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Recognizing Complex Upper Extremity Activities Using Body Worn Sensors

To evaluate arm-hand therapies for neurological patients it is important to be able to assess actual arm-hand performance objectively. Because instruments that measure the actual quality and quantity of specific activities in daily life are lacking, a new measure needs to be developed. The aims of t...

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Autores principales: Lemmens, Ryanne J. M., Janssen-Potten, Yvonne J. M., Timmermans, Annick A. A., Smeets, Rob J. E. M., Seelen, Henk A. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4348509/
https://www.ncbi.nlm.nih.gov/pubmed/25734641
http://dx.doi.org/10.1371/journal.pone.0118642
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author Lemmens, Ryanne J. M.
Janssen-Potten, Yvonne J. M.
Timmermans, Annick A. A.
Smeets, Rob J. E. M.
Seelen, Henk A. M.
author_facet Lemmens, Ryanne J. M.
Janssen-Potten, Yvonne J. M.
Timmermans, Annick A. A.
Smeets, Rob J. E. M.
Seelen, Henk A. M.
author_sort Lemmens, Ryanne J. M.
collection PubMed
description To evaluate arm-hand therapies for neurological patients it is important to be able to assess actual arm-hand performance objectively. Because instruments that measure the actual quality and quantity of specific activities in daily life are lacking, a new measure needs to be developed. The aims of this study are to a) elucidate the techniques used to identify upper extremity activities, b) provide a proof-of-principle of this method using a set of activities tested in a healthy adult and in a stroke patient, and c) provide an example of the method’s applicability in daily life based on readings taken from a healthy adult. Multiple devices, each of which contains a tri-axial accelerometer, a tri-axial gyroscope and a tri-axial magnetometer were attached to the dominant hand, wrist, upper arm and chest of 30 healthy participants and one stroke patient, who all performed the tasks ‘drinking’, ‘eating’ and ‘brushing hair’ in a standardized environment. To establish proof-of-principle, a prolonged daily life recording of 1 participant was used to identify the task ‘drinking’. The activities were identified using multi-array signal feature extraction and pattern recognition algorithms and 2D-convolution. The activities ‘drinking’, ‘eating’ and ‘brushing hair’ were unambiguously recognized in a sequence of recordings of multiple standardized daily activities in a healthy participant and in a stroke patient. It was also possible to identify a specific activity in a daily life recording. The long term aim is to use this method to a) identify arm-hand activities that someone performs during daily life, b) determine the quantity of activity execution, i.e. amount of use, and c) determine the quality of arm-hand skill performance.
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spelling pubmed-43485092015-03-06 Recognizing Complex Upper Extremity Activities Using Body Worn Sensors Lemmens, Ryanne J. M. Janssen-Potten, Yvonne J. M. Timmermans, Annick A. A. Smeets, Rob J. E. M. Seelen, Henk A. M. PLoS One Research Article To evaluate arm-hand therapies for neurological patients it is important to be able to assess actual arm-hand performance objectively. Because instruments that measure the actual quality and quantity of specific activities in daily life are lacking, a new measure needs to be developed. The aims of this study are to a) elucidate the techniques used to identify upper extremity activities, b) provide a proof-of-principle of this method using a set of activities tested in a healthy adult and in a stroke patient, and c) provide an example of the method’s applicability in daily life based on readings taken from a healthy adult. Multiple devices, each of which contains a tri-axial accelerometer, a tri-axial gyroscope and a tri-axial magnetometer were attached to the dominant hand, wrist, upper arm and chest of 30 healthy participants and one stroke patient, who all performed the tasks ‘drinking’, ‘eating’ and ‘brushing hair’ in a standardized environment. To establish proof-of-principle, a prolonged daily life recording of 1 participant was used to identify the task ‘drinking’. The activities were identified using multi-array signal feature extraction and pattern recognition algorithms and 2D-convolution. The activities ‘drinking’, ‘eating’ and ‘brushing hair’ were unambiguously recognized in a sequence of recordings of multiple standardized daily activities in a healthy participant and in a stroke patient. It was also possible to identify a specific activity in a daily life recording. The long term aim is to use this method to a) identify arm-hand activities that someone performs during daily life, b) determine the quantity of activity execution, i.e. amount of use, and c) determine the quality of arm-hand skill performance. Public Library of Science 2015-03-03 /pmc/articles/PMC4348509/ /pubmed/25734641 http://dx.doi.org/10.1371/journal.pone.0118642 Text en © 2015 Lemmens et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lemmens, Ryanne J. M.
Janssen-Potten, Yvonne J. M.
Timmermans, Annick A. A.
Smeets, Rob J. E. M.
Seelen, Henk A. M.
Recognizing Complex Upper Extremity Activities Using Body Worn Sensors
title Recognizing Complex Upper Extremity Activities Using Body Worn Sensors
title_full Recognizing Complex Upper Extremity Activities Using Body Worn Sensors
title_fullStr Recognizing Complex Upper Extremity Activities Using Body Worn Sensors
title_full_unstemmed Recognizing Complex Upper Extremity Activities Using Body Worn Sensors
title_short Recognizing Complex Upper Extremity Activities Using Body Worn Sensors
title_sort recognizing complex upper extremity activities using body worn sensors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4348509/
https://www.ncbi.nlm.nih.gov/pubmed/25734641
http://dx.doi.org/10.1371/journal.pone.0118642
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