Christopher E Henderson1,2, Lindsay Toth3, Andrew Kaplan4, T George Hornby1,2,5. 1. Department of Physical Medicine and Rehabilitation, Indiana University School of Medicine, Indianapolis, IN. 2. Rehabilitation Hospital of Indiana, Indianapolis, IN. 3. Department of Clinical and Applied Movement Science, University of North Florida, Jacksonville, FL. 4. Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN. 5. Department of Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, IL.
Abstract
Introduction/Purpose: The amount of stepping activity during rehabilitation post-stroke can predict walking outcomes, although the most accurate methods to evaluate stepping activity are uncertain with conflicting findings on available stepping monitors during walking assessments. Rehabilitation sessions also include non-stepping activities and the ability of activity monitors to differentiate these activities from stepping is unclear. The objective of this study was to examine the accuracy of different activity monitors worn by individuals post-stroke with variable walking speeds during clinical physical therapy (PT) and research interventions focused on walking. Methods: In Part I, 28 participants post-stroke wore a StepWatch, ActiGraph with and without a Low Frequency Extension (LFE) filter, and Fitbit on paretic and non-paretic distal shanks at or above the ankle during clinical PT or research interventions with steps simultaneously hand counted. Mean absolute percent errors were compared between limbs and tasks performed. In Part II, 12 healthy adults completed 8 walking and 9 non-walking tasks observed during clinical PT or research. Data were descriptively analyzed and used to assist interpretation of Part I results. Results: Part I results indicate most devices did not demonstrate an optimal limb configuration during research sessions focused on walking, with larger errors during clinical PT on the non-paretic limb. Using the limb that minimized errors for each device, the StepWatch had smaller errors than the ActiGraph and Fitbit (p<0.01), particularly in those who walked < 0.8 m/s. Conversely, errors from the ActiGraph-LFE demonstrated inconsistent differences in step counts between Fitbit and ActiGraph. Part II results indicate that errors observed during different stepping and non-stepping activities were often device-specific, with non-stepping tasks frequently detected as stepping. Conclusions: The StepWatch and ActiGraph-LFE had smaller errors than the Fitbit or ActiGraph, with greater errors in those walking at slower speeds. Inclusion of non-stepping activities affected step counts and should be considered when measuring stepping activity in individuals post-stroke to predict locomotor outcomes following rehabilitation.
Introduction/Purpose: The amount of stepping activity during rehabilitation post-stroke can predict walking outcomes, although the most accurate methods to evaluate stepping activity are uncertain with conflicting findings on available stepping monitors during walking assessments. Rehabilitation sessions also include non-stepping activities and the ability of activity monitors to differentiate these activities from stepping is unclear. The objective of this study was to examine the accuracy of different activity monitors worn by individuals post-stroke with variable walking speeds during clinical physical therapy (PT) and research interventions focused on walking. Methods: In Part I, 28 participants post-stroke wore a StepWatch, ActiGraph with and without a Low Frequency Extension (LFE) filter, and Fitbit on paretic and non-paretic distal shanks at or above the ankle during clinical PT or research interventions with steps simultaneously hand counted. Mean absolute percent errors were compared between limbs and tasks performed. In Part II, 12 healthy adults completed 8 walking and 9 non-walking tasks observed during clinical PT or research. Data were descriptively analyzed and used to assist interpretation of Part I results. Results: Part I results indicate most devices did not demonstrate an optimal limb configuration during research sessions focused on walking, with larger errors during clinical PT on the non-paretic limb. Using the limb that minimized errors for each device, the StepWatch had smaller errors than the ActiGraph and Fitbit (p<0.01), particularly in those who walked < 0.8 m/s. Conversely, errors from the ActiGraph-LFE demonstrated inconsistent differences in step counts between Fitbit and ActiGraph. Part II results indicate that errors observed during different stepping and non-stepping activities were often device-specific, with non-stepping tasks frequently detected as stepping. Conclusions: The StepWatch and ActiGraph-LFE had smaller errors than the Fitbit or ActiGraph, with greater errors in those walking at slower speeds. Inclusion of non-stepping activities affected step counts and should be considered when measuring stepping activity in individuals post-stroke to predict locomotor outcomes following rehabilitation.
Authors: Lindsay P Toth; David R Bassett; Scott E Crouter; Brittany S Overstreet; Samuel R LaMunion; Susan Park; Shahnawaz N Notta; Cary M Springer Journal: Gait Posture Date: 2016-11-21 Impact factor: 2.840
Authors: Tryntsje Fokkema; Thea J M Kooiman; Wim P Krijnen; Cees P VAN DER Schans; Martijn DE Groot Journal: Med Sci Sports Exerc Date: 2017-04 Impact factor: 5.411
Authors: Tara D Klassen; Jennifer A Semrau; Sean P Dukelow; Mark T Bayley; Michael D Hill; Janice J Eng Journal: Stroke Date: 2017-08-07 Impact factor: 7.914
Authors: Christopher E Henderson; Megan Fahey; Gabrielle Brazg; Jennifer L Moore; T George Hornby Journal: Arch Phys Med Rehabil Date: 2020-11-20 Impact factor: 4.060