Motor Recovery in Stroke Rehabilitation Supported by Robot-Assisted Therapy

This chapter discussed the potential usefulness of robot-assisted therapy for motor recovery after a stroke. An overview of the available literature was performed providing up-to-date information about the use of robot-assistive technology in rehabilitation practice. The chapter discussed the rationale for the use and the different machines in terms of basic engineering principles and the related rehabilitation possibilities. Finally, clinical and rehabilitative implications of the findings were critically discussed.

Multimodal Imaging Biomarker-Based Model Using Stratification Strategies for Predicting Upper Extremity Motor Recovery in Severe Stroke Patients

Background. Various prognostic biomarkers for upper extremity (UE) motor recovery after stroke have been reported. However, most have relatively low predictive accuracy in severe stroke patients. Objective. This study suggests an imaging biomarker-based model for effectively predicting UE recovery in severe stroke patients. Methods. Of 104 ischemic stroke patients screened, 42 with severe motor impairment were included. All patients underwent structural, diffusion, and functional magnetic resonance imaging at 2 weeks and underwent motor function assessments at 2 weeks and 3 months after stroke onset. According to motor function recovery at 3 months, patients were divided into good and poor subgroups. The value of multimodal imaging biomarkers of lesion load, lesion volume, white matter integrity, and cortical functional connectivity for motor recovery prediction was investigated in each subgroup. Results. Imaging biomarkers varied depending on recovery pattern. The integrity of the cerebellar tract ( P = .005, R 2 = .432) was the primary biomarker in the good recovery group. In contrast, the sensory-related corpus callosum tract ( P = .026, R 2 = .332) and sensory-related functional connectivity ( P = .001, R 2 = .531) were primary biomarkers in the poor recovery group. A prediction model was proposed by applying each biomarker in the subgroup to patients with different motor evoked potential responses ( P < .001, R 2 = .853, root mean square error = 5.28). Conclusions. Our results suggest an optimized imaging biomarker model for predicting UE motor recovery after stroke. This model can contribute to individualized management of severe stroke in a clinical setting.

Application Of Mirror Therapy On Upper Extremity Motor Recovery In Post-Stroke Patients

Background: Stroke is a health problem for both developed and developing countries, including Indonesia. Paralysis in stroke is mainly due to damage to the internal capsule. This damage requires neuroplasticity involving a number of parts of the brain to restore. One therapy that is beneficial for neuroplasticity is Mirror Therapy (MT). MT is a rehabilitation tool that aims to restore some of the pathological conditions in which the body representation is affected, including post-stroke motor impairment. Methods: This research is a quantitative pre-experimental design with the type one group pretest-postest. The research subjects were 15 post-stroke patients in residency of Semarang. Research data were collected in August-September 2020. Sample selection with purposive sampling technique who conform inclusion criteria. The Fulg-Meyer Upper Extremity Assessment (FMA-UE) as an aoutcame measure that be avowed valid and reliabel. Data analysis using Paired Sample T-Test because of normally distributed. Results: Statistically the results represent a significant difference in the UE motor ability of post-stroke patients between baseline and after mirror therapy intervention, with a mean difference (5,14) and p value = 0.000 (ρ < 0,05). Application of MT effect on upper extremity motor recovery in post-stroke patients. Conclusions: MT program is an effective intervention for UE motor recovery and motor function improvement in post- stroke patients. MT program can be used as a standardized of hand rehabilitation intervention in hospital, clinics and homes.

No evidence for motor recovery-related cortical connectivity changes after stroke using resting-state fMRI

It has been proposed that a form of cortical reorganization (changes in functional connectivity between brain areas) can be assessed with resting-state (rs) fMRI. Here we report a longitudinal data-set collected from 19 patients with subcortical stroke and 11 controls. Patients were imaged up to five times over one year. We found no evidence, using rs-fMRI, for post-stroke cortical connectivity changes despite substantial behavioral recovery. These results could be construed as questioning the value of resting-state imaging. Here we argue instead that they are consistent with other emerging reasons to challenge the idea of motor recovery-related cortical reorganization post-stroke when conceived of as changes in connectivity between cortical areas.

Brain–Computer Interface Training Based on Brain Activity Can Induce Motor Recovery in Patients With Stroke: A Meta-Analysis

Background Brain–computer interface (BCI) is a procedure involving brain activity in which neural status is provided to the participants for self-regulation. The current review aims to evaluate the effect sizes of clinical studies investigating the use of BCI-based rehabilitation interventions in restoring upper extremity function and effective methods to detect brain activity for motor recovery. Methods A computerized search of MEDLINE, CENTRAL, Web of Science, and PEDro was performed to identify relevant articles. We selected clinical trials that used BCI-based training for post-stroke patients and provided motor assessment scores before and after the intervention. The pooled standardized mean differences of BCI-based training were calculated using the random-effects model. Results We initially identified 655 potentially relevant articles; finally, 16 articles fulfilled the inclusion criteria, involving 382 participants. A significant effect of neurofeedback intervention for the paretic upper limb was observed (standardized mean difference = .48, [.16-.80], P = .006). However, the effect estimates were moderately heterogeneous among the studies ( I2 = 45%, P = .03). Subgroup analysis of the method of measurement of brain activity indicated the effectiveness of the algorithm focusing on sensorimotor rhythm. Conclusion This meta-analysis suggested that BCI-based training was superior to conventional interventions for motor recovery of the upper limbs in patients with stroke. However, the results are not conclusive because of a high risk of bias and a large degree of heterogeneity due to the differences in the BCI interventions and the participants; therefore, further studies involving larger cohorts are required to confirm these results.

Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers

Background: The efficacy of upper-limb Robot-assisted Therapy (ulRT) in stroke subjects is well-established. The robot-measured kinematic data can assess the biomechanical changes induced by ulRT and the progress of patient over time. However, literature on the analysis of pre-treatment kinematic parameters as predictive biomarkers of upper limb recovery is limited.Objective: The aim of this study was to calculate pre-treatment kinematic parameters from point-to-point reaching movements in different directions and to identify biomarkers of upper-limb motor recovery in subacute stroke subjects after ulRT.Methods: An observational retrospective study was conducted on 66 subacute stroke subjects who underwent ulRT with an end-effector robot. Kinematic parameters were calculated from the robot-measured trajectories during movements in different directions. A Generalized Linear Model (GLM) was applied considering the post-treatment Upper Limb Motricity Index and the kinematic parameters (from demanding directions of movement) as dependent variables, and the pre-treatment kinematic parameters as independent variables.Results: A subset of kinematic parameters significantly predicted the motor impairment after ulRT: the accuracy in adduction and internal rotation movements of the shoulder was the major predictor of post-treatment Upper Limb Motricity Index. The post-treatment kinematic parameters of the most demanding directions of movement significantly depended on the ability to execute elbow flexion-extension and abduction and external rotation movements of the shoulder at baseline.Conclusions: The multidirectional analysis of robot-measured kinematic data predicts motor recovery in subacute stroke survivors and paves the way in identifying subjects who may benefit more from ulRT.

Effect of Diabetes on Post-stroke Recovery: A Systematic Narrative Review

Background: Patients with stroke often have comorbid diabetes. Considering its detrimental effects on brain function, diabetes may increase the risk of poor recovery.Methods: The aim of this review was to investigate the effect of diabetes on post-stroke recovery by a systematic review. Several specific aspects of post-stroke recovery, including activities of daily living (ADL), motor, cognitive, and quality of life (QOL) recovery, were examined. We searched the PubMed, SCOPUS, Embase, and Cochrane Library databases for relevant studies on the effect of diabetes on post-stroke recovery, published until May 26, 2021. A total of 52,051 potentially relevant articles were identified. After reading the titles and abstracts and assessing their eligibility based on full-text articles, 34 publications were included in this review.Results: Of 29 studies that assessed ADL recovery after stroke, 22 studies suggested that diabetes had a negative effect on recovery of ADL after stroke. Regarding motor recovery, only one out of four studies showed that diabetes had some effect on motor recovery after stroke. Of the two studies on cognitive recovery, one reported that diabetes was an independent predictor of poor cognitive recovery after stroke. Three studies on QOL reported that a poor QOL after stroke was associated with the presence of diabetes.Conclusions: The current review suggests that the post-stroke recovery of ADL seems to be poorer in patients with diabetes than patients without diabetes. Further, there are insufficient data to conclude the effect of diabetes on motor and cognitive recovery, but it may have some influence on the quality of life after stroke.Systematic Review Registration: doi: 10.37766/inplasy2021.11.0032, identifier: INPLASY2021110032.

Unlike Brief Inhibition of Microglia Proliferation after Spinal Cord Injury, Long-Term Treatment Does Not Improve Motor Recovery

Microglia are major players in scar formation after an injury to the spinal cord. Microglia proliferation, differentiation, and survival are regulated by the colony-stimulating factor 1 (CSF1). Complete microglia elimination using CSF1 receptor (CSF1R) inhibitors worsens motor function recovery after spinal injury (SCI). Conversely, a 1-week oral treatment with GW2580, a CSF1R inhibitor that only inhibits microglia proliferation, promotes motor recovery. Here, we investigate whether prolonged GW2580 treatment further increases beneficial effects on locomotion after SCI. We thus assessed the effect of a 6-week GW2580 oral treatment after lateral hemisection of the spinal cord on functional recovery and its outcome on tissue and cellular responses in adult mice. Long-term depletion of microglia proliferation after SCI failed to improve motor recovery and had no effect on tissue reorganization, as revealed by ex vivo diffusion-weighted magnetic resonance imaging. Six weeks after SCI, GW2580 treatment decreased microglial reactivity and increased astrocytic reactivity. We thus demonstrate that increasing the duration of GW2580 treatment is not beneficial for motor recovery after SCI.