Literature DB >> 23679899

An evaluation of inertial sensor technology in the discrimination of human gait.

Chris Little1, James Bruce Lee, Daniel A James, Kade Davison.   

Abstract

Inertial sensors may provide the opportunity for broader and more cost effective gait analysis; however some questions remain over their potential use in this capacity. The aim of the study was to determine whether an inertial sensor could discriminate between normal walking, fast walking, and running. A single group crossover design was used to compare acceleration profiles between three gait conditions: normal walking, fast walking, and running. An inertial sensor was placed on the sacrum of 12 participants (6 male, 6 female) who performed 3 trials of each gait condition on both overground and treadmill settings. A significant difference (P < 0.001) in the occurrence of heel strike in the gait cycle was found between running and both walking conditions. No differences were seen between overground and treadmill in any condition or variable. The results indicate that a single sacral mounted inertial sensor can differentiate running from normal walking and fast walking using temporal gait event measures. This study indicates that inertial sensors can differentiate walking from running gait in healthy individuals which may have potential for application in the quantification of physical activity in the health and exercise industry.

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Mesh:

Year:  2013        PMID: 23679899     DOI: 10.1080/02640414.2013.779739

Source DB:  PubMed          Journal:  J Sports Sci        ISSN: 0264-0414            Impact factor:   3.337


  6 in total

Review 1.  Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review.

Authors:  Valentina Camomilla; Elena Bergamini; Silvia Fantozzi; Giuseppe Vannozzi
Journal:  Sensors (Basel)       Date:  2018-03-15       Impact factor: 3.576

2.  IART: Inertial Assistant Referee and Trainer for Race Walking.

Authors:  Teodorico Caporaso; Stanislao Grazioso
Journal:  Sensors (Basel)       Date:  2020-01-31       Impact factor: 3.576

3.  Translational Applications of Wearable Sensors in Education: Implementation and Efficacy.

Authors:  Brendon Ferrier; Jim Lee; Alex Mbuli; Daniel A James
Journal:  Sensors (Basel)       Date:  2022-02-21       Impact factor: 3.576

4.  Detection of illegal race walking: a tool to assist coaching and judging.

Authors:  James B Lee; Rebecca B Mellifont; Brendan J Burkett; Daniel A James
Journal:  Sensors (Basel)       Date:  2013-11-26       Impact factor: 3.576

5.  Ground reaction force estimates from ActiGraph GT3X+ hip accelerations.

Authors:  Jennifer M Neugebauer; Kelsey H Collins; David A Hawkins
Journal:  PLoS One       Date:  2014-06-10       Impact factor: 3.240

6.  On-Body Sensor Positions Hierarchical Classification.

Authors:  Vu Ngoc Thanh Sang; Shiro Yano; Toshiyuki Kondo
Journal:  Sensors (Basel)       Date:  2018-10-24       Impact factor: 3.576

  6 in total

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