Feature analysis of joint motion in paralyzed and non-paralyzed upper limbs while reaching the occiput: A cross-sectional study in patients with mild hemiplegia

The reaching motion to the back of the head with the hand is an important movement for daily living. The scores of upper limb function tests used in clinical practice alone are difficult to use as a reference when planning exercises for movement improvements. This cross-sectional study aimed to clarify in patients with mild hemiplegia the kinematic characteristics of paralyzed and non-paralyzed upper limbs reaching the occiput. Ten patients with post-stroke hemiplegia who attended the Department of Rehabilitation Medicine of the Jikei University Hospital and met the eligibility criteria were included. Reaching motion to the back of the head by the participants' paralyzed and non-paralyzed upper limbs was measured using three-dimensional motion analysis, and the motor time, joint angles, and angular velocities were calculated. Repeated measures multivariate analysis of covariance was performed on these data. After confirming the fit to the binomial logistic regression model, the cutoff values were calculated using receiver operating characteristic curves. Pattern identification using random forest clustering was performed to analyze the pattern of motor time and joint angles. The cutoff values for the movement until the hand reached the back of the head were 1.6 s for the motor time, 55° for the maximum shoulder joint flexion angle, and 145° for the maximum elbow joint flexion angle. The cutoff values for the movement from the back of the head to the hand being returned to its original position were 1.6 s for the motor time, 145° for the maximum elbow joint flexion angle, 53°/s for the maximum angular velocity of shoulder joint abduction, and 62°/s for the maximum angular velocity of elbow joint flexion. The numbers of clusters were three, four, and four for the outward non-paralyzed side, outward and return paralyzed side, and return non-paralyzed side, respectively. The findings obtained by this study can be used for practice planning in patients with mild hemiplegia who aim to improve the reaching motion to the occiput.

Kinematic analysis of movement patterns during a reach-and-grasp task in stroke patients

Background

This study aimed to evaluate the kinematic movement patterns during a reach-and-grasp task in post-stroke patients according to the upper extremity impairment severity.

Methods

Subacute stroke patients (n = 46) and healthy controls (n = 20) were enrolled in this study. Spatiotemporal and kinematic data were obtained through 3D motion analysis during the reach-and-grasp task. Stroke patients were grouped using the Fugl-Meyer Assessment (FMA) scale, and a comparison of the groups was performed.

Results

The severe group showed a significantly longer movement time, lower peak velocity, and higher number of movement units than the mild group during the reach-and-grasp task (p < 0.05). Characteristic compensatory movement patterns, such as shoulder abduction, thoracic posterior tilting, and upward and external rotation were significantly greater during the forward transporting phase in the severe group than in the mild group (p < 0.05). The FMA score was significantly associated with the movement time during the forward transporting phase, number of movement units during the reaching phase, range of shoulder abduction-adduction and wrist flexion-extension movements during the reaching phase, and range of thoracic internal-external rotation during the backward transporting phase (p < 0.05).

Conclusion

Post-stroke patients have unique spatiotemporal and kinematic movement patterns during a reach-and grasp-task according to the impairment severity.

Muscle synergies for evaluating upper limb in clinical applications: A systematic review

INTRODUCTION

Muscle synergies have been proposed as a strategy employed by the central nervous system to control movements. Muscle synergy analysis is a well-established framework to examine the pathophysiological basis of neurological diseases and has been applied for analysis and assessment in clinical applications in the last decades, even if it has not yet been widely used in clinical diagnosis, rehabilitative treatment and interventions. Even if inconsistencies in the outputs among studies and lack of a normative pipeline including signal processing and synergy analysis limit the progress, common findings and results are identifiable as a basis for future research. Therefore, a literature review that summarizes methods and main findings of previous works on upper limb muscle synergies in clinical environment is needed to i) summarize the main findings so far, ii) highlight the barriers limiting their use in clinical applications, and iii) suggest future research directions needed for facilitating translation of experimental research to clinical scenarios.

METHODS

Articles in which muscle synergies were used to analyze and assess upper limb function in neurological impairments were reviewed. The literature research was conducted in Scopus, PubMed, and Web of Science. Experimental protocols (e.g., the aim of the study, number and type of participants, number and type of muscles, and tasks), methods (e.g., muscle synergy models and synergy extraction methods, signal processing methods), and the main findings of eligible studies were reported and discussed.

RESULTS

383 articles were screened and 51 were selected, which involved a total of 13 diseases and 748 patients and 1155 participants. Each study investigated on average 15 ± 10 patients. Four to forty-one muscles were included in the muscle synergy analysis. Point-to-point reaching was the most used task. The preprocessing of EMG signals and algorithms for synergy extraction varied among studies, and non-negative matrix factorization was the most used method. Five EMG normalization methods and five methods for identifying the optimal number of synergies were used in the selected papers. Most of the studies report that analyses on synergy number, structure, and activations provide novel insights on the physiopathology of motor control that cannot be gained with standard clinical assessments, and suggest that muscle synergies may be useful to personalize therapies and to develop new therapeutic strategies. However, in the selected studies synergies were used only for assessment; different testing procedures were used and, in general, study-specific modifications of muscle synergies were observed; single session or longitudinal studies mainly aimed at assessing stroke (71% of the studies), even though other pathologies were also investigated. Synergy modifications were either study-specific or were not observed, with few analyses available for temporal coefficients. Thus, several barriers prevent wider adoption of muscle synergy analysis including a lack of standardized experimental protocols, signal processing procedures, and synergy extraction methods. A compromise in the design of the studies must be found to combine the systematicity of motor control studies and the feasibility of clinical studies. There are however several potential developments that might promote the use of muscle synergy analysis in clinical practice, including refined assessments based on synergistic approaches not allowed by other methods and the availability of novel models. Finally, neural substrates of muscle synergies are discussed, and possible future research directions are proposed.

CONCLUSIONS

This review provides new perspectives about the challenges and open issues that need to be addressed in future work to achieve a better understanding of motor impairments and rehabilitative therapy using muscle synergies. These include the application of the methods on wider scales, standardization of procedures, inclusion of synergies in the clinical decisional process, assessment of temporal coefficients and temporal-based models, extensive work on the algorithms and understanding of the physio-pathological mechanisms of pathology, as well as the application and adaptation of synergy-based approaches to various rehabilitative scenarios for increasing the available evidence.

Novel clinically-relevant assessment of upper extremity movement using depth sensors

BACKGROUND

For individuals post-stroke, home-based programs are necessary to deliver additional hours of therapy outside of the limited time in the clinic. Virtual reality (VR)-based approaches show modest outcomes in improving client function when delivered in the home. The movement sensors used in these VR-based approaches, such as the Microsoft Kinect® have been validated against gold standards tools but have not been used as an assessment of upper extremity movement quality in the stroke population.

OBJECTIVES

The purpose of this study was to explore the use of a movement sensor paired with a VR-based intervention to assess upper extremity movement for individuals post-stroke.

METHODS

Movement data captured with the Microsoft Kinect® from four separate studies were aggregated for analysis (n = 8 individuals post-stroke, n = 30 individuals without disabilities). For all participants, the skeletal data (x, y, z coordinates for 15 tracked joints) for each game play session were processed in MatLab and movement variables (normalized jerk, movement path ratio, average path sway) were calculated using an OPTICS density-based cluster algorithm.

RESULTS

Data from the 30 healthy individuals created a normative baseline for the three kinematic variables. Individuals post-stroke were less efficient and had more jerky movements in both upper extremities as compared to healthy individuals.

CONCLUSION

It is feasible to use a movement sensor paired with a VR-based intervention to quantify and qualify upper extremity movement for individuals post-stroke. Further research with a larger cohort is necessary to establish clinical sensitivity and specificity.

Technology-Based Compensation Assessment and Detection of Upper Extremity Activities of Stroke Survivors: Systematic Review

Background

Upper extremity (UE) impairment affects up to 80% of stroke survivors and accounts for most of the rehabilitation after discharge from the hospital release. Compensation, commonly used by stroke survivors during UE rehabilitation, is applied to adapt to the loss of motor function and may impede the rehabilitation process in the long term and lead to new orthopedic problems. Intensive monitoring of compensatory movements is critical for improving the functional outcomes during rehabilitation.

Objective

This review analyzes how technology-based methods have been applied to assess and detect compensation during stroke UE rehabilitation.

Methods

We conducted a wide database search. All studies were independently screened by 2 reviewers (XW and YF), with a third reviewer (BY) involved in resolving discrepancies. The final included studies were rated according to their level of clinical evidence based on their correlation with clinical scales (with the same tasks or the same evaluation criteria). One reviewer (XW) extracted data on publication, demographic information, compensation types, sensors used for compensation assessment, compensation measurements, and statistical or artificial intelligence methods. Accuracy was checked by another reviewer (YF). Four research questions were presented. For each question, the data were synthesized and tabulated, and a descriptive summary of the findings was provided. The data were synthesized and tabulated based on each research question.

Results

A total of 72 studies were included in this review. In all, 2 types of compensation were identified: disuse of the affected upper limb and awkward use of the affected upper limb to adjust for limited strength, mobility, and motor control. Various models and quantitative measurements have been proposed to characterize compensation. Body-worn technology (25/72, 35% studies) was the most used sensor technology to assess compensation, followed by marker-based motion capture system (24/72, 33% studies) and marker-free vision sensor technology (16/72, 22% studies). Most studies (56/72, 78% studies) used statistical methods for compensation assessment, whereas heterogeneous machine learning algorithms (15/72, 21% studies) were also applied for automatic detection of compensatory movements and postures.

Conclusions

This systematic review provides insights for future research on technology-based compensation assessment and detection in stroke UE rehabilitation. Technology-based compensation assessment and detection have the capacity to augment rehabilitation independent of the constant care of therapists. The drawbacks of each sensor in compensation assessment and detection are discussed, and future research could focus on methods to overcome these disadvantages. It is advised that open data together with multilabel classification algorithms or deep learning algorithms could benefit from automatic real time compensation detection. It is also recommended that technology-based compensation predictions be explored.

The Effect of Robot-Mediated Virtual Reality Gaming on Upper Limb Spasticity Poststroke: A Randomized-Controlled Trial

Objective: Stroke is a common reason for motor disability and is often associated with spasticity and poor motor function of the upper limbs involved. Spasticity management is important to accelerate motor recovery. The objective of this study was to investigate the effects of training with robot-mediated virtual reality gaming on upper limb spasticity and motor functions in individuals with chronic stroke. Materials and Methods: A total of 40 Saudi individuals with chronic stroke were involved in this study. Participants were randomly assigned to two groups. The experimental group received conventional physiotherapy and training with robot-mediated virtual reality gaming, and the control group received only conventional physiotherapy. Outcomes were measured by the Action Research Arm Test (ARAT), Wolf Motor Function Test (WMFT), WMFT-Time, Modified Ashworth Scale (MAS), Active Range of Motion (AROM) of multiple joints of the upper limb, and Handgrip Strength (HGS). The scores of all the outcome measures were recorded at baseline and after the completion of the treatment. Results: Individuals with stroke in the experimental group had a better improvement in most measured variables (AROM of shoulder abduction, elbow supination and wrist extension, WMFT-Time, HGS, ARAT, WMFT, and MAS) compared with the control group after the completion of the treatment. Both groups showed significant improvement in all the measured variables after completion of the treatment, except in MAS for wrist flexors in the control group. Conclusion: Training with robot-mediated virtual reality gaming was effective in modulating spasticity and improving the motor functions of the affected upper limbs in individuals with chronic stroke. This study was registered in ClinicalTrial.gov (NCT05069480).

Kinematic descriptions of upper limb function using simulated tasks in activities of daily living after stroke

Assessment of upper limb function poststroke is critical for clinical management and determining the efficacy of interventions. We designed a unilateral upper limb task to simulate activities of daily living to examine how chronic stroke survivors manage reaching, grasping and handling skills simultaneously to perform the functional task using kinematic analysis. The aim of the study was to compare the motor strategies for performing a functional task between paretic and nonparetic arms. Sixteen chronic stroke survivors were instructed to control an ergonomic spoon to transfer liquid from a large bowl to a small bowl using paretic or nonparetic arm. Kinematic data were recorded using a Vicon motion capture system. Outcome measures included movement duration, relative timing, path length, joint excursions, and trial-to-trial variability. Results showed that movement duration, spoon path length, and trunk path length increased significantly when participants used paretic arm to perform the task. Participants tended to reduce shoulder and elbow excursions, and increase trunk excursions to perform the task with paretic arm and altered the relative timing of the task. Although participants used different motor strategies to perform the task with their paretic arms, we did not find the significant differences in trial-to trial variability of joint excursions between paretic and nonparetic arms. The results revealed differences in temporal and spatial aspects of motor strategies between paretic and nonparetic arms. Clinicians should explore the underlying causes of pathological movement patterns and facilitate preferred movement patterns of paretic arm.

The 4-Element Movement System Model to Guide Physical Therapist Education, Practice, and Movement-Related Research

The movement system has been adopted as the key identity for the physical therapy profession, and recognition of physical therapists' primary expertise in managing movement dysfunction is an important achievement. However, existing movement system models seem inadequate for guiding education, practice, or research. Lack of a clear, broadly applicable model may hamper progress in physical therapists actually adopting this identity. We propose a model composed of 4 primary elements essential to all movement: motion, force, energy, and control. Although these elements overlap and interact, they can each be examined and tested with some degree of specificity. The proposed 4-element model incorporates specific guidance for visual, qualitative assessment of movement during functional tasks that can be used to develop hypotheses about movement dysfunction and serve as a precursor to more quantitative tests and measures. Human movement always occurs within an environmental context and is affected by personal factors, and these concepts are represented within the model. The proposed scheme is consistent with other widely used models within the profession, such as the International Classification of Functioning, Disability and Health and the Patient Management Model. We demonstrate with multiple examples how the model can be applied to a broad spectrum of patients across the lifespan with musculoskeletal, neurologic, and cardiopulmonary disorders.

Does exposure to startle impact voluntary reaching movements in individuals with severe-to-moderate stroke?

When movements of individuals with stroke (iwS) are elicited by startling acoustic stimulus (SAS), reaching movements are faster, further, and directed away from the body. However, these startle-evoked movements also elicit task-inappropriate flexor activity, raising concerns that chronic exposure to startle might also induce heightened flexor activity during voluntarily elicited movement. The objective of this study is to evaluate the impact of startle exposure on voluntary movements during point-to-point reaching in individuals with moderate and severe stroke. We hypothesize that startle exposure will increase task-inappropriate activity in flexor muscles, which will be associated with worse voluntarily initiated reaching performance (e.g. decreased distance, displacement, and final accuracy). Eleven individuals with moderate-to-severe stroke (UEFM = 8–41/66 and MAS = 0–4/4) performed voluntary point-to-point reaching with 1/3 of trials elicited by an SAS. We used electromyography to measure activity in brachioradialis (BR), biceps (BIC), triceps lateral head (TRI), pectoralis (PEC), anterior deltoid (AD), and posterior deltoid (PD). Conversely to our hypothesis, exposure to startle did not increase abnormal flexion but rather antagonist activity in the elbow flexors and shoulder horizontal adductors decreased, suggesting that abnormal flexor/extensor co-contraction was reduced. This reduction of flexion led to increased reaching distance (18.2% farther), movement onset (8.6% faster), and final accuracy (16.1% more accurate) by the end of the session. This study offers the first evidence that exposure to startle in iwS does not negatively impact voluntary movement; moreover, exposure may improve volitionally activated reaching movements by decreasing abnormal flexion activity.

Upper limb kinematics during the first year after stroke: the stroke arm longitudinal study at the University of Gothenburg (SALGOT)

Background

Reduction of compensation and improved movement quality indicate recovery after stroke. Since clinical measures alone are often inadequate to distinguish between behavioral recovery and compensation, kinematic analysis of functional tasks has been recommended.

Objective

To quantify longitudinal changes and residual deficits in movement performance and quality during the first year after stroke using kinematic analysis of drinking task.

Methods

A total of 56 participants with first ever stroke causing upper extremity impairment were extracted from a non-selected stroke unit cohort (Stroke Arm Longitudinal Study at the University of Gothenburg-SALGOT). Participants needed to able to perform the drinking task with the more-affected arm at least on 2 occasions out of 6 (3 days, 10 days, 4 weeks, and 3, 6, and 12 months) during the first year to be included. A cohort of 60 healthy individuals was used as reference. Longitudinal changes were analyzed using linear mixed models.

Results

Movement time, number of movement units, peak angular velocity of the elbow, peak hand velocity, and trunk displacement improved significantly over the first 3 months with a peak at 6 months. Movement time and peak hand velocity reached levels comparable to healthy at 3 months, but number of movement units, peak elbow angular velocity, trunk displacement, and arm abduction remained different from healthy over the first year after stroke.

Conclusions

Even when the recovery patterns of kinematics follow the known nonlinear pattern, not all kinematic measures reach the levels in par with healthy controls at one year post stroke. Since the number of movement units, peak angular velocity, trunk displacement, and arm abduction remained impaired over the first year, they might be the most suited measures to distinguish behavioral recovery from compensation strategies.

Trial registration

ClinicalTrials: NCT01115348. 4 May 2010. Retrospectively registered.

Movement kinematics and proprioception in post-stroke spasticity: assessment using the Kinarm robotic exoskeleton

Background

Motor impairment after stroke interferes with performance of everyday activities. Upper limb spasticity may further disrupt the movement patterns that enable optimal function; however, the specific features of these altered movement patterns, which differentiate individuals with and without spasticity, have not been fully identified. This study aimed to characterize the kinematic and proprioceptive deficits of individuals with upper limb spasticity after stroke using the Kinarm robotic exoskeleton.

Methods

Upper limb function was characterized using two tasks: Visually Guided Reaching, in which participants moved the limb from a central target to 1 of 4 or 1 of 8 outer targets when cued (measuring reaching function) and Arm Position Matching, in which participants moved the less-affected arm to mirror match the position of the affected arm (measuring proprioception), which was passively moved to 1 of 4 or 1 of 9 different positions. Comparisons were made between individuals with (n = 35) and without (n = 35) upper limb post-stroke spasticity.

Results

Statistically significant differences in affected limb performance between groups were observed in reaching-specific measures characterizing movement time and movement speed, as well as an overall metric for the Visually Guided Reaching task. While both groups demonstrated deficits in proprioception compared to normative values, no differences were observed between groups. Modified Ashworth Scale score was significantly correlated with these same measures.

Conclusions

The findings indicate that individuals with spasticity experience greater deficits in temporal features of movement while reaching, but not in proprioception in comparison to individuals with post-stroke motor impairment without spasticity. Temporal features of movement can be potential targets for rehabilitation in individuals with upper limb spasticity after stroke.

Detecting compensatory movements of stroke survivors using pressure distribution data and machine learning algorithms

BACKGROUND

Compensatory movements are commonly employed by stroke survivors during seated reaching and may have negative effects on their long-term recovery. Detecting compensation is useful for coaching the patient to reduce compensatory trunk movements and improving the motor function of the paretic arm. Sensor-based and camera-based systems have been developed to detect compensatory movements, but they still have some limitations, such as causing object obstructions, requiring complex setups and raising privacy concerns. To overcome these drawbacks, this paper proposes a compensatory movement detection system based on pressure distribution data and is unobtrusive, simple and practical. Machine learning algorithms were applied to classify compensatory movements automatically. Therefore, the purpose of this study was to develop and test a pressure distribution-based system for the automatic detection of compensation movements of stroke survivors using machine learning algorithms.

METHODS

Eight stroke survivors performed three types of reaching tasks (back-and-forth, side-to-side, and up-and-down reaching tasks) with both the healthy side and the affected side. The pressure distribution data were recorded, and five features were extracted for classification. The k-nearest neighbor (k-NN) and support vector machine (SVM) algorithms were applied to detect and categorize the compensatory movements. The surface electromyography (sEMG) signals of nine trunk muscles were acquired to provide a detailed description and explanation of compensatory movements.

RESULTS

Cross-validation yielded high classification accuracies (F1-score>0.95) for both the k-NN and SVM classifiers in detecting compensation movements during all the reaching tasks. In detail, an excellent performance was achieved in discriminating between compensation and noncompensation (NC) movements, with an average F1-score of 0.993. For the multiclass classification of compensatory movement patterns, an average F1-score of 0.981 was achieved in recognizing the NC, trunk lean-forward (TLF), trunk rotation (TR) and shoulder elevation (SE) movements.

CONCLUSIONS

Good classification performance in detecting and categorizing compensatory movements validated the feasibility of the proposed pressure distribution-based system. Reliable classification accuracy achieved by the machine learning algorithms indicated the potential to monitor compensation movements automatically by using the pressure distribution-based system when stroke survivors perform seated reaching tasks.

Development of Sensor-Based Measures of Upper Extremity Interlimb Coordination

The development of motor impairment after the onset of an injury such as stroke may result in long-term compensatory behaviors. Because compensation often evolves in ambient settings (outside the purview of monitoring clinicians), there is a need for quantitative tools capable of accurately detecting the subtleties of compensation and related reduction in interlimb coordination. Improvement in interlimb coordination may serve as a marker of recovery from stroke, and rehabilitation progress. The current study investigates measures of upper extremity interlimb coordination in persons post-stroke and healthy controls. It introduces a novel algorithm for objective characterization of interlimb coordination during the performance of real-world tasks.

Motion analysis for the evaluation of muscle overactivity: A point of view

Muscle overactivity is a general term for pathological increases in muscle activity such as spasticity. It is caused by damage to the central nervous system at the cortical, subcortical or spinal levels, leading to an upper motor neuron syndrome. In routine clinical practice, muscle overactivity, which induces abnormal muscle tone, is usually evaluated by using the Modified Ashworth Scale or the Tardieu Scale. However, both of these scales involve testing in passive conditions that do not always reflect muscle activity during dynamic tasks such as gait or reaching. To determine appropriate treatment strategies, muscle overactivity should be evaluated by using objective measures in dynamic conditions. Instrumental motion analysis systems that include 3-D motion analysis and electromyography are very useful for this purpose. The method can be used to identify patterns of abnormal muscle activity that can be related to abnormal kinematic patterns. It allows for objective and accurate assessment of the effects of treatments to reduce muscle overactivity on the movement to be improved. The aim of this point-of-view article is to describe the utility of instrumental motion analysis and to outline both its numerous advantages in evaluating muscle overactivity and to present the current limitations for its use (e.g., cost, the need for an engineer, errors relating to marker placement and cross talk between electromyography sensors).

Robot-Assisted Reaching Performance of Chronic Stroke and Healthy Individuals in a Virtual Versus a Physical Environment: A Pilot Study

The aim of the current study was to examine the role of environment, whether virtual or physical, on robot-assisted reaching movements in chronic stroke and healthy individuals, within a single session. Twenty-three subjects participated in the current study divided into three groups: nine chronic stroke individuals able to perform a reaching task with no need for the robot assistance, nine chronic stroke individuals who needed robot assistance to complete the reaching task, and five healthy individuals. The task was to reach six target buttons in two identical physical and virtual environments. The outcomes consisted of specific kinematic measures (amount of movement completion without robot assistance, mean speed, peak speed, straightness, and shakiness) and a custom questionnaire to assess how the stroke subjects perceived and experienced the reaching task in both environments. The results showed no differences between the two environments in terms of the outcome measures in any of the groups. Our findings suggest that the choice of environment, whether physical or virtual, is not a key factor in designing a simple robot-assisted reaching task for stroke survivors. Further studies are required for more complex environments and tasks as well as robot-assisted training protocols.

Análise da ativação muscular durante o movimento de alcance nas condições ativo, ativo-assistido e autoassistido em pacientes pós-AVE

RESUMO O Acidente Vascular Encefálico (AVE) é uma patologia que frequentemente causa limitações motoras nos Membros Superiores (MMSS) gerando prejuízos funcionais nos movimentos de alcance. O objetivo do estudo foi analisar o recrutamento muscular do membro superior parético durante três condições de alcance: ativo, ativo-assistido e autoassistido, através de dados eletromiográficos das fibras anteriores do Músculo Deltoide (MD), Bíceps Braquial (BB) e Tríceps Braquial (TB). Estudo do tipo transversal que utilizou como testes clínicos o miniexame do estado mental, escala de equilíbrio de Berg, medida de independência funcional, escala modificada de Ashworth e escala de Fugl-Meyer - seção MMSS. A coleta dos dados eletromiográficos de superfície foi realizada utilizando-se o eletromiógrafo e eletrodos de configuração bipolar da EMG System do Brasil com três canais posicionados nos pontos motores do MD (fibras anteriores), BB e TB de ambos os membros superiores. As variáveis clínicas apresentaram resultados de comprometimento motor, cognitivo e funcional leves. Os dados eletromiográficos mostraram que o MD e TB durante o alcance ativo-assistido contraíram mais que no alcance autoassistido (p<0.05). Os MD e TB apresentaram diferenças significativas durante os movimentos de alcance, enquanto que o músculo BB não mostrou alterações. Entre os diversos tipos de alcance, o ativo-assistido foi o que proporcionou maior ativação muscular. Sugere-se que sejam feitos ensaios clínicos para verificar a eficácia dos treinamentos.

Measuring Habitual Arm Use Post-stroke With a Bilateral Time-Constrained Reaching Task

Background: Spontaneous use of the more-affected arm is a meaningful indicator of stroke recovery. The Bilateral Arm Reaching Test (BART) was previously developed to quantify arm use by measuring arm choice to targets projected over a horizontal hemi-workspace. In order to improve clinical validity, we constrained the available movement time, thereby promoting more spontaneous decision making when selecting between the more-affected and less affected arm during the BART.

Methods: Twenty-two individuals with mild to moderate hemiparesis were tested with the time-based BART in three time-constraint conditions: no-time constraint, medium, and fast conditions. Arm use was measured across three sessions with a 2-week interval in a spontaneous choice block, in which participants were instructed to use either the more-affected or the less-affected arm to reach targets. We tested the effect of time-constraint condition on the more-affected arm use, external validity of the BART with the Actual Amount of Use Test (AAUT), and test-retest reliability across the three test sessions.

Results: The fast condition in the time-based BART showed reduced use of the more-affected arm compared to the no-time constraint condition P < 0.0001) and the medium condition P = 0.0006; Tukey post hoc analysis after mixed-effect linear regression). In addition, the fast condition showed strong correlation with the AAUT r = 0.829, P < 0.001), and excellent test-retest reliability (ICC = 0.960, P < 0.0001).

Conclusion: The revised BART with a time-restricted fast condition provides an objective, accurate, and repeatable measure of spontaneous arm use in individuals with chronic stroke hemiparesis.

Recovery of kinematic arm function in well-performing people with subacute stroke: a longitudinal cohort study

BACKGROUND

Most motor function improvements in people who have experienced strokes occur within the first 3 months. However, individuals showing complete or nearly complete arm function recovery, as assessed using clinical scales, still show certain movement kinematic deficits at 3 months, post-stroke. This study evaluated the changes in upper extremity kinematics, in individuals demonstrating minor clinical motor impairments, 3-12 months post-stroke, and also examined the association between kinematics and the subjects's self-perceived hand abilities during the chronic stage, 12 months post-stroke.

METHODS

Forty-two subjects recovering from strokes and having Fugl-Meyer upper extremity motor assessment scores ≥60 were included from the Stroke Arm Longitudinal Study at the University of Gothenburg (SALGOT). Kinematic analyses of a drinking task, performed 3, 6, and 12 months post-stroke, were compared with kinematic analyses performed in 35 healthy controls. The Stroke Impact Scale-Hand domain was evaluated at the 12-month follow-up.

RESULTS

There were no significant changes in kinematic performance between 3 and 12 months, post-stroke. The patients recovering from stroke showed lower peak elbow extension velocities, and increased shoulder abduction and trunk displacement during drinking than did healthy controls, at all time points. At 12 months, post-stroke, better self-perceived arm functions correlated with improved trunk displacements, movement times, movement units, and time to peak velocity percentages.

CONCLUSION

Kinematic movement deficits, observed at 3 months post-stroke, remained unchanged at 12 months. Movement kinematics were associated with the patient's self-perceived ability to use their more affected hand.

TRIAL REGISTRATION

ClinicalTrials: NCT01115348 .

Kinematic upper extremity performance in people with near or fully recovered sensorimotor function after stroke

Background: Clinical scales for upper extremity motor function may not capture improvement among higher functioning people with stroke. Objective: To describe upper extremity kinematics in people with stroke who score within the upper 10% of the Fugl-Meyer Assessment (FMA-UE) and explore the ceiling effects of the FMA-UE. Design: A cross-sectional study design was used. Participants: People with stroke were included from the Stroke Arm Longitudinal Study at University of Gothenburg together with 30 healthy controls. The first analysis included participants who achieved FMA-UE score > 60 within the first year of stroke (assessed at 3 days, 2 weeks, 4 weeks, 3 months, or 12 months post stroke). The second analysis included participants with submaximal FMA-UE (60-65 points, n = 24) or maximal FMA-UE score (66 points, n = 21) at 3 months post stroke. Measurements: The kinematic analysis of a standardized drinking task included movement time, velocity and strategy, joint angles of the elbow, and shoulder and trunk displacement. Results: The high FMA-UE stroke group showed deficits in seven of eight kinematic variables. The submaximal FMA-UE stroke group was slower, had lower tangential and angular peak velocity, and used more trunk displacement than the controls. In addition, the maximal FMA-UE stroke group showed larger trunk displacement and arm abduction during drinking and lower peak angular velocity of the elbow. Conclusions: Participants with near or fully recovered sensorimotor function after stroke still show deficits in movement kinematics; however, the FMA-UE may not be able to detect these impairments.

Modification of Spastic Stretch Reflexes at the Elbow by Flexion Synergy Expression in Individuals With Chronic Hemiparetic Stroke

OBJECTIVE

To systematically characterize the effect of flexion synergy expression on the manifestation of elbow flexor stretch reflexes poststroke, and to relate these findings to elbow flexor stretch reflexes in individuals without neurologic injury.

DESIGN

Controlled cohort study.

SETTING

Academic medical center.

PARTICIPANTS

Participants (N=20) included individuals with chronic hemiparetic stroke (n=10) and a convenience sample of individuals without neurologic or musculoskeletal injury (n=10).

INTERVENTIONS

Participants with stroke were interfaced with a robotic device that precisely manipulated flexion synergy expression (by regulating shoulder abduction loading) while delivering controlled elbow extension perturbations over a wide range of velocities. This device was also used to elicit elbow flexor stretch reflexes during volitional elbow flexor activation, both in the cohort of individuals with stroke and in a control cohort. In both cases, the amplitude of volitional elbow flexor preactivation was matched to that generated involuntarily during flexion synergy expression.

MAIN OUTCOME MEASURES

The amplitude of short- and long-latency stretch reflexes in the biceps brachii, assessed by electromyography, and expressed as a function of background muscle activation and stretch velocity.

RESULTS

Increased shoulder abduction loading potentiated elbow flexor stretch reflexes via flexion synergy expression in the paretic arm. Compared with stretch reflexes in individuals without neurologic injury, paretic reflexes were larger at rest but were approximately equal to control muscles at matched levels of preactivation.

CONCLUSIONS

Because flexion synergy expression modifies stretch reflexes in involved muscles, interventions that reduce flexion synergy expression may confer the added benefit of reducing spasticity during functional use of the arm.

Prospective clinical study of rehabilitation interventions with multisensory interactive training in patients with cerebral infarction: study protocol for a randomised controlled trial

BACKGROUND

Multisensory interactive training has an increasingly prominent role in stroke rehabilitation. Currently, there is insufficient evidence to demonstrate its efficacy on gait improvement, upper limb and lower limb functional improvement, global motor function and cognitive improvement. A recent Cochrane review confirmed that published studies on virtual reality (VR) training have the limitations of lack of powered sample size, did not evaluate the benefits over a long-term period and lacked trial quality on cognitive function. Another systematic review also concluded that the evidence for the use of VR in gait and balance improvement is limited. This study investigates the effects of multisensory training on gait pattern, upper and lower limb biomechanics, upper limb gross and fine motor functions, and lower limb functional recovery over a medium- to long-term period.

METHODS

Two hundred and twenty-four acute stroke patients will be recruited from a single centre over a period of 6 years. Participants will be randomly assigned to either conventional therapy or conventional therapy with VR training. Outcomes will be recorded at baseline, post intervention and at 3, 6 and 12 months post intervention. Primary outcome measure is gait speed. Secondary outcome measures include kinematic data of upper and lower limb motion, muscle tone, Action Research Arm Test and Short Orientation Memory Concentration Test.

DISCUSSION

The results of this trial will provide in-depth understanding of the effect of early VR interventions on gait, upper and lower limb biomechanics and how it may relate to changes in functional outcomes and muscle tone.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (Registration No.: ChiCTR-IOC-15006064 ). Registered on 11 May 2015.

Self-directed arm therapy at home after stroke with a sensor-based virtual reality training system

BACKGROUND

The effect of rehabilitative training after stroke is dose-dependent. Out-patient rehabilitation training is often limited by transport logistics, financial resources and a lack of motivation/compliance. We studied the feasibility of an unsupervised arm therapy for self-directed rehabilitation therapy in patients' homes.

METHODS

An open-label, single group study involving eleven patients with hemiparesis due to stroke (27 ± 31.5 months post-stroke) was conducted. The patients trained with an inertial measurement unit (IMU)-based virtual reality system (ArmeoSenso) in their homes for six weeks. The self-selected dose of training with ArmeoSenso was the principal outcome measure whereas the Fugl-Meyer Assessment of the upper extremity (FMA-UE), the Wolf Motor Function Test (WMFT) and IMU-derived kinematic metrics were used to assess arm function, training intensity and trunk movement. Repeated measures one-way ANOVAs were used to assess differences in training duration and clinical scores over time.

RESULTS

All subjects were able to use the system independently in their homes and no safety issues were reported. Patients trained on 26.5 ± 11.5 days out of 42 days for a duration of 137 ± 120 min per week. The weekly training duration did not change over the course of six weeks (p = 0.146). The arm function of these patients improved significantly by 4.1 points (p = 0.003) in the FMA-UE. Changes in the WMFT were not significant (p = 0.552). ArmeoSenso based metrics showed an improvement in arm function, a high number of reaching movements (387 per session), and minimal compensatory movements of the trunk while training.

CONCLUSIONS

Self-directed home therapy with an IMU-based home therapy system is safe and can provide a high dose of rehabilitative therapy. The assessments integrated into the system allow daily therapy monitoring, difficulty adaptation and detection of maladaptive motor patterns such as trunk movements during reaching.

TRIAL REGISTRATION

Unique identifier: NCT02098135 .

Upper Limb Outcome Measures Used in Stroke Rehabilitation Studies: A Systematic Literature Review

Background

Establishing which upper limb outcome measures are most commonly used in stroke studies may help in improving consensus among scientists and clinicians.

Objective

In this study we aimed to identify the most commonly used upper limb outcome measures in intervention studies after stroke and to describe domains covered according to ICF, how measures are combined, and how their use varies geographically and over time.

Methods

Pubmed, CinHAL, and PeDRO databases were searched for upper limb intervention studies in stroke according to PRISMA guidelines and477 studies were included.

Results

In studies 48different outcome measures were found. Only 15 of these outcome measures were used in more than 5% of the studies. The Fugl-Meyer Test (FMT)was the most commonly used measure (in 36% of studies). Commonly used measures covered ICF domains of body function and activity to varying extents. Most studies (72%) combined multiple outcome measures: the FMT was often combined with the Motor Activity Log (MAL), the Wolf Motor Function Test and the Action Research Arm Test, but infrequently combined with the Motor Assessment Scale or the Nine Hole Peg Test. Key components of manual dexterity such as selective finger movements were rarely measured. Frequency of use increased over a twelve-year period for the FMT and for assessments of kinematics, whereas other measures, such as the MAL and the Jebsen Taylor Hand Test showed decreased use over time. Use varied largely between countries showing low international consensus.

Conclusions

The results showed a large diversity of outcome measures used across studies. However, a growing number of studies used the FMT, a neurological test with good psychometric properties. For thorough assessment the FMT needs to be combined with functional measures. These findings illustrate the need for strategies to build international consensus on appropriate outcome measures for upper limb function after stroke.