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Related Experiment Video

Updated: May 23, 2026

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance
07:19

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance

Published on: March 19, 2020

Balancing on tightropes and slacklines.

P Paoletti1, L Mahadevan

  • 1School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.

Journal of the Royal Society, Interface
|April 20, 2012
PubMed
Summary
This summary is machine-generated.

Balancing on a rope requires minimal effort at an optimal rope sag, a finding from a new neuromechanical model. This research suggests strategies for improving human balance control during activities like walking.

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Screening People on Standing Balance with Romberg Testing and Walking Balance with Tandem Walking
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Last Updated: May 23, 2026

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance
07:19

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance

Published on: March 19, 2020

Screening People on Standing Balance with Romberg Testing and Walking Balance with Tandem Walking
06:28

Screening People on Standing Balance with Romberg Testing and Walking Balance with Tandem Walking

Published on: September 1, 2023

Area of Science:

  • Neuromechanics
  • Biomechanics
  • Control Theory

Background:

  • Human balance involves complex neuromechanical interactions with the environment.
  • Previous studies lack a unified model for balancing on dynamic surfaces.

Purpose of the Study:

  • To develop a minimal neuromechanical model for balancing on a rope or slackline.
  • To design an optimal control strategy for maintaining upright posture.

Main Methods:

  • Formulation of a minimal neuromechanical model.
  • Application of optimal control theory to derive balancing strategies.
  • Analysis of open and closed-loop dynamics.

Main Results:

  • Identified an optimal rope sag that minimizes balancing effort.
  • Demonstrated the persistence of an optimal strategy despite nonlinearities, parameter coupling, and delays.
  • Results align with qualitative observations of balancing behavior.

Conclusions:

  • An optimal rope sag exists, reducing the neuromechanical effort required for balancing.
  • The findings provide insights into optimizing human balance control strategies.
  • The model offers a framework for understanding and improving performance in tasks like walking.