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Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease
Parkinson’s disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. Dyskinesia and motor fluctuations are complications of PD medications. An objective measure of on/off time with/without dyskinesia has been sought for some time because it would facilitate the tit...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864964/ https://www.ncbi.nlm.nih.gov/pubmed/33547317 http://dx.doi.org/10.1038/s41597-021-00831-z |
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author | Vergara-Diaz, Gloria Daneault, Jean-Francois Parisi, Federico Admati, Chen Alfonso, Christina Bertoli, Matilde Bonizzoni, Edoardo Carvalho, Gabriela Ferreira Costante, Gianluca Fabara, Eric Eduardo Fixler, Naama Golabchi, Fatemah Noushin Growdon, John Sapienza, Stefano Snyder, Phil Shpigelman, Shahar Sudarsky, Lewis Daeschler, Margaret Bataille, Lauren Sieberts, Solveig K. Omberg, Larsson Moore, Steven Bonato, Paolo |
author_facet | Vergara-Diaz, Gloria Daneault, Jean-Francois Parisi, Federico Admati, Chen Alfonso, Christina Bertoli, Matilde Bonizzoni, Edoardo Carvalho, Gabriela Ferreira Costante, Gianluca Fabara, Eric Eduardo Fixler, Naama Golabchi, Fatemah Noushin Growdon, John Sapienza, Stefano Snyder, Phil Shpigelman, Shahar Sudarsky, Lewis Daeschler, Margaret Bataille, Lauren Sieberts, Solveig K. Omberg, Larsson Moore, Steven Bonato, Paolo |
author_sort | Vergara-Diaz, Gloria |
collection | PubMed |
description | Parkinson’s disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. Dyskinesia and motor fluctuations are complications of PD medications. An objective measure of on/off time with/without dyskinesia has been sought for some time because it would facilitate the titration of medications. The objective of the dataset herein presented is to assess if wearable sensor data can be used to generate accurate estimates of limb-specific symptom severity. Nineteen subjects with PD experiencing motor fluctuations were asked to wear a total of five wearable sensors on both forearms and shanks, as well as on the lower back. Accelerometer data was collected for four days, including two laboratory visits lasting 3 to 4 hours each while the remainder of the time was spent at home and in the community. During the laboratory visits, subjects performed a battery of motor tasks while clinicians rated limb-specific symptom severity. At home, subjects were instructed to use a smartphone app that guided the periodic performance of a set of motor tasks. |
format | Online Article Text |
id | pubmed-7864964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78649642021-02-16 Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease Vergara-Diaz, Gloria Daneault, Jean-Francois Parisi, Federico Admati, Chen Alfonso, Christina Bertoli, Matilde Bonizzoni, Edoardo Carvalho, Gabriela Ferreira Costante, Gianluca Fabara, Eric Eduardo Fixler, Naama Golabchi, Fatemah Noushin Growdon, John Sapienza, Stefano Snyder, Phil Shpigelman, Shahar Sudarsky, Lewis Daeschler, Margaret Bataille, Lauren Sieberts, Solveig K. Omberg, Larsson Moore, Steven Bonato, Paolo Sci Data Data Descriptor Parkinson’s disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. Dyskinesia and motor fluctuations are complications of PD medications. An objective measure of on/off time with/without dyskinesia has been sought for some time because it would facilitate the titration of medications. The objective of the dataset herein presented is to assess if wearable sensor data can be used to generate accurate estimates of limb-specific symptom severity. Nineteen subjects with PD experiencing motor fluctuations were asked to wear a total of five wearable sensors on both forearms and shanks, as well as on the lower back. Accelerometer data was collected for four days, including two laboratory visits lasting 3 to 4 hours each while the remainder of the time was spent at home and in the community. During the laboratory visits, subjects performed a battery of motor tasks while clinicians rated limb-specific symptom severity. At home, subjects were instructed to use a smartphone app that guided the periodic performance of a set of motor tasks. Nature Publishing Group UK 2021-02-05 /pmc/articles/PMC7864964/ /pubmed/33547317 http://dx.doi.org/10.1038/s41597-021-00831-z Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Vergara-Diaz, Gloria Daneault, Jean-Francois Parisi, Federico Admati, Chen Alfonso, Christina Bertoli, Matilde Bonizzoni, Edoardo Carvalho, Gabriela Ferreira Costante, Gianluca Fabara, Eric Eduardo Fixler, Naama Golabchi, Fatemah Noushin Growdon, John Sapienza, Stefano Snyder, Phil Shpigelman, Shahar Sudarsky, Lewis Daeschler, Margaret Bataille, Lauren Sieberts, Solveig K. Omberg, Larsson Moore, Steven Bonato, Paolo Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease |
title | Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease |
title_full | Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease |
title_fullStr | Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease |
title_full_unstemmed | Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease |
title_short | Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease |
title_sort | limb and trunk accelerometer data collected with wearable sensors from subjects with parkinson’s disease |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864964/ https://www.ncbi.nlm.nih.gov/pubmed/33547317 http://dx.doi.org/10.1038/s41597-021-00831-z |
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