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Cited by 182Physical Activity and HealthContext-Aware Activity Recognition SystemsStroke Rehabilitation and Recovery

Accuracy of 2 Activity Monitors in Detecting Steps in People With Stroke and Traumatic Brain Injury

Fulk, George D., Combs, Stephanie A., Danks, Kelly A., Nirider, Coby D., Raja, Bhavana, Reisman, Darcy S.·2014·Physical Therapy
DOI 10.2522/ptj.20120525
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Abstract

Background: Advances in sensor technologies and signal processing techniques provide a method to accurately measure walking activity in the home and community. Activity monitors geared toward consumer or patient use may be an alternative to more expensive monitors designed for research to measure stepping activity. Objective: The objective of this study was to examine the accuracy of 2 consumer/patient activity monitors, the Fitbit Ultra and the Nike+ Fuelband, in identifying stepping activity in people with stroke and traumatic brain injury (TBI). Secondarily, the study sought to compare the accuracy of these 2 activity monitors with that of the StepWatch Activity Monitor (SAM) and a pedometer, the Yamax Digi-Walker SW-701 pedometer (YDWP). Design: A cross-sectional design was used for this study. Method: People with chronic stroke and TBI wore the 4 activity monitors while they performed the Two-Minute Walk Test (2MWT), during which they were videotaped. Activity monitor estimated steps taken were compared with actual steps taken counted from videotape. Accuracy and agreement between activity monitor estimated steps and actual steps were examined using intraclass correlation coefficients (ICC [2,1]) and the Bland-Altman method. Results: The SAM demonstrated the greatest accuracy (ICC [2,1]=.97, mean difference between actual steps and SAM estimated steps=4.7 steps) followed by the Fitbit Ultra (ICC [2,1]=.73, mean difference between actual steps and Fitbit Ultra estimated steps=−9.7 steps), the YDWP (ICC [2,1]=.42, mean difference between actual steps and YDWP estimated steps=−28.8 steps), and the Nike+ Fuelband (ICC [2,1]=.20, mean difference between actual steps and Nike+ Fuelband estimated steps=−66.2 steps). Limitations: Walking activity was measured over a short distance in a closed environment, and participants were high functioning ambulators, with a mean gait speed of 0.93 m/s. Conclusions: The Fitbit Ultra may be a low-cost alternative to measure the stepping activity in level, predictable environments of people with stroke and TBI who can walk at speeds ≥0.58 m/s.

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Authors
Fulk, G. D., Combs, S. A., Danks, K. A., Nirider, C. D., Raja, B., & Reisman, D. S.
Affiliations
  • Clarkson University (US)
  • University of Indianapolis (US)
  • University of Delaware (US)
  • C.D. Nirider, PT, DPT, Touchstone Neurorecovery Center, Conroe, Texas.
  • Western University of Health Sciences (US)
Corresponding author
Fulk, George D.
ORCID
Venue
Physical Therapy
Publisher
Oxford University Press (OUP)
Published
2014-02-01
Volume
94
Issue
2
Pages
222-229
ISSN
  • 0031-9023 (ISSN-L)
  • 1538-6724
DOI
10.2522/ptj.20120525
OpenAlex
W2110108424
Cited by
182
References
51
Citations by year
2026: 5 · 2025: 7 · 2024: 7 · 2023: 4 · 2022: 11 · 2021: 17 · 2020: 23 · 2019: 20 · 2018: 23 · 2017: 26 · 2016: 20 · 2015: 14 · 2014: 5
FWCI
9.03
Type
journal article
Language
en
Open access
closed
Locations
  • Physical Therapy (publishedVersion)
  • PubMed (publishedVersion)
  • Scholarly Commons (University of the Pacific) (submittedVersion)
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
Keywords
wearable activity trackers, step count accuracy, stroke, traumatic brain injury, pedometers, consumer wearable devices, 2-minute walk test, walking speed
MeSH terms
Brain Injuries, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, United States, Videotape Recording, Monitoring, Ambulatory, Gait Disorders, Neurologic, Stroke

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