Identifying candidates for targeted gait rehabilitation after stroke: better prediction through biomechanics-informed characterization

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Paretic Propulsion and Trailing Limb Angle Are Key Determinants of Long-Distance Walking Function After Stroke

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Identifying candidates for targeted gait rehabilitation after stroke: better prediction through biomechanics-informed characterization

• Louis N. AwadEmail author,
• Darcy S. Reisman,
• Ryan T. Pohlig and
• Stuart A. Binder-Macleod

Journal of NeuroEngineering and Rehabilitation201613:84

DOI: 10.1186/s12984-016-0188-8

©  The Author(s). 2016

Received: 11 June 2016

Accepted: 26 August 2016

Published: 23 September 2016

Abstract

Background

Walking speed has been used to predict the efficacy of gait training; however, poststroke motor impairments are heterogeneous and different biomechanical strategies may underlie the same walking speed. Identifying which individuals will respond best to a particular gait rehabilitation program using walking speed alone may thus be limited. The objective of this study was to determine if, beyond walking speed, participants’ baseline ability to generate propulsive force from their paretic limbs (paretic propulsion) influences the improvements in walking speed resulting from a paretic propulsion-targeting gait intervention.

Methods

Twenty seven participants >6 months poststroke underwent a 12-week locomotor training program designed to target deficits in paretic propulsion through the combination of fast walking with functional electrical stimulation to the paretic ankle musculature (FastFES). The relationship between participants’ baseline usual walking speed (UWS_baseline), maximum walking speed (MWS_baseline), and paretic propulsion (prop_baseline) versus improvements in usual walking speed (∆UWS) and maximum walking speed (∆MWS) were evaluated in moderated regression models.

Results

UWS_baseline and MWS_baseline were, respectively, poor predictors of ΔUWS (R ²  = 0.24) and ΔMWS (R ²  = 0.01). Paretic propulsion × walking speed interactions (UWS_baseline × prop_baseline and MWS_baseline × prop_baseline) were observed in each regression model (R ² s  = 0.61 and 0.49 for ∆UWS and ∆MWS, respectively), revealing that slower individuals with higher utilization of the paretic limb for forward propulsion responded best to FastFES training and were the most likely to achieve clinically important differences.

Conclusions

Characterizing participants based on both their walking speed and ability to generate paretic propulsion is a markedly better approach to predicting walking recovery following targeted gait rehabilitation than using walking speed alone.