Evidence map›Paper›PMID 31159376›Full record

Trial reportSensors (Basel, Switzerland)2019

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?

Nizam U Ahamed, Lauren C Benson, Christian A Clermont, Andrew J Pohl, Reed Ferber

Abstract readClinical Trial
In one paragraph

Trial report in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nizam U AhamedFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada. nizam.ahamed1@ucalgary.ca.ORCID 0000-0003-0497-7356
Lauren C BensonFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada. lauren.benson@ucalgary.ca.ORCID 0000-0002-7526-273X
Christian A ClermontFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada. christian.clermont@ucalgary.ca.ORCID 0000-0002-4486-2062
Andrew J PohlFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada. andrew.pohl@ucalgary.ca.ORCID 0000-0002-2834-9058
Reed FerberFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada. rferber@ucalgary.ca.ORCID 0000-0002-6154-9115

Funding

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada #I2IPJ 493875-16
6 · The paper itself

Abstract

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.

Indexed as

Wearable Electronic DevicesAdultBiomechanical PhenomenaBiosensing TechniquesFemaleGaitHumansMaleMiddle AgedPelvisaccelerometerelevationgaitinertial measurement unitrunningslope

Identifiers

PMID31159376
PMCPMC6603692

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.