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Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment

INTRODUCTION: Many clinical studies reporting accelerometry data use sum score measures such as percentage of time spent in moderate to vigorous activity which do not provide insight into differences in activity patterns over 24 hours, and thus do not adequately depict circadian activity patterns. H...

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Autores principales: Rackoll, Torsten, Neumann, Konrad, Passmann, Sven, Grittner, Ulrike, Külzow, Nadine, Ladenbauer, Julia, Flöel, Agnes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118312/
https://www.ncbi.nlm.nih.gov/pubmed/33984029
http://dx.doi.org/10.1371/journal.pone.0251544
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author Rackoll, Torsten
Neumann, Konrad
Passmann, Sven
Grittner, Ulrike
Külzow, Nadine
Ladenbauer, Julia
Flöel, Agnes
author_facet Rackoll, Torsten
Neumann, Konrad
Passmann, Sven
Grittner, Ulrike
Külzow, Nadine
Ladenbauer, Julia
Flöel, Agnes
author_sort Rackoll, Torsten
collection PubMed
description INTRODUCTION: Many clinical studies reporting accelerometry data use sum score measures such as percentage of time spent in moderate to vigorous activity which do not provide insight into differences in activity patterns over 24 hours, and thus do not adequately depict circadian activity patterns. Here, we present an improved functional data analysis approach to model activity patterns and circadian rhythms from accelerometer data. As a use case, we demonstrated its application in patients with mild cognitive impairment (MCI) and age-matched healthy older volunteers (HOV). METHODS: Data of two studies were pooled for this analysis. Following baseline cognitive assessment participants were provided with accelerometers for seven consecutive days. A function on scalar regression (FoSR) approach was used to analyze 24 hours accelerometer data. RESULTS: Information on 48 HOV (mean age 65 SD 6 years) and 18 patients with MCI (mean age 70, SD 8 years) were available for this analysis. MCI patients displayed slightly lower activity in the morning hours (minimum relative activity at 6:05 am: -41.3%, 95% CI -64.7 to -2.5%, p = 0.031) and in the evening (minimum relative activity at 21:40 am: -48.4%, 95% CI -68.5 to 15.4%, p = 0.001) as compared to HOV after adjusting for age and sex. DISCUSSION: Using a novel approach of FoSR, we found timeframes with lower activity levels in MCI patients compared to HOV which were not evident if sum scores of amount of activity were used, possibly indicating that changes in circadian rhythmicity in neurodegenerative disease are detectable using easy-to-administer accelerometry. CLINICAL TRIALS: Effects of Brain Stimulation During Nocturnal Sleep on Memory Consolidation in Patients With Mild Cognitive Impairments, ClinicalTrial.gov identifier: NCT01782391. Effects of Brain Stimulation During a Daytime Nap on Memory Consolidation in Patients With Mild Cognitive Impairment, ClinicalTrial.gov identifier: NCT01782365.
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spelling pubmed-81183122021-05-24 Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment Rackoll, Torsten Neumann, Konrad Passmann, Sven Grittner, Ulrike Külzow, Nadine Ladenbauer, Julia Flöel, Agnes PLoS One Research Article INTRODUCTION: Many clinical studies reporting accelerometry data use sum score measures such as percentage of time spent in moderate to vigorous activity which do not provide insight into differences in activity patterns over 24 hours, and thus do not adequately depict circadian activity patterns. Here, we present an improved functional data analysis approach to model activity patterns and circadian rhythms from accelerometer data. As a use case, we demonstrated its application in patients with mild cognitive impairment (MCI) and age-matched healthy older volunteers (HOV). METHODS: Data of two studies were pooled for this analysis. Following baseline cognitive assessment participants were provided with accelerometers for seven consecutive days. A function on scalar regression (FoSR) approach was used to analyze 24 hours accelerometer data. RESULTS: Information on 48 HOV (mean age 65 SD 6 years) and 18 patients with MCI (mean age 70, SD 8 years) were available for this analysis. MCI patients displayed slightly lower activity in the morning hours (minimum relative activity at 6:05 am: -41.3%, 95% CI -64.7 to -2.5%, p = 0.031) and in the evening (minimum relative activity at 21:40 am: -48.4%, 95% CI -68.5 to 15.4%, p = 0.001) as compared to HOV after adjusting for age and sex. DISCUSSION: Using a novel approach of FoSR, we found timeframes with lower activity levels in MCI patients compared to HOV which were not evident if sum scores of amount of activity were used, possibly indicating that changes in circadian rhythmicity in neurodegenerative disease are detectable using easy-to-administer accelerometry. CLINICAL TRIALS: Effects of Brain Stimulation During Nocturnal Sleep on Memory Consolidation in Patients With Mild Cognitive Impairments, ClinicalTrial.gov identifier: NCT01782391. Effects of Brain Stimulation During a Daytime Nap on Memory Consolidation in Patients With Mild Cognitive Impairment, ClinicalTrial.gov identifier: NCT01782365. Public Library of Science 2021-05-13 /pmc/articles/PMC8118312/ /pubmed/33984029 http://dx.doi.org/10.1371/journal.pone.0251544 Text en © 2021 Rackoll et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Rackoll, Torsten
Neumann, Konrad
Passmann, Sven
Grittner, Ulrike
Külzow, Nadine
Ladenbauer, Julia
Flöel, Agnes
Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment
title Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment
title_full Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment
title_fullStr Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment
title_full_unstemmed Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment
title_short Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment
title_sort applying time series analyses on continuous accelerometry data—a clinical example in older adults with and without cognitive impairment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118312/
https://www.ncbi.nlm.nih.gov/pubmed/33984029
http://dx.doi.org/10.1371/journal.pone.0251544
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