMC classification such as power spectral densities or movement opening and closing speeds could set the basis for the design of more objective expert systems to assess hand dexterity in PD. Frontiers Media S.A. 2021-10-25 /pmc/articles/PMC8572888/ /pubmed/34759810 http://dx.doi.org/10.3389/fnagi.2021.716102 Text en Copyright © 2021 Garcia-Agundez and Eickhoff. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Garcia-Agundez, Augusto
Eickhoff, Carsten
Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review
title Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review
title_full Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review
title_fullStr Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review
title_full_unstemmed Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review
title_short Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review
title_sort towards objective quantification of hand tremors and bradykinesia using contactless sensors: a systematic review
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8572888/
https://www.ncbi.nlm.nih.gov/pubmed/34759810
http://dx.doi.org/10.3389/fnagi.2021.716102
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