Literature DB >> 33439858

Human walking in the real world: Interactions between terrain type, gait parameters, and energy expenditure.

Daniel B Kowalsky1, John R Rebula1, Lauro V Ojeda1, Peter G Adamczyk2, Arthur D Kuo1,3.   

Abstract

Humans often traverse real-world environments with a variety of surface irregularities and inconsistencies, which can disrupt steady gait and require additional effort. Such effects have, however, scarcely been demonstrated quantitatively, because few laboratory biomechanical measures apply outdoors. Walking can nevertheless be quantified by other means. In particular, the foot's trajectory in space can be reconstructed from foot-mounted inertial measurement units (IMUs), to yield measures of stride and associated variabilities. But it remains unknown whether such measures are related to metabolic energy expenditure. We therefore quantified the effect of five different outdoor terrains on foot motion (from IMUs) and net metabolic rate (from oxygen consumption) in healthy adults (N = 10; walking at 1.25 m/s). Energy expenditure increased significantly (P < 0.05) in the order Sidewalk, Dirt, Gravel, Grass, and Woodchips, with Woodchips about 27% costlier than Sidewalk. Terrain type also affected measures, particularly stride variability and virtual foot clearance (swing foot's lowest height above consecutive footfalls). In combination, such measures can also roughly predict metabolic cost (adjusted R2 = 0.52, partial least squares regression), and even discriminate between terrain types (10% reclassification error). Body-worn sensors can characterize how uneven terrain affects gait, gait variability, and metabolic cost in the real world.

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Year:  2021        PMID: 33439858      PMCID: PMC7806134          DOI: 10.1371/journal.pone.0228682

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  32 in total

1.  Metabolic energy expenditure and terrain coefficients for walking on snow.

Authors:  K B Pandolf; M F Haisman; R F Goldman
Journal:  Ergonomics       Date:  1976-11       Impact factor: 2.778

Review 2.  Energetic consequences of walking like an inverted pendulum: step-to-step transitions.

Authors:  Arthur D Kuo; J Maxwell Donelan; Andy Ruina
Journal:  Exerc Sport Sci Rev       Date:  2005-04       Impact factor: 6.230

3.  The advantages of a rolling foot in human walking.

Authors:  Peter G Adamczyk; Steven H Collins; Arthur D Kuo
Journal:  J Exp Biol       Date:  2006-10       Impact factor: 3.312

4.  A novel method for using accelerometer data to predict energy expenditure.

Authors:  Scott E Crouter; Kurt G Clowers; David R Bassett
Journal:  J Appl Physiol (1985)       Date:  2005-12-01

5.  Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Authors:  Benoit Mariani; Stephane Rochat; Christophe J Büla; Kamiar Aminian
Journal:  IEEE Trans Biomed Eng       Date:  2012-09-04       Impact factor: 4.538

6.  Predicting walking METs and energy expenditure from speed or accelerometry.

Authors:  Anthony G Brooks; Simon M Gunn; Robert T Withers; Christopher J Gore; John L Plummer
Journal:  Med Sci Sports Exerc       Date:  2005-07       Impact factor: 5.411

7.  Active control of lateral balance in human walking.

Authors:  C E Bauby; A D Kuo
Journal:  J Biomech       Date:  2000-11       Impact factor: 2.712

8.  Kinematic strategies for walking across a destabilizing rock surface.

Authors:  Deanna H Gates; Jason M Wilken; Shawn J Scott; Emily H Sinitski; Jonathan B Dingwell
Journal:  Gait Posture       Date:  2011-09-03       Impact factor: 2.840

9.  Mechanical work for step-to-step transitions is a major determinant of the metabolic cost of human walking.

Authors:  J Maxwell Donelan; Rodger Kram; Arthur D Kuo
Journal:  J Exp Biol       Date:  2002-12       Impact factor: 3.312

10.  Mechanics and energetics of human locomotion on sand.

Authors:  T M Lejeune; P A Willems; N C Heglund
Journal:  J Exp Biol       Date:  1998-07       Impact factor: 3.312

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  2 in total

1.  Humans optimally anticipate and compensate for an uneven step during walking.

Authors:  Osman Darici; Arthur D Kuo
Journal:  Elife       Date:  2022-01-11       Impact factor: 8.140

2.  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

  2 in total

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