Evidence map›Paper›PMID 37090658›Full record

ArticleResearch square2023

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

Marika Demers, Amelia Cain, Lauri Bishop, Tanisha Gunby, Justin B Rowe, Daniel Zondervan, Carolee J Winstein

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In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Marika DemersUniversity of Montreal.
Amelia CainUniversity of California, Los Angeles.
Lauri BishopUniversity of California, Los Angeles.
Tanisha GunbyUniversity of California, Los Angeles.
Justin B RoweFlint Rehabilitation Devices (United States).
Daniel ZondervanFlint Rehabilitation Devices (United States).
Carolee J WinsteinUniversity of California, Los Angeles.

Funding

Southern California Clinical and Translational Science InstituteUL1TR001855 · NCATS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Thomas A Buchanan, Michele D. Kipke · 2016 to 2026
$81.3M
Southern California Clinical and Translational Science InstituteUL1TR000130 · NCATS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BUCHANAN, THOMAS A · 2012 to 2015
$36.0M
MiGo: wearable sensors that combine actionable data with a behavioral intervention to improve function after strokeR41HD104296 · NICHD · FLINT REHABILITATION DEVICES · PI ROWE, JUSTIN, WINSTEIN, CAROLEE J · 2021 to 2021
$257k
NCATS NIH HHS UL1 TR000130NCATS NIH HHS UL1 TR001855NICHD NIH HHS R41 HD104296
6 · The paper itself

Abstract

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.

Indexed as

behavior changefeedbackmobilityrehabilitationstrokeupper extremityWearable electronic devices

Identifiers

PMID37090658
PMCPMC10120751

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.