Literature DB >> 29049964

The bit doesn't fit: Evaluation of a commercial activity-tracker at slower walking speeds.

Christopher K Wong1, Helena M Mentis2, Ravi Kuber3.   

Abstract

Accelerometer-based commercial activity trackers are a low-cost and convenient method for monitoring and assessing health measures such as gait. However, the accuracy of these activity trackers in slow walking conditions on a minute-by-minute basis is largely unknown. In this study, the accuracy of a hip-worn commercial activity tracker (FitBit Ultra) was examined through step counts. Accuracy was evaluated through four minute trials of treadmill walking at speeds representative of older adults (0.9, 1.1, and 1.3m/s). Minute-by-minute step count was extracted through the FitBit API and compared it to observer counted steps through video recordings. Results highlighted a significant over-reporting of steps at the highest speed, and a significant under-reporting of steps at the slowest speed, with the FitBit Ultra failing to count steps for one or more minutes at the slowest speed for 11 participants. This study highlights problems with using the FitBit Ultra by slow-walking populations, and recommends that researchers and clinicians should carefully consider the trade-off between accuracy and convenience when using commercial activity trackers with slow-walking populations.
Copyright © 2017. Published by Elsevier B.V.

Entities:  

Keywords:  Accelerometers; FitBit; Older adults; Step count; Walking speed

Mesh:

Year:  2017        PMID: 29049964     DOI: 10.1016/j.gaitpost.2017.10.010

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  12 in total

1.  Accuracy and Acceptability of Commercial-Grade Physical Activity Monitors in Older Adults.

Authors:  Andrea L Hergenroeder; Bethany Barone Gibbs; Mary P Kotlarczyk; Subashan Perera; Robert J Kowalsky; Jennifer S Brach
Journal:  J Aging Phys Act       Date:  2018-11-21       Impact factor: 1.961

2.  Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor.

Authors:  Mst Alema Khatun; Mohammad Abu Yousuf; Sabbir Ahmed; Md Zia Uddin; Salem A Alyami; Samer Al-Ashhab; Hanan F Akhdar; Asaduzzaman Khan; Akm Azad; Mohammad Ali Moni
Journal:  IEEE J Transl Eng Health Med       Date:  2022-05-25

Review 3.  Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data.

Authors:  Lynne M Feehan; Jasmina Geldman; Eric C Sayre; Chance Park; Allison M Ezzat; Ju Young Yoo; Clayon B Hamilton; Linda C Li
Journal:  JMIR Mhealth Uhealth       Date:  2018-08-09       Impact factor: 4.773

4.  Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults.

Authors:  Salvatore Tedesco; Marco Sica; Andrea Ancillao; Suzanne Timmons; John Barton; Brendan O'Flynn
Journal:  PLoS One       Date:  2019-05-21       Impact factor: 3.240

5.  Activity monitor use among persons with multiple sclerosis: Report on rate, pattern, and association with physical activity levels.

Authors:  Stephanie L Silveira; Robert W Motl
Journal:  Mult Scler J Exp Transl Clin       Date:  2019-11-09

6.  Step and Distance Measurement From a Low-Cost Consumer-Based Hip and Wrist Activity Monitor: Protocol for a Validity and Reliability Assessment.

Authors:  Thomas Carlin; Nicolas Vuillerme
Journal:  JMIR Res Protoc       Date:  2021-01-13

7.  Validity of Consumer Activity Monitors and an Algorithm Using Smartphone Data for Measuring Steps during Different Activity Types.

Authors:  Verena Hartung; Mustafa Sarshar; Viktoria Karle; Layal Shammas; Asarnusch Rashid; Paul Roullier; Caroline Eilers; Mathias Mäurer; Peter Flachenecker; Klaus Pfeifer; Alexander Tallner
Journal:  Int J Environ Res Public Health       Date:  2020-12-12       Impact factor: 3.390

8.  Free-Living Physical Activity Monitoring in Adult US Patients with Multiple Sclerosis Using a Consumer Wearable Device.

Authors:  Pronabesh DasMahapatra; Emil Chiauzzi; Rishi Bhalerao; Jane Rhodes
Journal:  Digit Biomark       Date:  2018-04-13

9.  Assessment of Physical Activity by Wearable Technology During Rehabilitation After Cardiac Surgery: Explorative Prospective Monocentric Observational Cohort Study.

Authors:  Isabeau Thijs; Libera Fresiello; Wouter Oosterlinck; Peter Sinnaeve; Filip Rega
Journal:  JMIR Mhealth Uhealth       Date:  2019-01-31       Impact factor: 4.773

10.  Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review.

Authors:  Daniel Fuller; Emily Colwell; Jonathan Low; Kassia Orychock; Melissa Ann Tobin; Bo Simango; Richard Buote; Desiree Van Heerden; Hui Luan; Kimberley Cullen; Logan Slade; Nathan G A Taylor
Journal:  JMIR Mhealth Uhealth       Date:  2020-09-08       Impact factor: 4.773

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