Step-to-step variations in human running reveal how humans run without falling

Humans can run without falling down, usually despite uneven terrain or occasional pushes. Even without such external perturbations, intrinsic sources like sensorimotor noise perturb the running motion incessantly, making each step variable. Here, using simple and generalizable models, we show that e...

Full description

Bibliographic Details
Main Authors: Nidhi Seethapathi, Manoj Srinivasan
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2019-03-01
Series:eLife
Subjects:
Online Access:https://elifesciences.org/articles/38371
id doaj-72db5b195f524d89b0680a291044ffc2
record_format Article
spelling doaj-72db5b195f524d89b0680a291044ffc22021-05-05T17:29:01ZengeLife Sciences Publications LtdeLife2050-084X2019-03-01810.7554/eLife.38371Step-to-step variations in human running reveal how humans run without fallingNidhi Seethapathi0https://orcid.org/0000-0002-5159-9717Manoj Srinivasan1https://orcid.org/0000-0002-7811-3617Mechanical and Aerospace Engineering, The Ohio State University, Columbus, United States; Department of Bioengineering, University of Pennsylvania, Philadelphia, United StatesMechanical and Aerospace Engineering, The Ohio State University, Columbus, United StatesHumans can run without falling down, usually despite uneven terrain or occasional pushes. Even without such external perturbations, intrinsic sources like sensorimotor noise perturb the running motion incessantly, making each step variable. Here, using simple and generalizable models, we show that even such small step-to-step variability contains considerable information about strategies used to run stably. Deviations in the center of mass motion predict the corrective strategies during the next stance, well in advance of foot touchdown. Horizontal motion is stabilized by total leg impulse modulations, whereas the vertical motion is stabilized by differentially modulating the impulse within stance. We implement these human-derived control strategies on a simple computational biped, showing that it runs stably for hundreds of steps despite incessant noise-like perturbations or larger discrete perturbations. This running controller derived from natural variability echoes behaviors observed in previous animal and robot studies.https://elifesciences.org/articles/38371human runninglocomotionmotor controlstabilityneuromechanicsbio-inspired control
collection DOAJ
language English
format Article
sources DOAJ
author Nidhi Seethapathi
Manoj Srinivasan
spellingShingle Nidhi Seethapathi
Manoj Srinivasan
Step-to-step variations in human running reveal how humans run without falling
eLife
human running
locomotion
motor control
stability
neuromechanics
bio-inspired control
author_facet Nidhi Seethapathi
Manoj Srinivasan
author_sort Nidhi Seethapathi
title Step-to-step variations in human running reveal how humans run without falling
title_short Step-to-step variations in human running reveal how humans run without falling
title_full Step-to-step variations in human running reveal how humans run without falling
title_fullStr Step-to-step variations in human running reveal how humans run without falling
title_full_unstemmed Step-to-step variations in human running reveal how humans run without falling
title_sort step-to-step variations in human running reveal how humans run without falling
publisher eLife Sciences Publications Ltd
series eLife
issn 2050-084X
publishDate 2019-03-01
description Humans can run without falling down, usually despite uneven terrain or occasional pushes. Even without such external perturbations, intrinsic sources like sensorimotor noise perturb the running motion incessantly, making each step variable. Here, using simple and generalizable models, we show that even such small step-to-step variability contains considerable information about strategies used to run stably. Deviations in the center of mass motion predict the corrective strategies during the next stance, well in advance of foot touchdown. Horizontal motion is stabilized by total leg impulse modulations, whereas the vertical motion is stabilized by differentially modulating the impulse within stance. We implement these human-derived control strategies on a simple computational biped, showing that it runs stably for hundreds of steps despite incessant noise-like perturbations or larger discrete perturbations. This running controller derived from natural variability echoes behaviors observed in previous animal and robot studies.
topic human running
locomotion
motor control
stability
neuromechanics
bio-inspired control
url https://elifesciences.org/articles/38371
work_keys_str_mv AT nidhiseethapathi steptostepvariationsinhumanrunningrevealhowhumansrunwithoutfalling
AT manojsrinivasan steptostepvariationsinhumanrunningrevealhowhumansrunwithoutfalling
_version_ 1721459205850791936