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Nonparametric methods in actigraphy: An update
Circadian rhythmicity in humans has been well studied using actigraphy, a method of measuring gross motor movement. As actigraphic technology continues to evolve, it is important for data analysis to keep pace with new variables and features. Our objective is to study the behavior of two variables,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4559593/ https://www.ncbi.nlm.nih.gov/pubmed/26483921 http://dx.doi.org/10.1016/j.slsci.2014.09.013 |
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author | Gonçalves, Bruno S.B. Cavalcanti, Paula R.A. Tavares, Gracilene R. Campos, Tania F. Araujo, John F. |
author_facet | Gonçalves, Bruno S.B. Cavalcanti, Paula R.A. Tavares, Gracilene R. Campos, Tania F. Araujo, John F. |
author_sort | Gonçalves, Bruno S.B. |
collection | PubMed |
description | Circadian rhythmicity in humans has been well studied using actigraphy, a method of measuring gross motor movement. As actigraphic technology continues to evolve, it is important for data analysis to keep pace with new variables and features. Our objective is to study the behavior of two variables, interdaily stability and intradaily variability, to describe rest activity rhythm. Simulated data and actigraphy data of humans, rats, and marmosets were used in this study. We modified the method of calculation for IV and IS by modifying the time intervals of analysis. For each variable, we calculated the average value (IVm and ISm) results for each time interval. Simulated data showed that (1) synchronization analysis depends on sample size, and (2) fragmentation is independent of the amplitude of the generated noise. We were able to obtain a significant difference in the fragmentation patterns of stroke patients using an IVm variable, while the variable IV60 was not identified. Rhythmic synchronization of activity and rest was significantly higher in young than adults with Parkinson׳s when using the ISM variable; however, this difference was not seen using IS60. We propose an updated format to calculate rhythmic fragmentation, including two additional optional variables. These alternative methods of nonparametric analysis aim to more precisely detect sleep–wake cycle fragmentation and synchronization. |
format | Online Article Text |
id | pubmed-4559593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-45595932015-10-19 Nonparametric methods in actigraphy: An update Gonçalves, Bruno S.B. Cavalcanti, Paula R.A. Tavares, Gracilene R. Campos, Tania F. Araujo, John F. Sleep Sci Original Article Circadian rhythmicity in humans has been well studied using actigraphy, a method of measuring gross motor movement. As actigraphic technology continues to evolve, it is important for data analysis to keep pace with new variables and features. Our objective is to study the behavior of two variables, interdaily stability and intradaily variability, to describe rest activity rhythm. Simulated data and actigraphy data of humans, rats, and marmosets were used in this study. We modified the method of calculation for IV and IS by modifying the time intervals of analysis. For each variable, we calculated the average value (IVm and ISm) results for each time interval. Simulated data showed that (1) synchronization analysis depends on sample size, and (2) fragmentation is independent of the amplitude of the generated noise. We were able to obtain a significant difference in the fragmentation patterns of stroke patients using an IVm variable, while the variable IV60 was not identified. Rhythmic synchronization of activity and rest was significantly higher in young than adults with Parkinson׳s when using the ISM variable; however, this difference was not seen using IS60. We propose an updated format to calculate rhythmic fragmentation, including two additional optional variables. These alternative methods of nonparametric analysis aim to more precisely detect sleep–wake cycle fragmentation and synchronization. Elsevier 2014-09 2014-09-29 /pmc/articles/PMC4559593/ /pubmed/26483921 http://dx.doi.org/10.1016/j.slsci.2014.09.013 Text en © 2014 Brazilian Association of Sleep. Production and Hosting by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). |
spellingShingle | Original Article Gonçalves, Bruno S.B. Cavalcanti, Paula R.A. Tavares, Gracilene R. Campos, Tania F. Araujo, John F. Nonparametric methods in actigraphy: An update |
title | Nonparametric methods in actigraphy: An update |
title_full | Nonparametric methods in actigraphy: An update |
title_fullStr | Nonparametric methods in actigraphy: An update |
title_full_unstemmed | Nonparametric methods in actigraphy: An update |
title_short | Nonparametric methods in actigraphy: An update |
title_sort | nonparametric methods in actigraphy: an update |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4559593/ https://www.ncbi.nlm.nih.gov/pubmed/26483921 http://dx.doi.org/10.1016/j.slsci.2014.09.013 |
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