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. 2021 Jun 23:123:110477.
doi: 10.1016/j.jbiomech.2021.110477. Epub 2021 May 2.

A progressive-individualized midstance gait perturbation protocol for reactive balance assessment in stroke survivors

Affiliations

A progressive-individualized midstance gait perturbation protocol for reactive balance assessment in stroke survivors

Hala E Osman et al. J Biomech. .

Abstract

Restoration of balance control is a primary focus of rehabilitation after a stroke. The study developed a gait perturbation, treadmill-based, balance assessment protocol and demonstrated that it can be used to quantify improvements in reactive balance responses among individuals post-stroke. The protocol consists of a sequence of fifteen 90-second treadmill walking trials, with a single perturbation applied during the middle third of each trial. Gait was perturbed by rapid acceleration-deceleration of the treadmill belt at mid-stance of the unaffected leg during a randomly selected gait cycle. The initial perturbation magnitude was based on the participant's maximum walking speed and increased or decreased in each trial, based on success or failure of recovery, as determined from an instrumented harness. The protocol was used before and after a 10-week period of therapy in twenty-four stroke survivors. Outcomes included maximum recoverable perturbation (MRP), self-selected gait speed, levels progressed through the algorithm, and falls versus recoveries.Participants were able to take recovery steps in response to the perturbation. Twelve participants completed the full assessment protocol before and after the therapeutic intervention. After the intervention, they had fewer falls and more recoveries (p < 0.001), progressed through more algorithm levels (p = 0.043), had a higher MRP (p = 0.005), and had higher gait speeds. The protocol was found to be feasible in stroke survivors with moderate gait deficits. The data supports the conclusion that this protocol can be used in clinical research to quantify improvements in balance during walking.

Keywords: Falls; Gait; Mid-stance perturbation; Reactive balance; Stroke survivors.

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Conflict of interest statement

Conflict of interest

Authors declare no conflicts of interest.

Figures

Fig. 1.
Fig. 1.
(A) Experimental setup for post stroke gait perturbation. An instrumented treadmill with two independent force plates (FP1 & FP2), load cell (solid red square), Harness system (solid blue rectangular), assistive 3-level steps. (B) Trial design consisted of a 90-second of walking of three periods: pre-perturbation, within perturbation, and after perturbation. Each participant in each trial was perturbed unexpectedly at exactly the same time in the gait cycle. Participants walked on the treadmill using their normal gait speed about 23 min (90 sec for maximum of 15 trials) in a single testing session. (C) Screen image from D-Flow system showing the console application parameters for individuals’ post-stroke; including the peak load as % of BW, affected side, NWS, MWS, and mPer. The data flow is shown on the left, in which the Lua scripting language was used to execute a perturbation under the unaffected foot exactly at midstance in one random gait cycle within the perturbation period.
Fig. 2.
Fig. 2.
(A) Initial perturbation magnitude (mPer) was calculated based on the participant’s’ Mini-BEST score and their maximum walking speed (MWS in m\s). There are 3 levels of intensities: high, medium, and low. Each level matched with Mini-BEST total score and % of MSW. The same initial mPer was used for pre-and post- intervention testing. (B) A stepwise progression based on trial outcome then modulates the magnitude for subsequent trials. Trial outcomes were classified based on the peak load (PKL) as percentage of body weight (BW). R represents the recovery trial (PKL< 5 % of BW), M represents the intermediate trials (PKL 5% −30 % of BW), and F represents the fall trials (PKL> 30 % of BW), following the stepwise progression algorithm.
Fig. 3.
Fig. 3.
Illustration of velocity and the ground forces reaction results (top). A left side hemi- paretic stroke participant response to different perturbation magnitudes; small perturbation and large perturbation on the right foot perturbed. The perturbation consisted of the treadmill belt speeding up to the calculated magnitude for 0.25 seconds then returning to its previous speed and was delivered at exactly at midstance in one random gait cycle within 30 seconds in the perturbation period. An example of a participant’s data (bottom). This to show how the levels of progression was calculated before and after balance testing; R represents the recovery trial, M represents the intermediate trials, and F represents the fall trials following the stepwise progression algorithm. Participants showed improvement in reactive balance response in pre-to post tests.
Fig. 4.
Fig. 4.
Difference of means for the normal walking speed (NWS) and maximum walking speed (MWS) were significantly different before and after the tests (p < 0.05). Error bars are the standard deviations. Note: The treadmill ran at each participant’s NWS throughout the perturbation testing sessions. Participant’s maximum gait speed was used to calculate the perturbation magnitude (mPer) in the first trial.
Fig. 5.
Fig. 5.
Comparing pre to post tests, change of means for FLP group (n =12) were found statistically different (P < 0.05) between the outcome measures; Falls and recoveries (top), progression levels (PrgL) in (middle), and maximum recoverable perturbation magnitudes (MRP) in the (bottom). Error bars are the standard deviations.

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References

    1. Beyaert C, Vasa R and Frykberg GE (2015) ‘Gait post-stroke: Pathophysiology and rehabilitation strategies’, Neurophysiologie Clinique. doi: 10.1016/j.neucli.2015.09.005. - DOI - PubMed
    1. Bhatt T et al. (2011) ‘Dynamic gait stability, clinical correlates, and prognosis of falls among community-dwelling older adults’, Archives of Physical Medicine and Rehabilitation, 92(5), pp. 799–805. doi: 10.1016/j.apmr.2010.12.032. - DOI - PubMed
    1. Daly JJ et al. (2011) ‘Recovery of coordinated gait: Randomized controlled stroke trial of functional electrical stimulation (FES) versus no FES, with weight-supported treadmill and over-ground training’, Neurorehabilitation and Neural Repair, 25(7), pp. 588–596. doi: 10.1177/1545968311400092. - DOI - PubMed
    1. Godi M et al. (2013) ‘Comparison of Reliability, Validity, and Responsiveness of the Mini-BESTest and Berg Balance Scale in Patients With Balance Disorders’, Physical Therapy. doi: 10.2522/ptj.20120171. - DOI - PubMed
    1. Hamacher D et al. (2011) ‘Kinematic measures for assessing gait stability in elderly individuals: A systematic review’, Journal of the Royal Society Interface, pp. 1682–1698. doi: 10.1098/rsif.2011.0416. - DOI - PMC - PubMed

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