» Articles » PMID: 33464213

Physical Activity Monitoring Using a Fitbit Device in Ischemic Stroke Patients: Prospective Cohort Feasibility Study

Overview
Date 2021 Jan 19
PMID 33464213
Citations 16
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Continuous tracking of ambulatory activity in real-world settings using step activity monitors has many potential uses. However, feasibility, accuracy, and correlation with performance measures in stroke patients have not been well-established.

Objective: The primary study objective was to determine adherence with wearing a consumer-grade step activity monitor, the Fitbit Charge HR, in home-going ischemic stroke patients during the first 90 days after hospital discharge. Secondary objectives were to (1) determine accuracy of step counts of the Fitbit Charge HR compared with a manual tally; (2) calculate correlations between the Fitbit step counts and the mobility performance scores at discharge and 30 days after stroke; (3) determine variability and change in weekly step counts over 90 days; and (4) evaluate patient experience with using the Fitbit Charge HR poststroke.

Methods: A total of 15 participants with recent mild ischemic stroke wore a Fitbit Charge HR for 90 days after discharge and completed 3 mobility performance tests from the National Institutes of Health Toolbox at discharge and Day 30: (1) Standing Balance Test, (2) 2-Minute Walk Endurance Test, and (3) 4-Meter Walk Gait Speed Test. Accuracy of step activity monitors was assessed by calculating differences in steps recorded on the step activity monitor and a manual tally during 2-minute walk tests.

Results: Participants had a mean age of 54 years and a median modified Rankin scale score of 1. Mean daily adherence with step activity monitor use was 83.6%. Mean daily step count in the first week after discharge was 4376. Daily step counts increased slightly during the first 30 days after discharge (average increase of 52.5 steps/day; 95% CI 32.2-71.8) and remained stable during the 30-90 day period after discharge. Mean step count difference between step activity monitor and manual tally was -4.8 steps (-1.8%). Intraclass correlation coefficients for step counts and 2-minute walk, standing balance, and 4-meter gait speed at discharge were 0.41 (95% CI -0.14 to 0.75), -0.12 (95% CI -0.67 to 0.64), and 0.17 (95% CI -0.46 to 0.66), respectively. Values were similarly poor at 30 days.

Conclusions: The use of consumer-grade Fitbit Charge HR in patients with recent mild stroke is feasible with reasonable adherence and accuracy. There was poor correlation between step counts and gait speed, balance, and endurance. Further research is needed to evaluate the association between step counts and other outcomes relevant to patients, including patient-reported outcomes and measures of physical function.

Citing Articles

Wearable Smartphone-Based Multisensory Feedback System for Torso Posture Correction: Iterative Design and Within-Subjects Study.

Pereira A, Machado Neto O, Elui V, Pimentel M JMIR Aging. 2025; 8:e55455.

PMID: 39841997 PMC: 11809616. DOI: 10.2196/55455.


Use of commercially available wearable devices for physical rehabilitation in healthcare: a systematic review.

Latif A, Al Janabi H, Joshi M, Fusari G, Shepherd L, Darzi A BMJ Open. 2024; 14(11):e084086.

PMID: 39515863 PMC: 11552580. DOI: 10.1136/bmjopen-2024-084086.


Impact of automated data flow and reminders on adherence and resource utilization for remotely monitoring physical activity in individuals with stroke or chronic obstructive pulmonary disease.

French M, Balasubramanian A, Hansel N, Penttinen S, Wise R, Raghavan P medRxiv. 2024; .

PMID: 38699312 PMC: 11064997. DOI: 10.1101/2024.04.15.24305852.


Exploring the Major Barriers to Physical Activity in Persons With Multiple Sclerosis: Observational Longitudinal Study.

Sieber C, Haag C, Polhemus A, Haile S, Sylvester R, Kool J JMIR Rehabil Assist Technol. 2024; 11:e52733.

PMID: 38498024 PMC: 10985607. DOI: 10.2196/52733.


Sequential multiple assignment randomised trial to develop an adaptive mobile health intervention to increase physical activity in people poststroke in the community setting in Ireland: TAPAS trial protocol.

Carr E, Whiston A, OReilly S, O Donoghue M, Cardy N, Carter D BMJ Open. 2024; 14(1):e072811.

PMID: 38238182 PMC: 10806784. DOI: 10.1136/bmjopen-2023-072811.


References
1.
Bland J, Altman D . Agreement between methods of measurement with multiple observations per individual. J Biopharm Stat. 2007; 17(4):571-82. DOI: 10.1080/10543400701329422. View

2.
Van der Walt N, Salmon L, Gooden B, Lyons M, OSullivan M, Martina K . Feedback From Activity Trackers Improves Daily Step Count After Knee and Hip Arthroplasty: A Randomized Controlled Trial. J Arthroplasty. 2018; 33(11):3422-3428. DOI: 10.1016/j.arth.2018.06.024. View

3.
Lord S, McPherson K, McNaughton H, Rochester L, Weatherall M . Community ambulation after stroke: how important and obtainable is it and what measures appear predictive?. Arch Phys Med Rehabil. 2004; 85(2):234-9. DOI: 10.1016/j.apmr.2003.05.002. View

4.
Piwek L, Ellis D, Andrews S, Joinson A . The Rise of Consumer Health Wearables: Promises and Barriers. PLoS Med. 2016; 13(2):e1001953. PMC: 4737495. DOI: 10.1371/journal.pmed.1001953. View

5.
Rowe D, Kemble C, Robinson T, Mahar M . Daily walking in older adults: day-to-day variability and criterion-referenced validity of total daily step counts. J Phys Act Health. 2008; 4(4):434-46. View