Prediction of Walking and Arm Recovery after Stroke: A Critical Review

Kwah, Li Khim; Herbert, Robert D.

doi:10.3390/brainsci6040053

Cited by 50 publications

(49 citation statements)

References 123 publications

(330 reference statements)

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“…These results of MRCP Npeak analysis suggest that 4 weeks of rehabilitation is not a su cient time to obtain consistent EEG signal changes for the brain stem stroke patients in group B. This outcome is consistent with clinical observations that patients with brain stem strokes are typically slower to recover motor function than patients with supratentorial strokes (48). Table 7 shows the average results of FMA-wrist, FMA-hand, MAS-hand movements, and MAS-advanced hand movements' clinical tests.…”

Section: Extended Training Of Group B and Its Resultssupporting

confidence: 84%

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Effect of Post-Stroke Motor Training on EEG Movement-Related Cortical Potentials

Butt

Naghdy

et al. 2020

Preprint

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BackgroundRehabilitation of post-stroke patients with motor impairments promotes re-learning of lost motor functions through the brain neuroplasticity. Monitoring of electroencephalogram (EEG) signals has the potential to show neuroplasticity changes that take place during motor training.MethodsIn this study, an EEG-derived time-domain pattern namely movement-related cortical potential (MRCP) was deployed to assess the effect of motor training in seven post-stroke patients. Patients were divided into two groups; group A comprising four subjects with supratentorial lesions and group B consisting of three subjects with infratentorial lesions. Both groups participated in motor training with an AMADEO hand rehabilitation device. During pre and post-training periods, EEG signals at eight selected electrodes were recorded. In addition, hand-kinematic parameters, and clinical tests were measured at the beginning and the end of all training sessions.ResultsThe negative peak of the MRCP signals decreased at all electrodes and reached significance in seven of eight electrodes for group A after 12 training sessions, while it was decreased at all electrodes and reached significance in two of eight electrodes for group B after 24 sessions according to paired t-test (p < 0.05). Moreover, these MRCP changes correlated with improvements in kinematic parameters and clinical test results for both groups.ConclusionsThis study shows that robot-assisted training that improves clinical outcomes is associated with MRCP pattern changes. Subjects with infratentorial strokes improved slower clinically compared to subjects with supratentorial strokes. This was consistent with the longer rehabilitation required for this group of patients to produce significant changes in MRCP. The reduction of negative peaks of the MRCP signal indicates that neurological pathways are established and less cortical resources are needed for motor tasks. This study demonstrates the significance of EEG as a practical and low-cost tool in detecting patterns associated with brain neuroplasticity in the course of motor re-learning. Ethics ApprovalThe procedures performed in this study were approved by the University of Wollongong Ethics Committee (Ethics application number: 2014/400) on 03/07/2017.

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Section: Extended Training Of Group B and Its Resultssupporting

confidence: 84%

“…At rst, it was decided to compare the results of four weeks of training for both groups. However, it was anticipated that group B participants might require longer training-period due to lesion location in their brain stem (48).…”

Section: Motor Training Protocolmentioning

confidence: 99%

Effect of Post-Stroke Motor Training on EEG Movement-Related Cortical Potentials

Butt

Naghdy

et al. 2020

Preprint

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“…Dynamic and static balance impairments are common and debilitating in patients with Parkinson disease (PD), leading to deficits in activities of daily living (ADLs) and fear of falling (FOF) . Among survivors of cerebrovascular accident (CVA), instability during standing and walking occurs immediately after CVA onset and may persist, leading to reduced independence and increased risk of falling …”

Section: Introductionmentioning

confidence: 99%

Instrumented Version of the Modified Dynamic Gait Index in Patients With Neurologic Disorders

Anastasi

Carpinella

Gervasoni

et al. 2019

PM&R

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Background: Gait instability is common in adults with neurologic disorders and the modified Dynamic Gait Index (mDGI) was recently introduced to assess dynamic balance. However, instrumental assessment is needed to provide quantitative measures. Objective: To develop and validate an instrumented version of the mDGI. Design: Cross-sectional study. Setting: Clinical setting. Participants: Thirty adults with neurologic disorders (10 with multiple sclerosis, 10 with Parkinson disease, and 10 with stroke) and 20 healthy volunteers. Methods: Participants were assessed with the Timed Up and Go test (TUG) and with the mDGI. During the assessment of mDGI, data were collected by a single Inertial Measurement Unit (IMU) positioned on the sternum. Principal component analysis (PCA) was performed on the instrumented data extracting eight PC scores (ImPC) describing dynamic balance. The instrumented overall score (ImDGI) was then calculated as the sum of the mPCs. PCA revealed two components associated with stride features and regularity (ImDGI_Gait_Pattern) and trunk movements (ImDGI_Trunk_Sway). Spearman coefficients were calculated between mDGI and ImDGI, whereas Mann-Whitney (U) and Kruskal-Wallis (H) tests assessed differences between groups and neurologic conditions. Main Outcome Measurements: ImDGI. Results: ImDGI did not show ceiling effects, and good correlations were found between ImDGI and mDGI (r = .84), and TUG (r = .84) for people with neurologic disorders (P < .001). Significant differences among pathologies (H test (2) =12.5, P = .002) and between healthy participants and adults with neurologic disorders (U test = 47.0, P = .001) were found. ImDGI_Trunk_Sway discriminated between people using or not using walking aids and among the three pathologies (H (2) = 10.0, P = .007). Conclusions:The ImDGI test seems to provide valid measures to objectively assess dynamic balance in neurologic conditions and possibly quantify balance deficits also in adults with neurologic disorders.

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“…The changes on the NIHSS and of symptoms and signs of traditional Chinese medicine during the first 5 days after stroke predicted the 90-day outcome [18]. As motor functions and walking are in the center of rehabilitative activities, several studies concentrated on the prediction of recovery of these modalities and developed special models for this application [19,20,21]. Chances for improvement of post-stroke aphasia can be estimated from the performance in word repetition from a language screening task, supporting the importance of perception and motor production for recovery of language function [22].…”

Section: Introductionmentioning

confidence: 99%

“…However, more studies are needed to establish conclusively which biomarkers are best predictors of functional recovery after stroke [25.] Current evidence suggests that the addition of neuroimaging data to models containing clinical predictors yields clinically important increases in predictive accuracy [21]. In this review, which is an update of a previous publication [26,] the contributions of various neuroimaging modalities for the prediction of recovery and of functional outcome in patients after ischemic stroke and their role in assessing the efficacy of rehabilitation therapies, both in clinical trials and in individual patients, are discussed.…”

Section: Introductionmentioning

confidence: 99%

Contribution of Neuro-Imaging for Prediction of Functional Recovery after Ischemic Stroke

Heiss¹

2017

Cerebrovasc Dis

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Prediction measures of recovery and outcome after stroke perform with only modest levels of accuracy if based only on clinical data. Prediction scores can be improved by including morphologic imaging data, where size, location, and development of the ischemic lesion is best documented by magnetic resonance imaging. In addition to the primary lesion, the involvement of fiber tracts contributes to prognosis, and consequently the use of diffusion tensor imaging (DTI) to assess primary and secondary pathways improves the prediction of outcome and of therapeutic effects. The recovery of ischemic tissue and the progression of damage are dependent on the quality of blood supply. Therefore, the status of the supplying arteries and of the collateral flow is not only crucial for determining eligibility for acute interventions, but also has an impact on the potential to integrate areas surrounding the lesion that are not typically part of a functional network into the recovery process. The changes in these functional networks after a localized lesion are assessed by functional imaging methods, which additionally show altered pathways and activated secondary centers related to residual functions and demonstrate changes in activation patterns within these networks with improved performance. These strategies in some instances record activation in secondary centers of a network, for example, also in homolog contralateral areas, which might be inhibitory to the recovery of primary centers. Such findings might have therapeutic consequences, for example, image-guided inhibitory stimulation of these areas. In the future, a combination of morphological imaging including DTI of fiber tracts and activation studies during specific tasks might yield the best information on residual function, reserve capacity, and prospects for recovery after ischemic stroke.

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Prediction of Walking and Arm Recovery after Stroke: A Critical Review

Cited by 50 publications

References 123 publications

Effect of Post-Stroke Motor Training on EEG Movement-Related Cortical Potentials

Effect of Post-Stroke Motor Training on EEG Movement-Related Cortical Potentials

Instrumented Version of the Modified Dynamic Gait Index in Patients With Neurologic Disorders

Contribution of Neuro-Imaging for Prediction of Functional Recovery after Ischemic Stroke

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