Cargando…

How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest

This study aimed to determine the most sensitive objective measures of balance dysfunction that differ between people with Parkinson’s Disease (PD) and healthy controls. One-hundred and forty-four people with PD and 79 age-matched healthy controls wore eight inertial sensors while performing tasks t...

Descripción completa

Detalles Bibliográficos
Autores principales: Hasegawa, Naoya, Shah, Vrutangkumar V., Carlson-Kuhta, Patricia, Nutt, John G., Horak, Fay B., Mancini, Martina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6696209/
https://www.ncbi.nlm.nih.gov/pubmed/31357742
http://dx.doi.org/10.3390/s19153320
_version_ 1783444216632836096
author Hasegawa, Naoya
Shah, Vrutangkumar V.
Carlson-Kuhta, Patricia
Nutt, John G.
Horak, Fay B.
Mancini, Martina
author_facet Hasegawa, Naoya
Shah, Vrutangkumar V.
Carlson-Kuhta, Patricia
Nutt, John G.
Horak, Fay B.
Mancini, Martina
author_sort Hasegawa, Naoya
collection PubMed
description This study aimed to determine the most sensitive objective measures of balance dysfunction that differ between people with Parkinson’s Disease (PD) and healthy controls. One-hundred and forty-four people with PD and 79 age-matched healthy controls wore eight inertial sensors while performing tasks to measure five domains of balance: standing posture (Sway), anticipatory postural adjustments (APAs), automatic postural responses (APRs), dynamic posture (Gait) and limits of stability (LOS). To reduce the initial 93 measures, we selected uncorrelated measures that were most sensitive to PD. After applying a threshold on the Standardized Mean Difference between PD and healthy controls, 44 measures remained; and after reducing highly correlated measures, 24 measures remained. The four most sensitive measures were from APAs and Gait domains. The random forest with 10-fold cross-validation on the remaining measures (n = 24) showed an accuracy to separate PD from healthy controls of 82.4%—identical to result for all measures. Measures from the most sensitive domains, APAs and Gait, were significantly correlated with the severity of disease and with patient-related outcomes. This method greatly reduced the objective measures of balance to the most sensitive for PD, while still capturing four of the five domains of balance.
format Online
Article
Text
id pubmed-6696209
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-66962092019-09-05 How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest Hasegawa, Naoya Shah, Vrutangkumar V. Carlson-Kuhta, Patricia Nutt, John G. Horak, Fay B. Mancini, Martina Sensors (Basel) Article This study aimed to determine the most sensitive objective measures of balance dysfunction that differ between people with Parkinson’s Disease (PD) and healthy controls. One-hundred and forty-four people with PD and 79 age-matched healthy controls wore eight inertial sensors while performing tasks to measure five domains of balance: standing posture (Sway), anticipatory postural adjustments (APAs), automatic postural responses (APRs), dynamic posture (Gait) and limits of stability (LOS). To reduce the initial 93 measures, we selected uncorrelated measures that were most sensitive to PD. After applying a threshold on the Standardized Mean Difference between PD and healthy controls, 44 measures remained; and after reducing highly correlated measures, 24 measures remained. The four most sensitive measures were from APAs and Gait domains. The random forest with 10-fold cross-validation on the remaining measures (n = 24) showed an accuracy to separate PD from healthy controls of 82.4%—identical to result for all measures. Measures from the most sensitive domains, APAs and Gait, were significantly correlated with the severity of disease and with patient-related outcomes. This method greatly reduced the objective measures of balance to the most sensitive for PD, while still capturing four of the five domains of balance. MDPI 2019-07-28 /pmc/articles/PMC6696209/ /pubmed/31357742 http://dx.doi.org/10.3390/s19153320 Text en © 2019 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
Hasegawa, Naoya
Shah, Vrutangkumar V.
Carlson-Kuhta, Patricia
Nutt, John G.
Horak, Fay B.
Mancini, Martina
How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest
title How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest
title_full How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest
title_fullStr How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest
title_full_unstemmed How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest
title_short How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest
title_sort how to select balance measures sensitive to parkinson’s disease from body-worn inertial sensors—separating the trees from the forest
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6696209/
https://www.ncbi.nlm.nih.gov/pubmed/31357742
http://dx.doi.org/10.3390/s19153320
work_keys_str_mv AT hasegawanaoya howtoselectbalancemeasuressensitivetoparkinsonsdiseasefrombodyworninertialsensorsseparatingthetreesfromtheforest
AT shahvrutangkumarv howtoselectbalancemeasuressensitivetoparkinsonsdiseasefrombodyworninertialsensorsseparatingthetreesfromtheforest
AT carlsonkuhtapatricia howtoselectbalancemeasuressensitivetoparkinsonsdiseasefrombodyworninertialsensorsseparatingthetreesfromtheforest
AT nuttjohng howtoselectbalancemeasuressensitivetoparkinsonsdiseasefrombodyworninertialsensorsseparatingthetreesfromtheforest
AT horakfayb howtoselectbalancemeasuressensitivetoparkinsonsdiseasefrombodyworninertialsensorsseparatingthetreesfromtheforest
AT mancinimartina howtoselectbalancemeasuressensitivetoparkinsonsdiseasefrombodyworninertialsensorsseparatingthetreesfromtheforest