Literature DB >> 30693580

Shoe-mounted accelerometers should be used with caution in gait retraining.

Roy T H Cheung1, Janet H Zhang1, Zoe Y S Chan1, Winko W An2, Ivan P H Au1, Aislinn MacPhail1, Irene S Davis3.   

Abstract

Real-time biofeedback gait retraining has been reported to be an effective intervention to lower the impact loading during gait. While many of the previous gait retraining studies have utilized a laboratory-based setup, some studies used accelerometers affixed at the distal tibia to allow training outside the laboratory environment. However, many commercial sensors for gait modification are shoe-mounted. Hence, this study sought to compare impact loading parameters measured by shoe-mounted and tibia sensors in participants before and after a course of walking or running retraining using signal source from the shoe-mounted sensors. We also compared the correlations between peak positive acceleration measured at shoe (PPAS ) and tibia (PPAT ) and vertical loading rates, as these loading rates have been related to injury. Twenty-four and 14 participants underwent a 2-week visual biofeedback walking and running retraining, respectively. Participants in the walking retraining group experienced lower PPAS following the intervention (P < 0.005). However, they demonstrated no change in PPAT (P = 0.409) nor vertical loading rates (P > 0.098) following the walking retraining. In contrast, participants in the running retraining group experienced a reduction in the PPAT (P = 0.001) and vertical loading rates (P < 0.013) after running retraining. PPAS values were four times that of PPAT for both walking and running suggesting an uncoupling of the shoe with tibia. As such, PPAS was not correlated with vertical loading rates for either walking or running, while significant correlations between PPAT and vertical loading rates were noted. The present study suggests potential limitations of the existing commercial shoe-mounted sensors.
© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  kinetics; running; walking; wearable sensor

Mesh:

Year:  2019        PMID: 30693580     DOI: 10.1111/sms.13396

Source DB:  PubMed          Journal:  Scand J Med Sci Sports        ISSN: 0905-7188            Impact factor:   4.221


  8 in total

1.  Wearables for Running Gait Analysis: A Systematic Review.

Authors:  Rachel Mason; Liam T Pearson; Gillian Barry; Fraser Young; Oisin Lennon; Alan Godfrey; Samuel Stuart
Journal:  Sports Med       Date:  2022-10-15       Impact factor: 11.928

Review 2.  The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review.

Authors:  Ezio Preatoni; Elena Bergamini; Silvia Fantozzi; Lucie I Giraud; Amaranta S Orejel Bustos; Giuseppe Vannozzi; Valentina Camomilla
Journal:  Sensors (Basel)       Date:  2022-04-22       Impact factor: 3.847

3.  Estimating Lower Extremity Running Gait Kinematics with a Single Accelerometer: A Deep Learning Approach.

Authors:  Mohsen Gholami; Christopher Napier; Carlo Menon
Journal:  Sensors (Basel)       Date:  2020-05-22       Impact factor: 3.576

4.  Effects of Wearable Devices with Biofeedback on Biomechanical Performance of Running-A Systematic Review.

Authors:  Alexandra Giraldo-Pedroza; Winson Chiu-Chun Lee; Wing-Kai Lam; Robyn Coman; Gursel Alici
Journal:  Sensors (Basel)       Date:  2020-11-19       Impact factor: 3.576

5.  Foot Strike Angle Prediction and Pattern Classification Using LoadsolTM Wearable Sensors: A Comparison of Machine Learning Techniques.

Authors:  Stephanie R Moore; Christina Kranzinger; Julian Fritz; Thomas Stӧggl; Josef Krӧll; Hermann Schwameder
Journal:  Sensors (Basel)       Date:  2020-11-25       Impact factor: 3.576

6.  Differences in Peak Impact Accelerations Among Foot Strike Patterns in Recreational Runners.

Authors:  Christopher Napier; Lauren Fridman; Paul Blazey; Nicholas Tran; Tom V Michie; Amy Schneeberg
Journal:  Front Sports Act Living       Date:  2022-03-04

7.  Validation of the RunScribe inertial measurement unit for walking gait measurement.

Authors:  Max Lewin; Carina Price; Christopher Nester
Journal:  PLoS One       Date:  2022-08-22       Impact factor: 3.752

Review 8.  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

  8 in total

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