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Updated: Dec 30, 2025

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A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance
Published on: March 19, 2020
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Cortical reactive balance responses to unexpected slippages while walking: a pilot study
Summary
This study introduces a new method using electroencephalography (EEG) to detect brain cortex changes during unexpected balance challenges. This approach could help monitor fall risk in daily activities.
Area of Science:
- Neuroscience
- Biomechanics
- Human Motor Control
Background:
- Understanding cortical responses to balance perturbations is crucial for developing fall prevention strategies.
- Current methods for assessing balance recovery may not capture early cortical adaptations.
- The human brain cortex plays a key role in maintaining dynamic balance during locomotion.
Purpose of the Study:
- To develop and validate a novel methodological approach for early detection of scalp-level electroencephalographic (EEG) signal modifications during perturbed walking.
- To assess cortical activity changes in response to unexpected balance challenges using EEG and electromyography (EMG).
- To investigate the potential of EEG-based monitoring for assessing fall risk during daily activities.
Main Methods:
- Synchronous recording of lower limb kinematics, EMG, and 13-channel EEG signals in four young adults.
- Unexpected bilateral slippages were introduced during steady walking.
- EEG power spectrum density variation rate (m) was analyzed in five frequency bands (ϑ, α, β I, β II, β III) triggered by EMG signals.
Main Results:
- A significant increment in the EEG power spectrum density variation rate (m) was observed early after perturbation onset (perturbed step) across all analyzed rhythms.
- This heightened cortical activity diminished during the recovery step.
- The proposed method successfully distinguished between steady walking and early reactive balance recovery.
Conclusions:
- The developed methodological approach effectively detects early cortical changes associated with reactive balance recovery.
- This EEG-based method shows promise for real-time monitoring of fall risk during everyday activities.
- Further research can build upon this approach for advanced fall prevention strategies.
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