Cargando…

Quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke

BACKGROUND: Individuals with hemiparesis post-stroke often have difficulty with tasks requiring upper extremity (UE) intra- and interlimb use, yet methods to quantify both are limited. OBJECTIVE: To develop a quantitative yet sensitive method to identify distinct features of UE intra- and interlimb...

Descripción completa

Detalles Bibliográficos
Autores principales: Duff, Susan V., Miller, Aaron, Quinn, Lori, Youdan, Gregory, Bishop, Lauri, Ruthrauff, Heather, Wade, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9077965/
https://www.ncbi.nlm.nih.gov/pubmed/35525970
http://dx.doi.org/10.1186/s12984-022-01020-8
_version_ 1784702226707513344
author Duff, Susan V.
Miller, Aaron
Quinn, Lori
Youdan, Gregory
Bishop, Lauri
Ruthrauff, Heather
Wade, Eric
author_facet Duff, Susan V.
Miller, Aaron
Quinn, Lori
Youdan, Gregory
Bishop, Lauri
Ruthrauff, Heather
Wade, Eric
author_sort Duff, Susan V.
collection PubMed
description BACKGROUND: Individuals with hemiparesis post-stroke often have difficulty with tasks requiring upper extremity (UE) intra- and interlimb use, yet methods to quantify both are limited. OBJECTIVE: To develop a quantitative yet sensitive method to identify distinct features of UE intra- and interlimb use during task performance. METHODS: Twenty adults post-stroke and 20 controls wore five inertial sensors (wrists, upper arms, sternum) during 12 seated UE tasks. Three sensor modalities (acceleration, angular rate of change, orientation) were examined for three metrics (peak to peak amplitude, time, and frequency). To allow for comparison between sensor data, the resultant values were combined into one motion parameter, per sensor pair, using a novel algorithm. This motion parameter was compared in a group-by-task analysis of variance as a similarity score (0–1) between key sensor pairs: sternum to wrist, wrist to wrist, and wrist to upper arm. A use ratio (paretic/non-paretic arm) was calculated in persons post-stroke from wrist sensor data for each modality and compared to scores from the Adult Assisting Hand Assessment (Ad-AHA Stroke) and UE Fugl-Meyer (UEFM). RESULTS: A significant group × task interaction in the similarity score was found for all key sensor pairs. Post-hoc tests between task type revealed significant differences in similarity for sensor pairs in 8/9 comparisons for controls and 3/9 comparisons for persons post stroke. The use ratio was significantly predictive of the Ad-AHA Stroke and UEFM scores for each modality. CONCLUSIONS: Our algorithm and sensor data analyses distinguished task type within and between groups and were predictive of clinical scores. Future work will assess reliability and validity of this novel metric to allow development of an easy-to-use app for clinicians.
format Online
Article
Text
id pubmed-9077965
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-90779652022-05-08 Quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke Duff, Susan V. Miller, Aaron Quinn, Lori Youdan, Gregory Bishop, Lauri Ruthrauff, Heather Wade, Eric J Neuroeng Rehabil Research BACKGROUND: Individuals with hemiparesis post-stroke often have difficulty with tasks requiring upper extremity (UE) intra- and interlimb use, yet methods to quantify both are limited. OBJECTIVE: To develop a quantitative yet sensitive method to identify distinct features of UE intra- and interlimb use during task performance. METHODS: Twenty adults post-stroke and 20 controls wore five inertial sensors (wrists, upper arms, sternum) during 12 seated UE tasks. Three sensor modalities (acceleration, angular rate of change, orientation) were examined for three metrics (peak to peak amplitude, time, and frequency). To allow for comparison between sensor data, the resultant values were combined into one motion parameter, per sensor pair, using a novel algorithm. This motion parameter was compared in a group-by-task analysis of variance as a similarity score (0–1) between key sensor pairs: sternum to wrist, wrist to wrist, and wrist to upper arm. A use ratio (paretic/non-paretic arm) was calculated in persons post-stroke from wrist sensor data for each modality and compared to scores from the Adult Assisting Hand Assessment (Ad-AHA Stroke) and UE Fugl-Meyer (UEFM). RESULTS: A significant group × task interaction in the similarity score was found for all key sensor pairs. Post-hoc tests between task type revealed significant differences in similarity for sensor pairs in 8/9 comparisons for controls and 3/9 comparisons for persons post stroke. The use ratio was significantly predictive of the Ad-AHA Stroke and UEFM scores for each modality. CONCLUSIONS: Our algorithm and sensor data analyses distinguished task type within and between groups and were predictive of clinical scores. Future work will assess reliability and validity of this novel metric to allow development of an easy-to-use app for clinicians. BioMed Central 2022-05-07 /pmc/articles/PMC9077965/ /pubmed/35525970 http://dx.doi.org/10.1186/s12984-022-01020-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Duff, Susan V.
Miller, Aaron
Quinn, Lori
Youdan, Gregory
Bishop, Lauri
Ruthrauff, Heather
Wade, Eric
Quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke
title Quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke
title_full Quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke
title_fullStr Quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke
title_full_unstemmed Quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke
title_short Quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke
title_sort quantifying intra- and interlimb use during unimanual and bimanual tasks in persons with hemiparesis post-stroke
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9077965/
https://www.ncbi.nlm.nih.gov/pubmed/35525970
http://dx.doi.org/10.1186/s12984-022-01020-8
work_keys_str_mv AT duffsusanv quantifyingintraandinterlimbuseduringunimanualandbimanualtasksinpersonswithhemiparesispoststroke
AT milleraaron quantifyingintraandinterlimbuseduringunimanualandbimanualtasksinpersonswithhemiparesispoststroke
AT quinnlori quantifyingintraandinterlimbuseduringunimanualandbimanualtasksinpersonswithhemiparesispoststroke
AT youdangregory quantifyingintraandinterlimbuseduringunimanualandbimanualtasksinpersonswithhemiparesispoststroke
AT bishoplauri quantifyingintraandinterlimbuseduringunimanualandbimanualtasksinpersonswithhemiparesispoststroke
AT ruthrauffheather quantifyingintraandinterlimbuseduringunimanualandbimanualtasksinpersonswithhemiparesispoststroke
AT wadeeric quantifyingintraandinterlimbuseduringunimanualandbimanualtasksinpersonswithhemiparesispoststroke