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Understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study

BACKGROUND: In stroke rehabilitation, wearable technology can be used as an intervention modality by providing timely, meaningful feedback on motor performance. Stroke survivors’ preferences may offer a unique perspective on what metrics are intuitive, actionable, and meaningful to change behavior....

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Autores principales: Demers, Marika, Cain, Amelia, Bishop, Lauri, Gunby, Tanisha, Rowe, Justin B, Zondervan, Daniel, Winstein, Carolee J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120751/
https://www.ncbi.nlm.nih.gov/pubmed/37090658
http://dx.doi.org/10.21203/rs.3.rs-2789807/v1
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author Demers, Marika
Cain, Amelia
Bishop, Lauri
Gunby, Tanisha
Rowe, Justin B
Zondervan, Daniel
Winstein, Carolee J
author_facet Demers, Marika
Cain, Amelia
Bishop, Lauri
Gunby, Tanisha
Rowe, Justin B
Zondervan, Daniel
Winstein, Carolee J
author_sort Demers, Marika
collection PubMed
description BACKGROUND: In stroke rehabilitation, wearable technology can be used as an intervention modality by providing timely, meaningful feedback on motor performance. Stroke survivors’ preferences may offer a unique perspective on what metrics are intuitive, actionable, and meaningful to change behavior. However, few studies have identified feedback preferences from stroke survivors. This project aims to determine stroke survivors’ satisfaction with feedback from wearable sensors (both mobility and arm/hand use) and to identify preferences for feedback type and delivery schedule. METHODS: A sample of 30 chronic stroke survivors wore a multi-sensor system in the natural environment over a 1-week monitoring period. The sensor system captured time in active movement of each arm, arm use ratio, step counts and stance time symmetry. Using the data from the monitoring period, participants were presented with a movement report with visual displays of quantitative and qualitative feedback. A survey and qualitative interview were used to assess ease of understanding, actionability and components of feedback that users found most meaningful to drive lasting behavior change. RESULTS: Arm/hand use and mobility sensor-derived feedback metrics were easy to understand and actionable. The preferred metric to encourage arm/hand use was the hourly arm use bar plot, and similarly the preferred metric to encourage mobility was the hourly steps bar plot, which were each ranked as top choice by 40% of participants. Participants perceived that quantitative (i.e., step counts) and qualitative (i.e., stance time symmetry) mobility metrics provided complementary information. Three main themes emerged from the qualitative analysis: 1) Motivation for behavior change, 2) Real-time feedback based on individual goals, and 3) Value of experienced clinicians for prescription and accountability. Participants stressed the importance of having feedback tailored to their own personalized goals and receiving guidance from clinicians on strategies to progress and increase functional movement behavior in the unsupervised home and community setting. CONCLUSION: The resulting technology has the potential to integrate engineering and personalized rehabilitation to maximize participation in meaningful life activities outside clinical settings in a less structured environment—one where stroke survivors live their lives.
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spelling pubmed-101207512023-04-22 Understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study Demers, Marika Cain, Amelia Bishop, Lauri Gunby, Tanisha Rowe, Justin B Zondervan, Daniel Winstein, Carolee J Res Sq Article BACKGROUND: In stroke rehabilitation, wearable technology can be used as an intervention modality by providing timely, meaningful feedback on motor performance. Stroke survivors’ preferences may offer a unique perspective on what metrics are intuitive, actionable, and meaningful to change behavior. However, few studies have identified feedback preferences from stroke survivors. This project aims to determine stroke survivors’ satisfaction with feedback from wearable sensors (both mobility and arm/hand use) and to identify preferences for feedback type and delivery schedule. METHODS: A sample of 30 chronic stroke survivors wore a multi-sensor system in the natural environment over a 1-week monitoring period. The sensor system captured time in active movement of each arm, arm use ratio, step counts and stance time symmetry. Using the data from the monitoring period, participants were presented with a movement report with visual displays of quantitative and qualitative feedback. A survey and qualitative interview were used to assess ease of understanding, actionability and components of feedback that users found most meaningful to drive lasting behavior change. RESULTS: Arm/hand use and mobility sensor-derived feedback metrics were easy to understand and actionable. The preferred metric to encourage arm/hand use was the hourly arm use bar plot, and similarly the preferred metric to encourage mobility was the hourly steps bar plot, which were each ranked as top choice by 40% of participants. Participants perceived that quantitative (i.e., step counts) and qualitative (i.e., stance time symmetry) mobility metrics provided complementary information. Three main themes emerged from the qualitative analysis: 1) Motivation for behavior change, 2) Real-time feedback based on individual goals, and 3) Value of experienced clinicians for prescription and accountability. Participants stressed the importance of having feedback tailored to their own personalized goals and receiving guidance from clinicians on strategies to progress and increase functional movement behavior in the unsupervised home and community setting. CONCLUSION: The resulting technology has the potential to integrate engineering and personalized rehabilitation to maximize participation in meaningful life activities outside clinical settings in a less structured environment—one where stroke survivors live their lives. American Journal Experts 2023-04-13 /pmc/articles/PMC10120751/ /pubmed/37090658 http://dx.doi.org/10.21203/rs.3.rs-2789807/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. https://creativecommons.org/licenses/by/4.0/License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License (https://creativecommons.org/licenses/by/4.0/)
spellingShingle Article
Demers, Marika
Cain, Amelia
Bishop, Lauri
Gunby, Tanisha
Rowe, Justin B
Zondervan, Daniel
Winstein, Carolee J
Understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study
title Understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study
title_full Understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study
title_fullStr Understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study
title_full_unstemmed Understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study
title_short Understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study
title_sort understanding preferences of stroke survivors for feedback provision about functional movement behavior from wearable sensors: a mixed-methods study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120751/
https://www.ncbi.nlm.nih.gov/pubmed/37090658
http://dx.doi.org/10.21203/rs.3.rs-2789807/v1
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