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Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers?
Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant’s naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locati...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611403/ https://www.ncbi.nlm.nih.gov/pubmed/37896635 http://dx.doi.org/10.3390/s23208542 |
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author | Lin, Wenyi Karahanoglu, Fikret Isik Psaltos, Dimitrios Adamowicz, Lukas Santamaria, Mar Cai, Xuemei Demanuele, Charmaine Di, Junrui |
author_facet | Lin, Wenyi Karahanoglu, Fikret Isik Psaltos, Dimitrios Adamowicz, Lukas Santamaria, Mar Cai, Xuemei Demanuele, Charmaine Di, Junrui |
author_sort | Lin, Wenyi |
collection | PubMed |
description | Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant’s naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA). Deploying multiple devices in clinical trial settings leads to higher patient burden negatively impacting compliance and data quality and increases the operational complexity of the trial. In this work, we evaluated the joint information shared by features derived from the lumbar and wrist devices to assess whether gait characteristics can be adequately represented by PA measured with wrist-worn devices. Data collected at the Pfizer Innovation Research (PfIRe) Lab were used as a real data example, which had around 7 days of continuous at-home data from wrist- and lumbar-worn devices (GENEActiv) obtained from a group of healthy participants. The relationship between wrist- and lumbar-derived features was estimated using multiple statistical methods, including penalized regression, principal component regression, partial least square regression, and joint and individual variation explained (JIVE). By considering multilevel models, both between- and within-subject effects were taken into account. This work demonstrated that selected gait features, which are typically measured with lumbar-worn devices, can be represented by PA features measured with wrist-worn devices, which provides preliminary evidence to reduce the number of devices needed in clinical trials and to increase patients’ comfort. Moreover, the statistical methods used in this work provided an analytic framework to compare repeated measures collected from multiple data modalities. |
format | Online Article Text |
id | pubmed-10611403 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106114032023-10-28 Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers? Lin, Wenyi Karahanoglu, Fikret Isik Psaltos, Dimitrios Adamowicz, Lukas Santamaria, Mar Cai, Xuemei Demanuele, Charmaine Di, Junrui Sensors (Basel) Article Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant’s naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA). Deploying multiple devices in clinical trial settings leads to higher patient burden negatively impacting compliance and data quality and increases the operational complexity of the trial. In this work, we evaluated the joint information shared by features derived from the lumbar and wrist devices to assess whether gait characteristics can be adequately represented by PA measured with wrist-worn devices. Data collected at the Pfizer Innovation Research (PfIRe) Lab were used as a real data example, which had around 7 days of continuous at-home data from wrist- and lumbar-worn devices (GENEActiv) obtained from a group of healthy participants. The relationship between wrist- and lumbar-derived features was estimated using multiple statistical methods, including penalized regression, principal component regression, partial least square regression, and joint and individual variation explained (JIVE). By considering multilevel models, both between- and within-subject effects were taken into account. This work demonstrated that selected gait features, which are typically measured with lumbar-worn devices, can be represented by PA features measured with wrist-worn devices, which provides preliminary evidence to reduce the number of devices needed in clinical trials and to increase patients’ comfort. Moreover, the statistical methods used in this work provided an analytic framework to compare repeated measures collected from multiple data modalities. MDPI 2023-10-18 /pmc/articles/PMC10611403/ /pubmed/37896635 http://dx.doi.org/10.3390/s23208542 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lin, Wenyi Karahanoglu, Fikret Isik Psaltos, Dimitrios Adamowicz, Lukas Santamaria, Mar Cai, Xuemei Demanuele, Charmaine Di, Junrui Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers? |
title | Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers? |
title_full | Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers? |
title_fullStr | Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers? |
title_full_unstemmed | Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers? |
title_short | Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers? |
title_sort | can gait characteristics be represented by physical activity measured with wrist-worn accelerometers? |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611403/ https://www.ncbi.nlm.nih.gov/pubmed/37896635 http://dx.doi.org/10.3390/s23208542 |
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