Relationship between visuospatial neglect and kinesthetic deficits after stroke

Validating the measurement of upper limb sensorimotor behavior utilizing a tablet in neurologically intact controls and individuals with chronic stroke

BACKGROUND

Intact sensorimotor function of the upper extremity is essential for successfully performing activities of daily living. After a stroke, upper limb function is often compromised and requires rehabilitation. To develop appropriate rehabilitation interventions, sensitive and objective assessments are required. Current clinical measures often lack precision and technological devices (e.g. robotics) that are objective and sensitive to small changes in sensorimotor function are often unsuitable and impractical for performing home-based assessments. Here we developed a portable, tablet-based application capable of quantifying upper limb sensorimotor function after stroke. Our goal was to validate the developed application and accompanying data analysis against previously validated robotic measures of upper limb function in stroke.

METHODS

Twenty individuals with stroke, twenty age-matched older controls, and twenty younger controls completed an eight-target Visually Guided Reaching (VGR) task using a Kinarm Robotic Exoskeleton and a Samsung Galaxy Tablet. Participants completed eighty trials of the VGR task on each device, where each trial consisted of making a reaching movement to one of eight pseudorandomly appearing targets. We calculated several outcome parameters capturing various aspects of sensorimotor behavior (e.g., Reaction Time, Initial Direction Error, Max Speed, and Movement Time) from each reaching movement, and our analyses compared metric consistency between devices. We used the previously validated Kinarm Standard Analysis (KSA) and a custom in-house analysis to calculate each outcome parameter.

RESULTS

We observed strong correlations between the KSA and our custom analysis for all outcome parameters within each participant group, indicating our custom analysis accurately replicates the KSA. Minimal differences were observed for between-device comparisons (tablet vs. robot) in our outcome parameters. Additionally, we observed similar correlations for each device when comparing the Fugl-Meyer Assessment (FMA) scores of individuals with stroke to tablet-derived metrics, demonstrating that the tablet can capture clinically-based elements of upper limb impairment.

CONCLUSIONS

Tablet devices can accurately assess upper limb sensorimotor function in neurologically intact individuals and individuals with stroke. Our findings validate the use of tablets as a cost-effective and efficient assessment tool for upper-limb function after stroke.

Clinical, Neuroimaging and Robotic Measures Predict Long-Term Proprioceptive Impairments following Stroke

Proprioceptive impairments occur in ~50% of stroke survivors, with 20-40% still impaired six months post-stroke. Early identification of those likely to have persistent impairments is key to personalizing rehabilitation strategies and reducing long-term proprioceptive impairments. In this study, clinical, neuroimaging and robotic measures were used to predict proprioceptive impairments at six months post-stroke on a robotic assessment of proprioception. Clinical assessments, neuroimaging, and a robotic arm position matching (APM) task were performed for 133 stroke participants two weeks post-stroke (12.4 ± 8.4 days). The APM task was also performed six months post-stroke (191.2 ± 18.0 days). Robotics allow more precise measurements of proprioception than clinical assessments. Consequently, an overall APM Task Score was used as ground truth to classify proprioceptive impairments at six months post-stroke. Other APM performance parameters from the two-week assessment were used as predictive features. Clinical assessments included the Thumb Localisation Test (TLT), Behavioural Inattention Test (BIT), Functional Independence Measure (FIM) and demographic information (age, sex and affected arm). Logistic regression classifiers were trained to predict proprioceptive impairments at six months post-stroke using data collected two weeks post-stroke. Models containing robotic features, either alone or in conjunction with clinical and neuroimaging features, had a greater area under the curve (AUC) and lower Akaike Information Criterion (AIC) than models which only contained clinical or neuroimaging features. All models performed similarly with regard to accuracy and F1-score (>70% accuracy). Robotic features were also among the most important when all features were combined into a single model. Predicting long-term proprioceptive impairments, using data collected as early as two weeks post-stroke, is feasible. Identifying those at risk of long-term impairments is an important step towards improving proprioceptive rehabilitation after a stroke.

The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke

BACKGROUND

Robots can generate rich kinematic datasets that have the potential to provide far more insight into impairments than standard clinical ordinal scales. Determining how to define the presence or absence of impairment in individuals using kinematic data, however, can be challenging. Machine learning techniques offer a potential solution to this problem. In the present manuscript we examine proprioception in stroke survivors using a robotic arm position matching task. Proprioception is impaired in 50-60% of stroke survivors and has been associated with poorer motor recovery and longer lengths of hospital stay. We present a simple cut-off score technique for individual kinematic parameters and an overall task score to determine impairment. We then compare the ability of different machine learning (ML) techniques and the above-mentioned task score to correctly classify individuals with or without stroke based on kinematic data.

METHODS

Participants performed an Arm Position Matching (APM) task in an exoskeleton robot. The task produced 12 kinematic parameters that quantify multiple attributes of position sense. We first quantified impairment in individual parameters and an overall task score by determining if participants with stroke fell outside of the 95% cut-off score of control (normative) values. Then, we applied five machine learning algorithms (i.e., Logistic Regression, Decision Tree, Random Forest, Random Forest with Hyperparameters Tuning, and Support Vector Machine), and a deep learning algorithm (i.e., Deep Neural Network) to classify individual participants as to whether or not they had a stroke based only on kinematic parameters using a tenfold cross-validation approach.

RESULTS

We recruited 429 participants with neuroimaging-confirmed stroke (< 35 days post-stroke) and 465 healthy controls. Depending on the APM parameter, we observed that 10.9-48.4% of stroke participants were impaired, while 44% were impaired based on their overall task score. The mean performance metrics of machine learning and deep learning models were: accuracy 82.4%, precision 85.6%, recall 76.5%, and F1 score 80.6%. All machine learning and deep learning models displayed similar classification accuracy; however, the Random Forest model had the highest numerical accuracy (83%). Our models showed higher sensitivity and specificity (AUC = 0.89) in classifying individual participants than the overall task score (AUC = 0.85) based on their performance in the APM task. We also found that variability was the most important feature in classifying performance in the APM task.

CONCLUSION

Our ML models displayed similar classification performance. ML models were able to integrate more kinematic information and relationships between variables into decision making and displayed better classification performance than the overall task score. ML may help to provide insight into individual kinematic features that have previously been overlooked with respect to clinical importance.

Spatial Neglect Subtypes, Definitions and Assessment Tools: A Scoping Review

Objective: The objective of this scoping review was to capture the reported definitions for the subtypes of neglect post stroke and map the range of assessment tools employed for each neglect subtype.

Methods: EMBASE, Emcare, Medline, and psychINFO were searched from database inception. Searching included all allied terms and mesh headings for stroke, spatial neglect, measurement, screening tools, psychometric properties. Two reviewers independently screened studies for inclusion. Primary studies with documented protocols of a spatial neglect tool for adults post stroke, with some aspect of validity or reliability were included. Two reviewers independently reviewed the documented protocols of each tool to determine the underlying subtypes and disagreements were resolved through discussion.

Results: There were 371 articles included with 292 tools used for the screening or diagnosis of neglect. The majority of studies (67%) included a tool that did not specify the neglect subtype being assessed, therefore an analysis of the underlying subtypes for each tool is presented.

Conclusions: There is no consistency with the terms used to refer to the syndrome of spatial neglect with over 200 different terms used within the included studies to refer to the syndrome as a whole or one of its subtypes. It is essential to unify the terminology and definition for each neglect subtype. There are hundreds of neglect tools available, however many are not able to differentiate presenting subtypes. It is important for clinicians and researchers to critically evaluate the neglect tools being used for the screening and diagnosis of neglect.

Neglect syndrome in post-stroke conditions: assessment and treatment (scoping review)

There is no consensus about the definition or most effective treatment for neglect syndrome. The aim of this review was therefore to evaluate the results of trials that investigated different treatment methods for neglect syndrome. A systematic literature search in PubMed and Web of Science databases was performed to identify studies that investigated the effects of neglect therapies. Authors followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Studies were selected by two assayers, and disagreement was resolved by a third reviewer. The literature search identified 202 articles: 19 met the inclusion criteria and were included for data extraction. Thirty-five different kinds of assessments were used in these studies, and 17 treatment methods were applied. Successful treatments were reported at least in some parts of the assessments in 12 studies: mirror therapy (in two trials), transcranial magnetic stimulation, street crossing test in virtual reality, smooth pursuit eye movement training, saccadic eye movement therapy, direct current stimulation, eye patching therapy, prism adaptation treatment, socially assistive pet-type therapeutic robot (PARO), Kinesiological Instrument for Normal and Altered Reaching Movement robotic device therapy, transcutaneous electrical nerve stimulation, and optokinetic stimulation (the last two methods in the same trial). No success was shown in seven trials, which contained not only single treatments but combined ones also. Authors concluded that there are no convincing results for or against any of the different therapies used for neglect syndrome. The quality of the trials is questionable, and the numbers of included patients are small in the trials.

Proprioceptive impairment in unilateral neglect after stroke: A systematic review

Introduction:

Unilateral neglect is a debilitating condition that can occur after stroke and can affect a variety of domains and modalities, including proprioception. Proprioception is a sensorimotor process essential to motor function and is thus important to consider in unilateral neglect. To date, there has not been a comprehensive review of studies examining the various aspects of proprioceptive impairment in unilateral neglect after stroke. This review aimed to determine if people with unilateral neglect have more severe proprioceptive impairments than those without unilateral neglect after stroke.

Methods:

The MEDLINE, Embase, Scopus, CINAHL and Web of Science databases were searched from inception to September 2019 using an a priori search strategy. Two independent reviewers screened abstracts and full texts, and extracted data from the included full texts. A third reviewer resolved disagreements at each step. Risk of bias was assessed using the AXIS Quality Assessment tool.

Results:

A total of 191 abstracts were identified, with 56 eligible for full-text screening. A total of 18 studies were included in the review and provided evidence that people with unilateral neglect have more severe proprioceptive impairment than people without unilateral neglect. This impairment is present in multiple subtypes of unilateral neglect and aspects of proprioception. Most studies had a moderate risk of bias.

Conclusion:

People with unilateral neglect after stroke are more likely to have impaired processing of multiple types of proprioceptive information than those without unilateral neglect. However, the available evidence is limited by the large heterogeneity of assessment tools used to identify unilateral neglect and proprioception. Unilateral neglect and proprioception were rarely assessed comprehensively.

PROSPERO Registration: CRD42018086070.

Standing Balance Strategies and Dual-Task Interference Are Differentially Modulated Across Various Sensory Contexts and Cognitive Tests in Individuals With Chronic Stroke

BACKGROUND AND PURPOSE

Mental tracking and verbal fluency tests have been linked to poor mobility and falls; however, no studies have examined the influence of imposing these tests on standing balance post-stroke. The purpose of this study was to investigate standing balance and cognitive performance across sensory conditions and cognitive tests post-stroke.

METHODS

Ninety-two participants with chronic stroke stood on dual-force platforms while performing various sensory conditions (eyes open/fixed surface, eyes closed/fixed surface, eyes open/sway-referenced surface, and eyes closed/sway-referenced surface) and cognitive tests (no cognitive test, serial subtractions, and verbal fluency). Equilibrium scores were computed based on the anterior-posterior sway angle. The number of correct verbal responses was recorded.

RESULTS

Performing serial subtractions during eyes closed/sway-referenced surface revealed the highest equilibrium score (64.0 ± 13.5), followed by the same sensory condition with added verbal fluency test (59.6 ± 15.1), followed by the single-task condition with no cognitive test (52.6 ± 20.9). The number of correct serial subtractions between seated (7.7 ± 3.7) and standing (7.2 ± 3.5) conditions was similar. A trend for more correct verbal fluency responses emerged when seated (8.1 ± 2.9) than the eyes open/sway-referenced surface condition (7.5 ± 2.8). Greater correct verbal fluency responses emerged when seated (8.6 ± 3.1) than the eyes closed/sway-referenced surface condition (7.8 ± 2.7).

DISCUSSION AND CONCLUSIONS

Standing balance enhancement (higher equilibrium score/better balance) depends on the neuropsychological process targeted and the sensory input available post-stroke. Cognitive dual-task interference emerged for the verbal fluency test during the most attention demanding sensory condition. Cognitive tests that enhance standing balance should be considered in assessments and interventions to evaluate and improve dual-tasking post-stroke.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A321).

Effect of Combined Therapy of Robot and Low-Frequency Repetitive Transcranial Magnetic Stimulation on Hemispatial Neglect in Stroke Patients

Objective

To investigate the effect of upper limb rehabilitation combining robot with low-frequency repetitive transcranial magnetic stimulation (rTMS) on unilateral spatial neglect in stroke patients.

Methods

Patients who had hemispatial neglect after right hemisphere stroke were randomly divided into rTMS only group, robot only group, and combined group. All groups received conventional neglect therapy and additional treatment for each group. rTMS group received rTMS therapy. Robot group received robot therapy, while combined group received both therapies. The effect of therapy was assessed with Motor-Free Visual Perception Test-3 (MVPT-3), line bisection test, star cancellation test, Catherine Bergego Scale (CBS), Mini-Mental State Examination (MMSE), and the Korean version of Modified Barthel Index (K-MBI). These measurements were evaluated before and after treatment.

Results

For each group, 10 patients were recruited. There were no significant differences in baseline characteristics or initial values among the three groups. Two weeks after the therapy, all groups showed significant improvement in MVPT-3, line bisection test, star cancellation test, CBS, MMSE, and K-MBI. However, changes in measurements showed no significant differences among groups.

Conclusion

Treatment effect of the combined therapy of robotic therapy and low-frequency rTMS therapy for hemispatial neglect was not statistically different from that of each single treatment.

Results

of this study did not prove the superiority of any of the three treatments. Further study with large number of patients is needed to evaluate the superiority of these treatments.

Sensorimotor Robotic Measures of tDCS- and HD-tDCS-Enhanced Motor Learning in Children

Transcranial direct-current stimulation (tDCS) enhances motor learning in adults. We have demonstrated that anodal tDCS and high-definition (HD) tDCS of the motor cortex can enhance motor skill acquisition in children, but behavioral mechanisms remain unknown. Robotics can objectively quantify complex sensorimotor functions to better understand mechanisms of motor learning. We aimed to characterize changes in sensorimotor function induced by tDCS and HD-tDCS paired motor learning in children within an interventional trial. Healthy, right-handed children (12–18 y) were randomized to anodal tDCS, HD-tDCS, or sham targeting the right primary motor cortex during left-hand Purdue pegboard test (PPT) training over five consecutive days. A KINARM robotic protocol quantifying proprioception, kinesthesia, visually guided reaching, and an object hit task was completed at baseline, posttraining, and six weeks later. Effects of the treatment group and training on changes in sensorimotor parameters were explored. Twenty-four children (median 15.5 years, 52% female) completed all measures. Compared to sham, both tDCS and HD-tDCS demonstrated enhanced motor learning with medium effect sizes. At baseline, multiple KINARM measures correlated with PPT performance. Following training, visually guided reaching in all groups was faster and required less corrective movements in the trained arm (H(2) = 9.250, p = 0.010). Aspects of kinesthesia including initial direction error improved across groups with sustained effects at follow-up (H(2) = 9.000, p = 0.011). No changes with training or stimulation were observed for position sense. For the object hit task, the HD-tDCS group moved more quickly with the right hand compared to sham at posttraining (χ²(2) = 6.255, p = 0.044). Robotics can quantify complex sensorimotor function within neuromodulator motor learning trials in children. Correlations with PPT performance suggest that KINARM metrics can assess motor learning effects. Understanding how tDCS and HD-tDCS enhance motor learning may be improved with robotic outcomes though specific mechanisms remain to be defined. Exploring mechanisms of neuromodulation may advance therapeutic approaches in children with cerebral palsy and other disabilities.

Vision of the upper limb fails to compensate for kinesthetic impairments in subacute stroke

Kinesthesia is an essential component of proprioception allowing for perception of movement. Due to neural injury, such as stroke, kinesthesia can be significantly impaired. Throughout neurorehabilitation, clinicians may encourage use of vision to guide limb movement to retrain impaired kinesthesia. However, little evidence exists that vision improves kinesthetic performance after stroke. We examined behavioral and neuroanatomical characteristics of kinesthesia post-stroke to determine if these impairments improve with vision. Stroke subjects (N = 281) performed a robotic kinesthetic matching task (KIN) without and with vision at ∼10 days post-stroke. A robotic exoskeleton moved the stroke-affected arm while subjects mirror-matched the movement with the opposite arm. Performance was compared to 160 controls. Spatial and temporal parameters were used to quantify kinesthetic performance. A Kinesthetic Task Score was calculated to determine overall performance on KIN without and with vision. Acute stroke imaging (N = 236) was collected to determine commonalities in lesion characteristics amongst kinesthetic impairment groups. Forty-eight percent (N = 135) of subjects had post-stroke impairment in kinesthesia both without and with vision. Only 19% (N = 52) improved to control-level performance with vision. Of the 48% of subjects that failed to improve with vision, many (N = 77, 57%) had neglect and/or field deficits. Notably 58 subjects (43%) did not have these deficits and still failed to improve with vision. Subjects who failed to improve with vision often had lesions affecting corticospinal tracts, insula, and parietal cortex, specifically the supramarginal gyrus and inferior parietal lobule. Many individuals could not use vision of the limb to correct for impaired kinesthesia after stroke. Subjects that failed to improve kinesthesia with vision had lesions affecting known sensorimotor integration areas. Our results suggest that integration of spatial information is impaired in many individuals post-stroke, particularly after parietal cortex damage. The result is a disconnect between kinesthetic and visuomotor processing necessary for visual limb guidance.

Smallest real differences for robotic measures of upper extremity function after stroke: Implications for tracking recovery

Introduction

Measurements from upper limb rehabilitation robots could guide therapy progression, if a robotic assessment’s measurement error was small enough to detect changes occurring on a time scale of a few days. To guide this determination, this study evaluated the smallest real differences of robotic measures, and of clinical outcome assessments predicted from these measures.

Methods

A total of nine older chronic stroke survivors took part in 12-week study with an upper-limb end-effector robot. Fourteen robotic measures were extracted, and used to predict Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and Action Research Arm Test (ARAT) scores using multilinear regression. Smallest real differences and intraclass correlation coefficients were computed for the robotic measures and predicted clinical outcomes, using data from seven baseline sessions.

Results

Smallest real differences of robotic measures ranged from 8.8% to 26.9% of the available range. Smallest real differences of predicted clinical assessments varied widely depending on the regression model (1.3 to 36.2 for FMA-UE, 1.8 to 59.7 for ARAT), and were not strongly related to a model’s predictive performance or to the smallest real differences of the model inputs. Models with acceptable predictive performance as well as low smallest real differences were identified.

Conclusions

Smallest real difference evaluations suggest that using robotic assessments to guide therapy progression is feasible.

A composite robotic-based measure of upper limb proprioception

Background

Proprioception is the sense of the position and movement of our limbs, and is vital for executing coordinated movements. Proprioceptive disorders are common following stroke, but clinical tests for measuring impairments in proprioception are simple ordinal scales that are unreliable and relatively crude. We developed and validated specific kinematic parameters to quantify proprioception and compared two common metrics, Euclidean and Mahalanobis distances, to combine these parameters into an overall summary score of proprioception.

Methods

We used the KINARM robotic exoskeleton to assess proprioception of the upper limb in subjects with stroke (N = 285. Mean days post-stroke = 12 ± 15). Two aspects of proprioception (position sense and kinesthetic sense) were tested using two mirror-matching tasks without vision. The tasks produced 12 parameters to quantify position sense and eight to quantify kinesthesia. The Euclidean and Mahalanobis distances of the z-scores for these parameters were computed each for position sense, kinesthetic sense, and overall proprioceptive function (average score of position and kinesthetic sense).

Results

A high proportion of stroke subjects were impaired on position matching (57%), kinesthetic matching (65%), and overall proprioception (62%). Robotic tasks were significantly correlated with clinical measures of upper extremity proprioception, motor impairment, and overall functional independence. Composite scores derived from the Euclidean distance and Mahalanobis distance showed strong content validity as they were highly correlated (r = 0.97–0.99).

Conclusions

We have outlined a composite measure of upper extremity proprioception to provide a single continuous outcome measure of proprioceptive function for use in clinical trials of rehabilitation. Multiple aspects of proprioception including sense of position, direction, speed, and amplitude of movement were incorporated into this measure. Despite similarities in the scores obtained with these two distance metrics, the Mahalanobis distance was preferred.

Spanish Transcultural Adaptation and Validity of the Behavioral Inattention Test

Objective

To adapt, validate, and translate the Behavioral Inattention Test as an assessment tool for Spanish individuals with unilateral spatial neglect.

Design

A cross-sectional descriptive study.

Setting

University laboratories.

Participants

A sample of 75 Spanish stroke patients and 18 healthy control subjects.

Interventions

Not applicable.

Main Outcome Measures

The Behavioral Inattention Test.

Results

The Spanish version of the Behavioral Inattention Test shows a high degree of reliability both in the complete test (α = .90) and in the conventional (α = .93) and behavioral subtests (α = .75). The concurrent validity between the total conventional and behavioral scores was high (r = −.80; p < 0.001). Significant differences were found between patients with and without unilateral spatial neglect (p < 0.001). In the comparison between right and left damaged sides, differences were found in all items, except for article reading (p = 0.156) and card sorting (p = 0.117).

Conclusions

This measure is a useful tool for evaluating unilateral spatial neglect as it provides information on everyday problems. The BIT discriminates between stroke patients with and without unilateral spatial neglect. This measure constitutes a reliable tool for the diagnosis, planning, performance, and design of specific treatment programs intended to improve the functionality and quality of life of people with unilateral spatial neglect.

White matter lesions and cognitive impairment may be related to recovery from unilateral spatial neglect after stroke

BACKGROUND

Unilateral spatial neglect (USN) is frequently found in ischemic stroke patients. Because USN is related to poor functional outcomes, evaluating recovery from USN after stroke is critical.

METHODS

Patients with acute ischemic stroke with lesions in the right cerebral hemisphere on MRI and exhibiting left USN were administered the Behavior Inattention Test (BIT) at 1 and 3weeks after admission. BIT improvement was defined as a ≥1-point increase in ≥4 of the 6 BIT subtests from 1 to 3weeks, or a total BIT score ≥131 at 3weeks. Factors associated with improvement of left USN were analyzed.

RESULTS

Eighteen patients (8 men; mean age, 70±12years) were enrolled in this study. BIT was performed at 5.3±0.7 and 18.2±0.7days after admission. Twelve patients were classified to the improvement (I) group, and 6 to the non-improvement (NI) group. BIT scores increased substantially from 76.6±40.5 in the acute phase to 109.2±43.3 in the subacute phase. The I group displayed higher BIT scores than the NI group in both acute and subacute phases (P<0.01 each). The degree of white matter lesions on the Fazekas scale was lower in the I group (0.6±0.7) than in the NI group (1.7±1.2, P=0.028). Increased BIT scores correlated significantly with increased Mini Mental State Examination scores (r=0.487, P=0.040).

CONCLUSIONS

Amelioration of left USN might be related to white matter lesions and cognitive impairment. Sample size in the current study was small, limiting the generalizability of results, and larger studies are warranted in the future.

Inter-rater reliability of kinesthetic measurements with the KINARM robotic exoskeleton

Background

Kinesthesia (sense of limb movement) has been extremely difficult to measure objectively, especially in individuals who have survived a stroke. The development of valid and reliable measurements for proprioception is important to developing a better understanding of proprioceptive impairments after stroke and their impact on the ability to perform daily activities. We recently developed a robotic task to evaluate kinesthetic deficits after stroke and found that the majority (~60%) of stroke survivors exhibit significant deficits in kinesthesia within the first 10 days post-stroke. Here we aim to determine the inter-rater reliability of this robotic kinesthetic matching task.

Methods

Twenty-five neurologically intact control subjects and 15 individuals with first-time stroke were evaluated on a robotic kinesthetic matching task (KIN). Subjects sat in a robotic exoskeleton with their arms supported against gravity. In the KIN task, the robot moved the subjects’ stroke-affected arm at a preset speed, direction and distance. As soon as subjects felt the robot begin to move their affected arm, they matched the robot movement with the unaffected arm. Subjects were tested in two sessions on the KIN task: initial session and then a second session (within an average of 18.2 ± 13.8 h of the initial session for stroke subjects), which were supervised by different technicians. The task was performed both with and without the use of vision in both sessions. We evaluated intra-class correlations of spatial and temporal parameters derived from the KIN task to determine the reliability of the robotic task.

Results

We evaluated 8 spatial and temporal parameters that quantify kinesthetic behavior. We found that the parameters exhibited moderate to high intra-class correlations between the initial and retest conditions (Range, r-value = [0.53–0.97]).

Conclusions

The robotic KIN task exhibited good inter-rater reliability. This validates the KIN task as a reliable, objective method for quantifying kinesthesia after stroke.

Kinesthetic deficits after perinatal stroke: robotic measurement in hemiparetic children

Background

While sensory dysfunction is common in children with hemiparetic cerebral palsy (CP) secondary to perinatal stroke, it is an understudied contributor to disability with limited objective measurement tools. Robotic technology offers the potential to objectively measure complex sensorimotor function but has been understudied in perinatal stroke. The present study aimed to quantify kinesthetic deficits in hemiparetic children with perinatal stroke and determine their association with clinical function.

Methods

Case–control study. Participants were 6–19 years of age. Stroke participants had MRI confirmed unilateral perinatal arterial ischemic stroke or periventricular venous infarction, and symptomatic hemiparetic cerebral palsy. Participants completed a robotic assessment of upper extremity kinesthesia using a robotic exoskeleton (KINARM). Four kinesthetic parameters (response latency, initial direction error, peak speed ratio, and path length ratio) and their variabilities were measured with and without vision. Robotic outcomes were compared across stroke groups and controls and to clinical measures of sensorimotor function.

Results

Forty-three stroke participants (23 arterial, 20 venous, median age 12 years, 42% female) were compared to 106 healthy controls. Stroke cases displayed significantly impaired kinesthesia that remained when vision was restored. Kinesthesia was more impaired in arterial versus venous lesions and correlated with clinical measures.

Conclusions

Robotic assessment of kinesthesia is feasible in children with perinatal stroke. Kinesthetic impairment is common and associated with stroke type. Failure to correct with vision suggests sensory network dysfunction.

Sensory tractography and robot-quantified proprioception in hemiparetic children with perinatal stroke

Perinatal stroke causes most hemiparetic cerebral palsy, resulting in lifelong disability. We have demonstrated the ability of robots to quantify sensory dysfunction in hemiparetic children but the relationship between such deficits and sensory tract structural connectivity has not been explored. It was aimed to characterize the relationship between the dorsal column medial lemniscus (DCML) pathway connectivity and proprioceptive dysfunction in children with perinatal stroke. Twenty-nine participants (6-19 years old) with MRI-classified, unilateral perinatal ischemic stroke (14 arterial, 15 venous), and upper extremity deficits were recruited from a population-based cohort and compared with 21 healthy controls. Diffusion tensor imaging (DTI) defined DCML tracts and five diffusion properties were quantified: fractional anisotropy (FA), mean, radial, and axial diffusivities (MD, RD, AD), and fiber count. A robotic exoskeleton (KINARM) tested upper limb proprioception in an augmented reality environment. Correlations between robotic measures and sensory tract diffusion parameters were evaluated. Lesioned hemisphere sensory tracts demonstrated lower FA and higher MD, RD, and AD compared with the non-dominant hemisphere of controls. Dominant (contralesional) hemisphere tracts were not different from controls. Both arterial and venous stroke groups demonstrated impairments in proprioception that correlated with lesioned hemisphere DCML tract diffusion properties. Sensory tract connectivity is altered in the lesioned hemisphere of hemiparetic children with perinatal stroke. A correlation between lesioned DCML tract diffusion properties and robotic proprioceptive measures suggests clinical relevance and a possible target for therapeutic intervention. Hum Brain Mapp 38:2424-2440, 2017. © 2017 Wiley Periodicals, Inc.

Robotic Quantification of Position Sense in Children With Perinatal Stroke

Background Perinatal stroke is the leading cause of hemiparetic cerebral palsy. Motor deficits and their treatment are commonly emphasized in the literature. Sensory dysfunction may be an important contributor to disability, but it is difficult to measure accurately clinically. Objective Use robotics to quantify position sense deficits in hemiparetic children with perinatal stroke and determine their association with common clinical measures. Methods Case-control study. Participants were children aged 6 to 19 years with magnetic resonance imaging-confirmed unilateral perinatal arterial ischemic stroke or periventricular venous infarction and symptomatic hemiparetic cerebral palsy. Participants completed a position matching task using an exoskeleton robotic device (KINARM). Position matching variability, shift, and expansion/contraction area were measured with and without vision. Robotic outcomes were compared across stroke groups and controls and to clinical measures of disability (Assisting Hand Assessment) and sensory function. Results Forty stroke participants (22 arterial, 18 venous, median age 12 years, 43% female) were compared with 60 healthy controls. Position sense variability was impaired in arterial (6.01 ± 1.8 cm) and venous (5.42 ± 1.8 cm) stroke compared to controls (3.54 ± 0.9 cm, P < .001) with vision occluded. Impairment remained when vision was restored. Robotic measures correlated with functional disability. Sensitivity and specificity of clinical sensory tests were modest. Conclusions Robotic assessment of position sense is feasible in children with perinatal stroke. Impairment is common and worse in arterial lesions. Limited correction with vision suggests cortical sensory network dysfunction. Disordered position sense may represent a therapeutic target in hemiparetic cerebral palsy.

Somatosensory Impairments in the Upper Limb Poststroke: Distribution and Association With Motor Function and Visuospatial Neglect

BACKGROUND

A thorough understanding of the presence of different upper-limb somatosensory deficits poststroke and the relation with motor performance remains unclear. Additionally, knowledge about the relation between somatosensory deficits and visuospatial neglect is limited.

OBJECTIVE

To investigate the distribution of upper-limb somatosensory impairments and the association with unimanual and bimanual motor outcomes and visuospatial neglect.

METHODS

A cross-sectional observational study was conducted, including 122 patients within 6 months after stroke (median = 82 days; interquartile range = 57-133 days). Somatosensory measurement included the Erasmus MC modification of the (revised) Nottingham Sensory Assessment (Em-NSA), Perceptual Threshold of Touch (PTT), thumb finding test, 2-point discrimination, and stereognosis subscale of the NSA. Upper-limb motor assessment comprised the Fugl-Meyer assessment, motricity index, Action Research Arm Test, and Adult-Assisting Hand Assessment Stroke. Screening for visuospatial neglect was performed using the Star Cancellation Test.

RESULTS

Upper-limb somatosensory impairments were common, with prevalence rates ranging from 21% to 54%. Low to moderate Spearman ρ correlations were found between somatosensory and motor deficits (r = 0.22-0.61), with the strongest associations for PTT (r = 0.56-0.61) and stereognosis (r = 0.51-0.60). Visuospatial neglect was present in 27 patients (22%). Between-group analysis revealed somatosensory deficits that occurred significantly more often and more severely in patients with visuospatial neglect (P < .05). Results showed consistently stronger correlations between motor and somatosensory deficits in patients with visuospatial neglect (r = 0.44-0.78) compared with patients without neglect (r = 0.08-0.59).

CONCLUSIONS

Somatosensory impairments are common in subacute patients poststroke and are related to motor outcome. Visuospatial neglect was associated with more severe upper-limb somatosensory impairments.

Robot-based assessment of motor and proprioceptive function identifies biomarkers for prediction of functional independence measures

Background

Neurological impairments following stroke impact the ability of individuals to perform daily activities, although the relative impact of individual impairments is not always clear. Recovery of sensorimotor function following stroke can vary widely, from complete recovery to modest or minimal improvements, across individuals. An important question is whether one can predict the amount of recovery based on initial examination of the individual. Robotic technologies are now being used to quantify a range of behavioral capabilities of individuals post-stroke, providing a rich set of biomarkers of sensory and motor dysfunction. The objective of the present study is to use mathematical models to identify which biomarkers best predict the ability of subjects with stroke to perform daily activities before and after rehabilitation.

Methods

The Functional Independence Measure (FIM) was quantified approximately 2 weeks and three months post-stroke in 61 ischemic and 24 hemorrhagic subjects with stroke. At 2 weeks post-stroke, subjects also completed clinical assessments and robotic assessments of sensory and motor function. A computational search algorithm, known as Fast Orthogonal Search, was used to identify the robotic and clinical biomarkers that best estimated Functional Independence Measures.

Results

Clinical and robot-based biomarkers were statistically similar at predicting FIM scores at 2 weeks (r = 0.817 vs. 0.774, respectively) and 3 months (r = 0.643 vs. 0.685, respectively). Importantly, robot-based biomarkers highlighted that parameters related to proprioception were influential for predicting FIM scores at 2 weeks, whereas biomarkers related to bimanual motor function were influential for predicting FIM scores at 3 months.

Conclusions

The present study provides a proof of principle on the use of robot-based biomarkers of sensory and motor dysfunction to estimate present and future FIM scores. The addition of other behavioral tasks will likely increase the accuracy of these predictions, and potentially help guide rehabilitation strategies to maximize functional recovery.