Temporal Evolution of Frontal Plane Center-of-Mass Transfer Asymmetry in Post-Stroke Gait

In typical human gait, the body center-of-mass (CoM) is cyclically transferred towards and supported by each lower extremity. The magnitude of this CoM transfer can be quantified by measuring the minimum mediolateral distance between the CoM and the stance foot during each step. Individuals with hemiparesis due to stroke often show a reduced and more variable CoM transfer magnitude in paretic versus non-paretic steps, which are linked to slower walking speeds and an increased risk of falling. While the commonly observed wider and more variable paretic foot placement at initial contact likely contributes to such frontal plane CoM transfer abnormalities, other factors could continue to adjust the CoM transfer magnitude after initial contact. To understand how the CoM transfer magnitude evolves throughout the transfer process, we derived an inverted-pendulum-based equation that projects the experimentally measured instantaneous mediolateral CoM position and velocity to the CoM transfer magnitude. We first validated our derived equation by demonstrating that CoM transfer magnitude can be predicted by the CoM position and velocity at the end of the double support phase with passive inverted pendulum dynamics. We then investigated how the asymmetry of this projected CoM transfer magnitude between the paretic and non-paretic steps evolves during the transfer process. Our findings revealed that about 54% of the transfer magnitude asymmetry was established at initial contact, predominantly influenced by foot placement, while another 38% was established during the double support phase, partly due to reduced work input from the non-paretic trailing limb. Additionally, the variability in transfer magnitude was augmented during the double support phase in paretic steps. Overall, the present study introduces a physics-based method capable of predicting CoM transfer magnitude in advance of its completion, and our findings highlight the significant contribution of the double support phase, which was previously less explored, to the asymmetries in CoM transfer magnitude and variability. Our results suggest that biomechanical factors during this phase, such as trailing limb work input, could be critical targets for future research and therapeutic interventions.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/tnsre.2025.3559857
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Temporal Evolution of Frontal Plane Center-of-Mass Transfer Asymmetry in Post-Stroke Gait

Keng-Hung Shen, Hao‐Yuan Hsiao, Robert Lee
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Advanced Neuroimaging Techniques and Applications
article

Temporal Evolution of Frontal Plane Center-of-Mass Transfer Asymmetry in Post-Stroke Gait

Keng-Hung Shen, Hao‐Yuan Hsiao, Robert Lee
article en

Abstract

In typical human gait, the body center-of-mass (CoM) is cyclically transferred towards and supported by each lower extremity. The magnitude of this CoM transfer can be quantified by measuring the minimum mediolateral distance between the CoM and the stance foot during each step. Individuals with hemiparesis due to stroke often show a reduced and more variable CoM transfer magnitude in paretic versus non-paretic steps, which are linked to slower walking speeds and an increased risk of falling. While the commonly observed wider and more variable paretic foot placement at initial contact likely contributes to such frontal plane CoM transfer abnormalities, other factors could continue to adjust the CoM transfer magnitude after initial contact. To understand how the CoM transfer magnitude evolves throughout the transfer process, we derived an inverted-pendulum-based equation that projects the experimentally measured instantaneous mediolateral CoM position and velocity to the CoM transfer magnitude. We first validated our derived equation by demonstrating that CoM transfer magnitude can be predicted by the CoM position and velocity at the end of the double support phase with passive inverted pendulum dynamics. We then investigated how the asymmetry of this projected CoM transfer magnitude between the paretic and non-paretic steps evolves during the transfer process. Our findings revealed that about 54% of the transfer magnitude asymmetry was established at initial contact, predominantly influenced by foot placement, while another 38% was established during the double support phase, partly due to reduced work input from the non-paretic trailing limb. Additionally, the variability in transfer magnitude was augmented during the double support phase in paretic steps. Overall, the present study introduces a physics-based method capable of predicting CoM transfer magnitude in advance of its completion, and our findings highlight the significant contribution of the double support phase, which was previously less explored, to the asymmetries in CoM transfer magnitude and variability. Our results suggest that biomechanical factors during this phase, such as trailing limb work input, could be critical targets for future research and therapeutic interventions.

IEEE Transactions on Neural Systems and Rehabilitation EngineeringVol. 33
St David's Medical Center (US), The University of Texas at Austin (US)
National Institutes of Health
Climate action
Openalex Percentile: Top 89%
Advanced Neuroimaging Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.