New Considerations for Collecting Biomechanical Data Using Wearable Sensors: How Does Inclination Influence the Number of Runs Needed to Determine a Stable Running Gait Pattern? Article Swipe
Nizam Uddin Ahamed
,
Lauren C. Benson
,
Christian A. Clermont
,
Andrew J. Pohl
,
Reed Ferber
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/s19112516
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/s19112516
As inertial measurement units (IMUs) are used to capture gait data in real-world environments, guidelines are required in order to determine a ‘typical’ or ‘stable’ gait pattern across multiple days of data collection. Since uphill and downhill running can greatly affect the biomechanics of running gait, this study sought to determine the number of runs needed to establish a stable running pattern during level, downhill, and uphill conditions for both univariate and multivariate analyses of running biomechanical data collected using a single wearable IMU device. Pelvic drop, ground contact time, braking, vertical oscillation, pelvic rotation, and cadence, were recorded from thirty-five recreational runners running in three elevation conditions: level, downhill, and uphill. Univariate and multivariate normal distributions were estimated from differing numbers of runs and stability was defined when the addition of a new run resulted in less than a 5% change in the 2.5 and 97.5 quantiles of the 95% probability density function for each individual runner. This stability point was determined separately for each runner and each IMU variable (univariate and multivariate). The results showed that 2–4 runs were needed to define a stable running pattern for univariate, and 4–5 days were necessary for multivariate analysis across all inclination conditions. Pearson’s correlation coefficients were calculated to cross-validate differing elevation conditions and showed excellent correlations (r = 0.98 to 1.0) comparing the training and testing data within the same elevation condition and good to very good correlations (r = 0.63–0.88) when comparing training and testing data from differing elevation conditions. These results suggest that future research involving wearable technology should collect multiple days of data in order to build reliable and accurate representations of an individual’s stable gait pattern.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s19112516
- https://www.mdpi.com/1424-8220/19/11/2516/pdf?version=1559370450
- OA Status
- gold
- Cited By
- 14
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2947292774
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2947292774Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s19112516Digital Object Identifier
- Title
-
New Considerations for Collecting Biomechanical Data Using Wearable Sensors: How Does Inclination Influence the Number of Runs Needed to Determine a Stable Running Gait Pattern?Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-06-01Full publication date if available
- Authors
-
Nizam Uddin Ahamed, Lauren C. Benson, Christian A. Clermont, Andrew J. Pohl, Reed FerberList of authors in order
- Landing page
-
https://doi.org/10.3390/s19112516Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/19/11/2516/pdf?version=1559370450Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/19/11/2516/pdf?version=1559370450Direct OA link when available
- Concepts
-
Wearable computer, Gait, Computer science, Wearable technology, Physical medicine and rehabilitation, Gait analysis, Simulation, Medicine, Embedded systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
14Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2023: 3, 2022: 4, 2021: 2, 2020: 1Per-year citation counts (last 5 years)
- References (count)
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31Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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