Literature DB >> 28530503

A Comparison of Self-Selected Walking Speeds and Walking Speed Variability When Data Are Collected During Repeated Discrete Trials and During Continuous Walking.

Marcus J Brown1, Laura A Hutchinson2, Michael J Rainbow2, Kevin J Deluzio2, Alan R De Asha3.   

Abstract

A typical gait analysis data collection consists of a series of discrete trials, where a participant initiates gait, walks through a motion capture volume, and then terminates gait. This is not a normal 'everyday' gait pattern, yet measurements are considered representative of normal walking. However, walking speed, a global descriptor of gait quality that can affect joint kinematics and kinetics, may be different during discrete trials, compared to continuous walking. Therefore, the purpose of this study was to investigate the effect of continuous walking versus discrete trials on walking speed and walking speed variability. Data were collected for 25 healthy young adults performing 2 walking tasks. The first task represented a typical gait data collection session, where subjects completed repeated trials, beginning from a standstill and walking along a 12-m walkway. The second task was continuous walking along a "figure-of-8" circuit, with 1 section containing the same 12-m walkway. Walking speed was significantly higher during the discrete trials compared to the continuous trials (p < .001), but there were no significant differences in walking speed variability between the conditions. The results suggest that choice of gait protocol may affect results where variables are sensitive to walking speed.

Entities:  

Keywords:  gait; methodology; walking speed

Mesh:

Year:  2017        PMID: 28530503     DOI: 10.1123/jab.2016-0355

Source DB:  PubMed          Journal:  J Appl Biomech        ISSN: 1065-8483            Impact factor:   1.833


  5 in total

1.  Normative database of spatiotemporal gait parameters using inertial sensors in typically developing children and young adults.

Authors:  Stephanie Voss; Jessica Joyce; Alexandras Biskis; Medha Parulekar; Nicholas Armijo; Cris Zampieri; Rachel Tracy; Alexandra Sasha Palmer; Marie Fefferman; Bichun Ouyang; Yuanqing Liu; Elizabeth Berry-Kravis; Joan A O'Keefe
Journal:  Gait Posture       Date:  2020-05-21       Impact factor: 2.840

2.  Machine Learning Approaches Identify Genes Containing Spatial Information From Single-Cell Transcriptomics Data.

Authors:  Phillipe Loher; Nestoras Karathanasis
Journal:  Front Genet       Date:  2021-02-01       Impact factor: 4.599

Review 3.  The Iliotibial Band: A Complex Structure with Versatile Functions.

Authors:  L A Hutchinson; G A Lichtwark; R W Willy; L A Kelly
Journal:  Sports Med       Date:  2022-01-24       Impact factor: 11.928

4.  Intra-day variation in daily outdoor walking speed among community-dwelling older adults.

Authors:  Hisashi Kawai; Shuichi Obuchi; Ryo Hirayama; Yutaka Watanabe; Hirohiko Hirano; Yoshinori Fujiwara; Kazushige Ihara; Hunkyung Kim; Yoshiyuki Kobayashi; Masaaki Mochimaru; Eiki Tsushima; Kozo Nakamura
Journal:  BMC Geriatr       Date:  2021-07-08       Impact factor: 3.921

5.  The Microsoft HoloLens 2 Provides Accurate Measures of Gait, Turning, and Functional Mobility in Healthy Adults.

Authors:  Mandy Miller Koop; Anson B Rosenfeldt; Kelsey Owen; Amanda L Penko; Matthew C Streicher; Alec Albright; Jay L Alberts
Journal:  Sensors (Basel)       Date:  2022-03-04       Impact factor: 3.576

  5 in total

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