Literature DB >> 27131177

Comparison of the correlations between impact loading rates and peak accelerations measured at two different body sites: Intra- and inter-subject analysis.

Janet H Zhang1, Winko W An2, Ivan P H Au2, Tony L Chen3, Roy T H Cheung2.   

Abstract

BACKGROUND: High average (VALR) and instantaneous vertical loading rates (VILR) during impact have been associated with many running-related injuries. Peak acceleration (PA), measured with an accelerometer, has provided an alternative method to estimate impact loading during outdoor running. This study sought to compare both intra- and inter-subject correlations between vertical loading rates and PA measured at two body sites during running.
METHODS: Ground reaction force data were collected from 10 healthy adults (age=23.6±3.8 years) during treadmill running at different speeds and inclination surfaces. Concurrently, PAs at the lateral malleoli and the distal tibia were measured using synchronized accelerometers.
RESULTS: We found significant positive intra-subject correlation between loading rates and PA at the lateral malleoli (r=0.561-0.950, p<0.001) and the distal tibia (r=0.486-0.913, p<0.001). PA measured at the lateral malleoli showed stronger correlation with loading rates (p=0.004) than the measurement at the distal tibia. On the other hand, inter-subject variances were observed in the association between PA and vertical loading rates. The inter-subject variances at the distal tibia were 3.88±3.09BW/s and 5.69±3.05BW/s in VALR and VLIR respectively. Similarly, the inter-subject variances in the measurement at lateral malleoli were 5.24±2.85BW/s and 6.67±2.83BW/s in VALR and VLIR respectively.
CONCLUSIONS: PA measured at lateral malleoli has stronger correlation with VALR or VILR than the measurement at distal tibia. Caution is advised when using PA to conduct inter-subject comparisons of vertical loading rates during running.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Between-subject; Body-worn sensors; Variance; Within-subject

Mesh:

Year:  2016        PMID: 27131177     DOI: 10.1016/j.gaitpost.2016.02.002

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


  3 in total

1.  Measurement agreement between a newly developed sensing insole and traditional laboratory-based method for footstrike pattern detection in runners.

Authors:  Roy T H Cheung; Winko W An; Ivan P H Au; Janet H Zhang; Zoe Y S Chan; Alfred Man; Fannie O Y Lau; Melody K Y Lam; K K Lau; C Y Leung; N W Tsang; Louis K Y Sze; Gilbert W K Lam
Journal:  PLoS One       Date:  2017-06-09       Impact factor: 3.240

2.  A machine learning approach to identify risk factors for running-related injuries: study protocol for a prospective longitudinal cohort trial.

Authors:  A L Rahlf; T Hoenig; J Stürznickel; K Cremans; D Fohrmann; A Sanchez-Alvarado; T Rolvien; K Hollander
Journal:  BMC Sports Sci Med Rehabil       Date:  2022-04-26

Review 3.  Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis.

Authors:  Lauren C Benson; Anu M Räisänen; Christian A Clermont; Reed Ferber
Journal:  Sensors (Basel)       Date:  2022-02-23       Impact factor: 3.576

  3 in total

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