Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients

A low-dimensional representation of arm movements and hand grip forces in post-stroke individuals

Characterizing post-stroke impairments in the sensorimotor control of arm and hand is essential to better understand altered mechanisms of movement generation. Herein, we used a decomposition algorithm to characterize impairments in end-effector velocity and hand grip force data collected from an instrumented functional task in 83 healthy control and 27 chronic post-stroke individuals with mild-to-moderate impairments. According to kinematic and kinetic raw data, post-stroke individuals showed reduced functional performance during all task phases. After applying the decomposition algorithm, we observed that the behavioural data from healthy controls relies on a low-dimensional representation and demonstrated that this representation is mostly preserved post-stroke. Further, it emerged that reduced functional performance post-stroke correlates to an abnormal variance distribution of the behavioural representation, except when reducing hand grip forces. This suggests that the behavioural repertoire in these post-stroke individuals is mostly preserved, thereby pointing towards therapeutic strategies that optimize movement quality and the reduction of grip forces to improve performance of daily life activities post-stroke.

Principal Components Analysis Using Data Collected From Healthy Individuals on Two Robotic Assessment Platforms Yields Similar Behavioral Patterns

BACKGROUND

Kinarm Standard Tests (KSTs) is a suite of upper limb tasks to assess sensory, motor, and cognitive functions, which produces granular performance data that reflect spatial and temporal aspects of behavior (>100 variables per individual). We have previously used principal component analysis (PCA) to reduce the dimensionality of multivariate data using the Kinarm End-Point Lab (EP). Here, we performed PCA using data from the Kinarm Exoskeleton Lab (EXO), and determined agreement of PCA results across EP and EXO platforms in healthy participants. We additionally examined whether further dimensionality reduction was possible by using PCA across behavioral tasks.

METHODS

Healthy participants were assessed using the Kinarm EXO (N = 469) and EP (N = 170-200). Four behavioral tasks (six assessments in total) were performed that quantified arm sensory and motor function, including position sense [Arm Position Matching (APM)] and three motor tasks [Visually Guided Reaching (VGR), Object Hit (OH), and Object Hit and Avoid (OHA)]. The number of components to include per task was determined from scree plots and parallel analysis, and rotation type (orthogonal vs. oblique) was decided on a per-task basis. To assess agreement, we compared principal components (PCs) across platforms using distance correlation. We additionally considered inter-task interactions in EXO data by performing PCA across all six behavioral assessments.

RESULTS

By applying PCA on a per task basis to data collected using the EXO, the number of behavioral parameters were substantially reduced by 58-75% while accounting for 76-87% of the variance. These results compared well to the EP analysis, and we found good-to-excellent agreement values (0.75-0.99) between PCs from the EXO and those from the EP. Finally, we were able to reduce the dimensionality of the EXO data across tasks down to 16 components out of a total of 76 behavioral parameters, which represents a reduction of 79% while accounting for 73% of the total variance.

CONCLUSION

PCA of Kinarm robotic assessment appears to capture similar relationships between kinematic features in healthy individuals and is agnostic to the robotic platform used for collection. Further work is needed to investigate the use of PCA-based data reduction for the characterization of neurological deficits in clinical populations.

Motor improvement estimation and task adaptation for personalized robot-aided therapy: a feasibility study

Background

In the past years, robotic systems have become increasingly popular in upper limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients’ individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches.

Methods

Here, we present a model-based approach to personalize robot-aided rehabilitation therapy within training sessions. The proposed method combines the information from different motor performance measures recorded from the robot to continuously estimate patients’ motor improvement for a series of point-to-point reaching movements in different directions. Additionally, it comprises a personalization routine to automatically adapt the rehabilitation training. We engineered our approach using an upper-limb exoskeleton. The implementation was tested with 17 healthy subjects, who underwent a motor-adaptation paradigm, and two subacute stroke patients, exhibiting different degrees of motor impairment, who participated in a pilot test undergoing rehabilitative motor training.

Results

The results of the exploratory study with healthy subjects showed that the participants divided into fast and slow adapters. The model was able to correctly estimate distinct motor improvement progressions between the two groups of participants while proposing individual training protocols. For the two pilot patients, an analysis of the selected motor performance measures showed that both patients were able to retain the improvements gained during training when reaching movements were reintroduced at a later stage. These results suggest that the automated training adaptation was appropriately timed and specifically tailored to the abilities of each individual.

Conclusions

The results of our exploratory study demonstrated the feasibility of the proposed model-based approach for the personalization of robot-aided rehabilitation therapy. The pilot test with two subacute stroke patients further supported our approach, while providing encouraging results for the applicability in clinical settings.

Trial registration This study is registered in ClinicalTrials.gov (NCT02770300, registered 30 March 2016, https://clinicaltrials.gov/ct2/show/NCT02770300)

Resting-state EEG topographies: Reliable and sensitive signatures of unilateral spatial neglect

Theoretical advances in the neurosciences are leading to the development of an increasing number of proposed interventions for the enhancement of functional recovery after brain damage. Integration of these novel approaches in clinical practice depends on the availability of reliable, simple, and sensitive biomarkers of impairment level and extent of recovery, to enable an informed clinical-decision process. However, the neuropsychological tests currently in use do not tap into the complex neural re-organization process that occurs after brain insult and its modulation by treatment. Here we show that topographical analysis of resting-state electroencephalography (rsEEG) patterns using singular value decomposition (SVD) could be used to capture these processes. In two groups of subacute stroke patients, we show reliable detection of deviant neurophysiological patterns over repeated measurement sessions on separate days. These patterns generalized across patients groups. Additionally, they maintained a significant association with ipsilesional attention bias, discriminating patients with spatial neglect of different severity levels. The sensitivity and reliability of these rsEEG topographical analyses support their use as a tool for monitoring natural and treatment-induced recovery in the rehabilitation process.

The Effects of Upper Limb Motor Recovery on Submovement Characteristics among the Patients with Stroke: A Meta-Analysis

OBJECTIVE

To evaluate the evidence related to the effect of upper limb motor recovery on submovement characteristics, including duration, amplitude, overlap, interpeak distance, and the number of submovements in stroke patients using a meta-analysis.

TYPE OF STUDY

Meta-analysis.

LITERATURE SURVEY

The literature search was restricted to articles written in English published from inception to October 2018 in Web of Science, PubMed, Science Direct, IEEE Explore, MEDLINE, CDSR, Scopus, Compendex, Wiley Online Library, Springer Link, and REHABDATA.

METHODOLOGY

Studies were included if they encompassed adult participants with a clinical diagnosis of stroke who underwent upper limb rehabilitation and if they assessed and reported submovement characteristics as the outcome measures in pre- and posttreatment stages. Changes in submovement characteristics between pre- and postinterventions were compared using the standardized mean difference (SMD). Finally, a test for heterogeneity and publication bias was implemented for all meta-analyses.

SYNTHESIS

Among the 188 retrieved articles, seven of them (one randomized controlled trial, six pre-post) involving 259 patients were selected for meta-analysis. Based on the results, the overall observed changes in all meta-analyses were statistically significant. In total, submovement amplitude (SMD 0.624, 95% confidence interval [CI] [0.356, 0.893]), duration (SMD 0.61, 95% CI [0.332, 0.888]), and overlap (SMD 0.928, 95% CI [0.768, 1.088]) increased whereas interpeak distance (SMD -0.278, 95% CI [-0.42, -0.137]), and the total number of submovements (SMD -0.804, 95% CI [-1.069, -0.538]) decreased.

CONCLUSIONS

The submovements appeared to become longer, fewer, and more overlapped with motor recovery. Based on the results, the ability of the neural system to blend submovements increased in both acute/subacute and chronic patients during recovery. Therefore, assessing the submovements during recovery can be a new quantitative measure of motor improvement, providing another means of comparing rehabilitation interventions and individualizing therapy for stroke patients.

Functional differences in upper limb movement after early and chronic stroke based on kinematic motion indicators

AIMS

The main purpose of this study was to determine the changes in kinematic parameters of ischemic stroke affected upper limbs, during simple functional activity, to determine the most relevant changes.

METHODS

The OptiTrack system was used for motion capture. To determine upper extremity function in Activities of Daily Living (ADL) tasks. During particular phases, the following matrices were chosen: mean and peak speed, normalized movement unit, normalized jerk and phase movement time. The chosen matrices represent the speed and smoothness profile of end-point data. The the arm-trunk compensation was also taken into consideration. Twenty stroke patients, in early (G1 from 1 to 3 months after stroke) and chronic stage (G2 from 6 months to 1 year), were studied. The large and small cylinder forward and back transporting phases were evaluated.

RESULTS

The most significant differences between groups G1 and G2 were in mean and peak speed of the forward transport of the large and small cylinders for the paretic limb. Significant differences were also found for the smoothness (measured by movement unit, mean and peak speed and jerk) where the G2 group had a rougher motion. There were also differences in arm-trunk compensation in the frontal plane.

CONCLUSION

The variables used in the study showed applicability in assessing kinematic parameters in both the early and chronic period after stroke.

Translational effects of robot-mediated therapy in subacute stroke patients: an experimental evaluation of upper limb motor recovery

Robot-mediated therapies enhance the recovery of post-stroke patients with motor deficits. Repetitive and repeatable exercises are essential for rehabilitation following brain damage or other disorders that impact the central nervous system, as plasticity permits to reorganize its neural structure, fostering motor relearning. Despite the fact that so many studies claim the validity of robot-mediated therapy in post-stroke patient rehabilitation, it is still difficult to assess to what extent its adoption improves the efficacy of traditional therapy in daily life, and also because most of the studies involved planar robots. In this paper, we report the effects of a 20-session-rehabilitation project involving the Armeo Power robot, an assistive exoskeleton to perform 3D upper limb movements, in addition to conventional rehabilitation therapy, on 10 subacute stroke survivors. Patients were evaluated through clinical scales and a kinematic assessment of the upper limbs, both pre- and post-treatment. A set of indices based on the patients' 3D kinematic data, gathered from an optoelectronic system, was calculated. Statistical analysis showed a remarkable difference in most parameters between pre- and post-treatment. Significant correlations between the kinematic parameters and clinical scales were found. Our findings suggest that 3D robot-mediated rehabilitation, in addition to conventional therapy, could represent an effective means for the recovery of upper limb disability. Kinematic assessment may represent a valid tool for objectively evaluating the efficacy of the rehabilitation treatment.

Kinematic Components of the Reach-to-Target Movement After Stroke for Focused Rehabilitation Interventions: Systematic Review and Meta-Analysis

Background: Better upper limb recovery after stroke could be achieved through tailoring rehabilitation interventions directly at movement deficits. Aim: To identify potential; targets for therapy by synthesizing findings of differences in kinematics and muscle activity between stroke survivors and healthy adults performing reach-to-target tasks. Methods: A systematic review with identification of studies, data extraction, and potential risk of bias was completed independently by two reviewers. Online databases were searched from their inception to November 2017 to find studies of reach-to-target in people-with-stroke and healthy adults. Potential risk-of-bias was assessed using the Down's and Black Tool. Synthesis was undertaken via: (a) meta-analysis of kinematic characteristics utilizing the standardized mean difference (SMD) [95% confidence intervals]; and (b), narrative synthesis of muscle activation. Results: Forty-six studies met the review criteria but 14 had insufficient data for extraction. Consequently, 32 studies were included in the meta-analysis. Potential risk-of-bias was low for one study, unclear for 30, and high for one. Reach-to-target was investigated with 618 people-with-stroke and 429 healthy adults. The meta-analysis found, in all areas of workspace, that people-with-stroke had: greater movement times (seconds) e.g., SMD 2.57 [0.89, 4.25]; lower peak velocity (millimeters/second) e.g., SMD -1.76 [-2.29, -1.24]; greater trunk displacement (millimeters) e.g. SMD 1.42 [0.90, 1.93]; a more curved reach-path-ratio e.g., SMD 0.77 [0.32, 1.22] and reduced movement smoothness e.g., SMD 0.92 [0.32, 1.52]. In the ipsilateral and contralateral workspace, people-with-stroke exhibited: larger errors in target accuracy e.g., SMD 0.70 [0.39, 1.01]. In contralateral workspace, stroke survivors had: reduced elbow extension and shoulder flexion (degrees) e.g., elbow extension SMD -1.10 [-1.62, -0.58] and reduced shoulder flexion SMD -1.91 [-1.96, -0.42]. Narrative synthesis of muscle activation found that people-with-stroke, compared with healthy adults, exhibited: delayed muscle activation; reduced coherence between muscle pairs; and use of a greater percentage of muscle power. Conclusions: This first-ever meta-analysis of the kinematic differences between people with stroke and healthy adults performing reach-to-target found statistically significant differences for 21 of the 26 comparisons. The differences identified and values provided are potential foci for tailored rehabilitation interventions to improve upper limb recovery after stroke.

Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation

Ischemic damage to the brain triggers substantial reorganization of spared areas and pathways, which is associated with limited, spontaneous restoration of function. A better understanding of this plastic remodeling is crucial to develop more effective strategies for stroke rehabilitation. In this review article, we discuss advances in the comprehension of post-stroke network reorganization in patients and animal models. We first focus on rodent studies that have shed light on the mechanisms underlying neuronal remodeling in the perilesional area and contralesional hemisphere after motor cortex infarcts. Analysis of electrophysiological data has demonstrated brain-wide alterations in functional connectivity in both hemispheres, well beyond the infarcted area. We then illustrate the potential use of non-invasive brain stimulation (NIBS) techniques to boost recovery. We finally discuss rehabilitative protocols based on robotic devices as a tool to promote endogenous plasticity and functional restoration.