Identifying candidates for targeted gait rehabilitation after stroke: better prediction through biomechanics-informed characterization
Author(s) | Awad,Louis N. | |
Author(s) | Reisman,Darcy S. | |
Author(s) | Pohlig,Ryan T. | |
Author(s) | Binder-Macleod,Stuart A. | |
Ordered Author | Darcy S. Reisman PT, PhD, Ryan T. Pohlig PhD and Stuart A. Binder-MacleodPT, PhD | |
UD Author | Reisman, Darcy S;Pohlig, Ryan Todd;Binder-Macleod, Stuart | |
Date Accessioned | 2017-07-19T18:48:37Z | |
Date Available | 2017-07-19T18:48:37Z | |
Copyright Date | 2016 The Author(s). | |
Publication Date | 9/23/16 | |
Description | Publisher's PDF | |
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 (UWSbaseline), maximum walking speed (MWSbaseline), and paretic propulsion (prop(baseline)) versus improvements in usual walking speed (Delta UWS) and maximum walking speed (Delta MWS) were evaluated in moderated regression models. Results: UWSbaseline and MWSbaseline were, respectively, poor predictors of Delta UWS (R-2 = 0.24) and Delta MWS (R-2 = 0.01). Paretic propulsion x walking speed interactions (UWSbaseline x propbaseline and MWSbaseline x propbaseline) were observed in each regression model (R(2)s = 0.61 and 0.49 for Delta UWS and Delta 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. | |
Department | University of Delaware, Department of Physical Therapy University of Delaware, Graduate Program BioMechanical and Movement Sciences University of Delaware, Biostatistics Core Facility | |
Citation | Awad, L. N., Reisman, D. S., Pohlig, R. T., & Binder-Macleod, S. A. (2016). Identifying candidates for targeted gait rehabilitation after stroke: Better prediction through biomechanics-informed characterization. Journal of Neuroengineering and Rehabilitation, 13, 84. doi:10.1186/s12984-016-0188-8 | |
DOI | 10.1186/s12984-016-0188-8 | |
ISSN | 1743-0003 | |
URL | http://udspace.udel.edu/handle/19716/21565 | |
Language | English | |
Publisher | Biomed Central Ltd | |
dc.rights | CC BY 4.0 | |
dc.source | Journal of Neuroengineering and Rehabilitation | |
dc.source.uri | https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-016-0188-8 | |
Title | Identifying candidates for targeted gait rehabilitation after stroke: better prediction through biomechanics-informed characterization | |
Type | Article |
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