Literature DB >> 28784922

Consumer-Based Physical Activity Monitor as a Practical Way to Measure Walking Intensity During Inpatient Stroke Rehabilitation.

Tara D Klassen1, Jennifer A Semrau1, Sean P Dukelow1, Mark T Bayley1, Michael D Hill1, Janice J Eng2.   

Abstract

BACKGROUND AND
PURPOSE: Identifying practical ways to accurately measure exercise intensity and dose in clinical environments is essential to advancing stroke rehabilitation. This is especially relevant in monitoring walking activity during inpatient rehabilitation where recovery is greatest. This study evaluated the accuracy of a readily available consumer-based physical activity monitor during daily inpatient stroke rehabilitation physical therapy sessions.
METHODS: Twenty-one individuals admitted to inpatient rehabilitation were monitored for a total of 471 one-hour physical therapy sessions which consisted of walking and nonwalking therapeutic activities. Participants wore a consumer-based physical activity monitor (Fitbit One) and the gold standard for assessing step count (StepWatch Activity Monitor) during physical therapy sessions. Linear mixed modeling was used to assess the relationship of the step count of the Fitbit to the StepWatch Activity Monitor. Device accuracy is reported as the percent error of the Fitbit compared with the StepWatch Activity Monitor.
RESULTS: A strong relationship (slope=0.99; 95% confidence interval, 0.97-1.01) was found between the number of steps captured by the Fitbit One and the StepWatch Activity Monitor. The Fitbit One had a mean error of 10.9% (5.3) for participants with walking velocities <0.4 m/s, 6.8% (3.0) for walking velocities between 0.4 and 0.8 m/s, and 4.4% (2.8) for walking velocities >0.8 m/s.
CONCLUSIONS: This study provides preliminary evidence that the Fitbit One, when positioned on the nonparetic ankle, can accurately measure walking steps early after stroke during inpatient rehabilitation physical therapy sessions. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01915368.
© 2017 American Heart Association, Inc.

Entities:  

Keywords:  ankle; rehabilitation; stroke; technology; walking

Mesh:

Year:  2017        PMID: 28784922     DOI: 10.1161/STROKEAHA.117.018175

Source DB:  PubMed          Journal:  Stroke        ISSN: 0039-2499            Impact factor:   7.914


  16 in total

1.  Clinician's Commentary on Hui et al.1.

Authors:  Susan Marzolini
Journal:  Physiother Can       Date:  2018       Impact factor: 1.037

2.  Step Monitor Accuracy During PostStroke Physical Therapy and Simulated Activities.

Authors:  Christopher E Henderson; Lindsay Toth; Andrew Kaplan; T George Hornby
Journal:  Transl J Am Coll Sports Med       Date:  2022

3.  Relationships Among Environmental Variables, Physical Capacity, Balance Self-Efficacy, and Real-World Walking Activity Post-Stroke.

Authors:  Allison Miller; Ryan T Pohlig; Darcy S Reisman
Journal:  Neurorehabil Neural Repair       Date:  2022-08-04       Impact factor: 4.895

4.  Influence of upper limb activity on the step count and accuracy of sleep time of a wristband-type physical activity tracker.

Authors:  Nobuyuki Sano; Takanori Taniguchi; Hisato Nakazono
Journal:  PLoS One       Date:  2022-07-08       Impact factor: 3.752

5.  A machine learning approach to identifying important features for achieving step thresholds in individuals with chronic stroke.

Authors:  Allison E Miller; Emily Russell; Darcy S Reisman; Hyosub E Kim; Vu Dinh
Journal:  PLoS One       Date:  2022-06-17       Impact factor: 3.752

6.  Locomotor training intensity after stroke: Effects of interval type and mode.

Authors:  Pierce Boyne; Victoria Scholl; Sarah Doren; Daniel Carl; Sandra A Billinger; Darcy S Reisman; Myron Gerson; Brett Kissela; Jennifer Vannest; Kari Dunning
Journal:  Top Stroke Rehabil       Date:  2020-02-16       Impact factor: 2.119

7.  Social and physical environmental factors in daily stepping activity in those with chronic stroke.

Authors:  Allison Miller; Ryan T Pohlig; Darcy S Reisman
Journal:  Top Stroke Rehabil       Date:  2020-08-10       Impact factor: 2.119

8.  Readiness to Change is Related to Real-World Walking and Depressive Symptoms in Chronic Stroke.

Authors:  Allison Miller; Tamara Wright; Henry Wright; Elizabeth Thompson; Ryan T Pohlig; Darcy S Reisman
Journal:  J Neurol Phys Ther       Date:  2021-01       Impact factor: 4.655

9.  Activity Tracker-Based Metrics as Digital Markers of Cardiometabolic Health in Working Adults: Cross-Sectional Study.

Authors:  Yuri Rykov; Thuan-Quoc Thach; Gerard Dunleavy; Adam Charles Roberts; George Christopoulos; Chee-Kiong Soh; Josip Car
Journal:  JMIR Mhealth Uhealth       Date:  2020-01-31       Impact factor: 4.773

10.  Perspectives on the prospective development of stroke-specific lower extremity wearable monitoring technology: a qualitative focus group study with physical therapists and individuals with stroke.

Authors:  Dennis R Louie; Marie-Louise Bird; Carlo Menon; Janice J Eng
Journal:  J Neuroeng Rehabil       Date:  2020-02-25       Impact factor: 4.262

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