Original articleThe Use of Pedometers in Stroke Survivors: Are They Feasible and How Well Do They Detect Steps?
Section snippets
Methods
Ethical approval was from South East Scotland Research Ethics Committee 01.
Results
Fifty-one (76%) of 67 eligible patients agreed to participate, 1 of whom was unable to perform the walks safely and was excluded (table 1).
Discussion
To our knowledge, this is the first study in stroke patients to systematically record the feasibility of pedometers and to explore the influence of pedometer position on step count recordings, and it is the largest study to determine agreement between the pedometer step counts and a criterion standard measure of step count. Most patients correctly read step counts, all patients could take pedometers off, and only 5 (10%) needed help putting them on. Most would be willing to use pedometers again.
Conclusions
This study has shown that pedometers are feasible for use in ambulatory stroke patients. However, below a gait speed of 0.5m/s, agreement between the pedometer step count and the video-recorded step count is low, with many pedometers not detecting any steps. We are now developing a behavioral change intervention to increase physical activity after stroke, using a pedometer to provide feedback on step count, but restricting this intervention to patients with gait speeds of greater than 0.5m/s.
Acknowledgments
We thank the clinicians who helped with recruitment.
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2020, Annals of Physical and Rehabilitation MedicineCitation Excerpt :The heterogeneity of our population could affect the accuracy of the Actigraph GT3x. The low accuracy may be related to low walking speeds, as described [33]. The Actigraph GT3x may have provided more accurate results in a more homogeneous population, especially in participants with faster walking speeds.
Big data vs accurate data in health research: Large-scale physical activity monitoring, smartphones, wearable devices and risk of unconscious bias
2018, Medical HypothesesCitation Excerpt :Compared to laboratory gait, in the free-living context, people walk significantly slower and with more variability [18]. The step counting errors observed in laboratory settings [14–17] may further increase for remote-monitoring scenarios because in the real-world people walk with both slow and fast cadences (according to bimodal distributions) and complete far more short walks than long walks [20]. Across the global population (with its inherent variability) smartphone apps that have been designed for the average consumer are therefore unlikely to provide a valid and unbiased instrument for the scientific monitoring of physical activity [15].
Supported by The Chief Scientist Office, Scottish Government (ref no. CZG/2/428) and by the Scottish Stroke Research Network.
No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated.