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Background: A key motor skill is the ability to rapidly interact with our dynamic environment. Humans can generate goal-directed motor actions in response to sensory stimulus within ~ 60-200ms. This ability can be impaired after stroke, but most clinical tools lack any measures of rapid feedback processing. Reaching tasks have been used as a framework to quantify impairments in generating motor corrections for individuals with stroke. However, reaching may be inadequate as an assessment tool as repeated reaching can be fatiguing for individuals with stroke. Further, reaching requires many trials to be completed including trials with and without disturbances, and thus, exacerbate fatigue. Here, we describe a novel robotic task to quantify rapid feedback processing in healthy controls and compare this performance with individuals with stroke to (more) efficiently identify impairments in rapid feedback processing. Methods: We assessed a cohort of healthy controls (n = 135) and individuals with stroke (n = 40; Mean 41 days from stroke) in the Fast Feedback Interception Task (FFIT) using the Kinarm Exoskeleton robot. Participants were instructed to intercept a circular white target moving towards them with their hand represented as a virtual paddle. On some trials, the arm could be physically perturbed, the target or paddle could abruptly change location, or the target could change colour requiring the individual to now avoid the target. Results: Most participants with stroke were impaired in reaction time (85%) and end-point accuracy (83%) in at least one of the task conditions, most commonly with target or paddle shifts. Of note, this impairment was also evident in most individuals with stroke when performing the task using their unaffected arm (75%). Comparison with upper limb clinical measures identified moderate correlations with the FFIT. Conclusion: The FFIT was able to identify a high proportion of individuals with stroke as impaired in rapid feedback processing using either the affected or unaffected arms. The task allows many different types of feedback responses to be efficiently assessed in a short amount of time. [ABSTRACT FROM AUTHOR]

Background: Ipsilesional motor impairments of the arm are common after stroke. Previous studies have suggested that severity of contralesional arm impairment and/or hemisphere of lesion may predict the severity of ipsilesional arm impairments. Historically, these impairments have been assessed using clinical scales, which are less sensitive than robot-based measures of sensorimotor performance. Therefore, the objective of this study was to characterize progression of ipsilesional arm motor impairments using a robot-based assessment of motor function over the first 6-months post-stroke and quantify their relationship to (1) contralesional arm impairment severity and (2) stroke-lesioned hemisphere. Methods: A total of 106 participants with first-time, unilateral stroke completed a unilateral assessment of arm motor impairment (visually guided reaching task) using the Kinarm Exoskeleton. Participants completed the assessment along with a battery of clinical measures with both ipsilesional and contralesional arms at 1-, 6-, 12-, and 26-weeks post-stroke. Results: Robotic assessment of arm motor function revealed a higher incidence of ipsilesional arm impairment than clinical measures immediately post-stroke. The incidence of ipsilesional arm impairments decreased from 47 to 14% across the study period. Kolmogorov–Smirnov tests revealed that ipsilesional arm impairment severity, as measured by our task, was not related to which hemisphere was lesioned. The severity of ipsilesional arm impairments was variable but displayed moderate significant relationships to contralesional arm impairment severity with some robot-based parameters. Conclusions: Ipsilesional arm impairments were variable. They displayed relationships of varying strength with contralesional impairments and were not well predicted by lesioned hemisphere. With standard clinical care, 86% of ipsilesional impairments recovered by 6-months post-stroke. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Confidence intervals ranged from 0.84 to 1.41 for Z-Task Scores, and the average confidence interval magnitude was 1.12. There is a confidence interval (CI) of performance associated with every potential score, and so it is equally probable that an individual with a score of 1.64 at a single assessment is actually below (not impaired) or above (impaired) the threshold of 1.64. So, the paragraph will read as follows: Significant change thresholds (SC) and confidence intervals (CI) were estimated by first computing the difference in performance between the first and second assessments and determining the variability of these difference scores. 3 The probability of impairment given an observation, and true change given an initial score. a The cumulative sum of simulated scores (solid black curve), and a confidence interval (CI) of ± 0.95, as simulated for this parameter. [Extracted from the article]

Background: An individual's rapid motor skills allow them to perform many daily activities and are a hallmark of physical health. Although age and sex are both known to affect motor performance, standardized methods for assessing their impact on upper limb function are limited.Methods: Here we perform a cross-sectional study of 643 healthy human participants in two interactive motor tasks developed to quantify sensorimotor abilities, Object-Hit (OH) and Object-Hit-and-Avoid (OHA). The tasks required participants to hit virtual objects with and without the presence of distractor objects. Velocities and positions of hands and objects were recorded by a robotic exoskeleton, allowing a variety of parameters to be calculated for each trial. We verified that these tasks are viable for measuring performance in healthy humans and we examined whether any of our recorded parameters were related to age or sex.Results: Our analysis shows that both OH and OHA can assess rapid motor behaviours in healthy human participants. It also shows that while some parameters in these tasks decline with age, those most associated with the motor system do not. Three parameters show significant sex-related effects in OH, but these effects disappear in OHA.Conclusions: This study suggests that the underlying effect of aging on rapid motor behaviours is not on the capabilities of the motor system, but on the brain's capacity for processing inputs into motor actions. Additionally, this study provides a baseline description of healthy human performance in OH and OHA when using these tasks to investigate age-related declines in sensorimotor ability. [ABSTRACT FROM AUTHOR]

Background: Robotic rehabilitation after stroke provides the potential to increase and carefully control dosage of therapy. Only a small number of studies, however, have examined robotic therapy in the first few weeks post-stroke. In this study we designed robotic upper extremity therapy tasks for the bilateral Kinarm Exoskeleton Lab and piloted them in individuals with subacute stroke. Pilot testing was focused mainly on the feasibility of implementing these new tasks, although we recorded a number of standardized outcome measures before and after training.Methods: Our team developed 9 robotic therapy tasks to incorporate feedback, intensity, challenge, and subject engagement as well as addressing both unimanual and bimanual arm activities. Subacute stroke participants were assigned to a robotic therapy (N = 9) or control group (N = 10) in a matched-group manner. The robotic therapy group completed 1-h of robotic therapy per day for 10 days in addition to standard therapy. The control group participated only in standard of care therapy. Clinical and robotic assessments were completed prior to and following the intervention. Clinical assessments included the Fugl-Meyer Assessment of Upper Extremity (FMA UE), Action Research Arm Test (ARAT) and Functional Independence Measure (FIM). Robotic assessments of upper limb sensorimotor function included a Visually Guided Reaching task and an Arm Position Matching task, among others. Paired sample t-tests were used to compare initial and final robotic therapy scores as well as pre- and post-clinical and robotic assessments.Results: Participants with subacute stroke (39.8 days post-stroke) completed the pilot study. Minimal adverse events occurred during the intervention and adding 1 h of robotic therapy was feasible. Clinical and robotic scores did not significantly differ between groups at baseline. Scores on the FMA UE, ARAT, FIM, and Visually Guided Reaching improved significantly in the robotic therapy group following completion of the robotic intervention. However, only FIM and Arm Position Match improved over the same time in the control group.Conclusions: The Kinarm therapy tasks have the potential to improve outcomes in subacute stroke. Future studies are necessary to quantify the benefits of this robot-based therapy in a larger cohort.Trial Registration: ClinicalTrials.gov, NCT04201613, Registered 17 December 2019-Retrospectively Registered, https://clinicaltrials.gov/ct2/show/NCT04201613 . [ABSTRACT FROM AUTHOR]

Background: Robotic technologies for neurological assessment provide sensitive, objective measures of behavioural impairments associated with injuries or disease such as stroke. Previous robotic tasks to assess proprioception typically involve single limbs or in some cases both limbs. The challenge with these approaches is that they often rely on intact motor function and/or working memory to remember/reproduce limb position, both of which can be impaired following stroke. Here, we examine the feasibility of a single-arm Movement Discrimination Threshold (MDT) task to assess proprioception by quantifying thresholds for sensing passive limb movement without vision. We use a staircase method to adjust movement magnitude based on subject performance throughout the task in order to reduce assessment time. We compare MDT task performance to our previously-designed Arm Position Matching (APM) task. Critically, we determine test-retest reliability of each task in the same population of healthy controls.Method: Healthy participants (N = 21, age = 18-22 years) completed both tasks in the End-Point Kinarm robot. In the MDT task the robot moved the dominant arm left or right and participants indicated the direction moved. Movement displacement was systematically adjusted (decreased after correct answers, increased after incorrect) until the Discrimination Threshold was found. In the APM task, the robot moved the dominant arm and participants "mirror-matched" with the non-dominant arm.Results: Discrimination Threshold for direction of arm displacement in the MDT task ranged from 0.1-1.3 cm. Displacement Variability ranged from 0.11-0.71 cm. Test-retest reliability of Discrimination Threshold based on ICC confidence intervals was moderate to excellent (range, ICC = 0.78 [0.52-0.90]). Interestingly, ICC values for Discrimination Threshold increased to 0.90 [0.77-0.96] (good to excellent) when the number of trials was reduced to the first 50. Most APM parameters had ICC's above 0.80, (range, ICC = [0.86-0.88]) with the exception of variability (ICC = 0.30). Importantly, no parameters were significantly correlated across tasks as Spearman rank correlations across parameter-pairings ranged from - 0.27 to 0.30.Conclusions: The MDT task is a feasible and reliable task, assessing movement discrimination threshold in ~ 17 min. Lack of correlation between the MDT and a position-matching task (APM) indicates that these tasks assess unique aspects of proprioception that are not strongly related in young, healthy individuals. [ABSTRACT FROM AUTHOR]

Background: Traditional clinical assessments are used extensively in neurology; however, they can be coarse, which can also make them insensitive to change. Kinarm is a robotic assessment system that has been used for precise assessment of individuals with neurological impairments. However, this precision also leads to the challenge of identifying whether a given change in performance reflects a significant change in an individual's ability or is simply natural variation. Our objective here is to derive confidence intervals and thresholds of significant change for Kinarm Standard Tests™ (KST).Methods: We assessed participants twice within 15 days on all tasks presently available in KST. We determined the 5-95% confidence intervals for each task parameter, and derived thresholds for significant change. We tested for learning effects and corrected for the false discovery rate (FDR) to identify task parameters with significant learning effects. Finally, we calculated intraclass correlation of type ICC [1, 2] (ICC-C) to quantify consistency across assessments.Results: We recruited an average of 56 participants per task. Confidence intervals for Z-Task Scores ranged between 0.61 and 1.55, and the threshold for significant change ranged between 0.87 and 2.19. We determined that 4/11 tasks displayed learning effects that were significant after FDR correction; these 4 tasks primarily tested cognition or cognitive-motor integration. ICC-C values for Z-Task Scores ranged from 0.26 to 0.76.Conclusions: The present results provide statistical bounds on individual performance for KST as well as significant changes across repeated testing. Most measures of performance had good inter-rater reliability. Tasks with a higher cognitive burden seemed to be more susceptible to learning effects, which should be taken into account when interpreting longitudinal assessments of these tasks. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Spasticity is a common sequela of stroke. Traditional assessment methods include relatively coarse scales that may not capture all characteristics of elevated muscle tone. Thus, the aim of this study was to develop a tool to quantitatively assess post-stroke spasticity in the upper extremity.Methods: Ninety-six healthy individuals and 46 individuals with stroke participated in this study. The kinematic assessment of passive stretch (KAPS) protocol consisted of passive elbow stretch in flexion and extension across an 80° range in 5 movement durations. Seven parameters were identified and assessed to characterize spasticity (peak velocity, final angle, creep (or release), between-arm peak velocity difference, between-arm final angle, between-arm creep, and between-arm catch angle).Results: The fastest movement duration (600 ms) was most effective at identifying impairment in each parameter associated with spasticity. A decrease in peak velocity during passive stretch between the affected and unaffected limb was most effective at identifying individuals as impaired. Spasticity was also associated with a decreased passive range (final angle) and a classic 'catch and release' as seen through between-arm catch and creep metrics.Conclusions: The KAPS protocol and robotic technology can provide a sensitive and quantitative assessment of post-stroke elbow spasticity not currently attainable through traditional measures. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Better diagnostic and prognostic tools are needed to address issues related to early diagnosis and management of concussion across the continuum of aging but particularly in children and adolescents. The purpose of the current study was to evaluate the reliability of robotic technology (KINARM robot) assessments of reaching, position sense, bimanual motor function, visuospatial skills, attention and decision making in youth ice hockey players (ages 10-14). Methods: Thirty-four male children attended two testing days, one week apart. On day one, each subject completed five tasks on the robot with two examiners (alternating examiner sequence); the 2nd examiner followed the same procedure as the 1st immediately afterwards. One consistent examiner tested subjects one week later. This is a testretest reliability study. The robotic tasks characterize sensorimotor and/or cognitive performance; 63 parameters from 5 tasks are reported. Session 1 was the 1st time the subject performed the 5 tasks, session 2 the 2nd time on day 1, and session 3 one week following. Results: Intra-class correlation coefficients ranged from 0.06 to 0.91 and 0.09 to 0.90 for session 1 to 2 and 2 to 3, respectively. Bland-Altman plots showed agreement in a majority of the parameters and a learning effect in 25 % and 24 % of parameters in session 1 vs 2 and 1 vs 3, respectively but none for session 2 vs 3. Of those that showed a learning effect, only 8 % of parameters in session 1 vs 2 and 10 % in session 1 vs 3 had a clinical relevance measure ≥ 0.8. Conclusions: The relative homogeneity of the sample and the effect of learning seen in some of the task parameters appears to have negatively impacted the intra-class correlation coefficients from session 1 to 2, with less impact for 2 to 3. The Bland-Altman analysis supports good absolute reliability in healthy male children with no neurological impairment ranging in age from 10 to 14. The clinically relevant learning effect seen, in a small number of parameters could be addressed by creating a learning effect adjustment factor and/or implementing a practice session, which would eliminate the learning effect. [ABSTRACT FROM AUTHOR]

Background: Stroke is known to alter muscle stretch responses following a perturbation, but little is known about the behavioural consequences of these altered feedback responses. Characterizing impairments in people with stroke in their interactions with the external environment may lead to better long term outcomes. This information can inform therapists about rehabilitation targets and help subjects with stroke avoid injury when moving in the world. Methods: In this study, we developed a postural perturbation task to quantity upper limb function of subjects with subacute stroke (n = 38) and non-disabled controls (n = 74) to make rapid corrective responses with the arm. Subjects were instructed to maintain their hand at a target before and after a mechanical load was applied to the limb. Visual feedback of the hand was removed for half of the trials at perturbation onset. A number of parameters quantified subject performance, and impairment in performance was defined as outside the 95th percentile performance of control subjects. Results: Individual subjects with stroke showed increased postural instability (44%), delayed motor responses (79%), delayed returns towards the spatial target (79%), and greater endpoint errors (74%). Several subjects also showed impairments in the temporal coordination of the elbow and shoulder joints when responding to the perturbation (47%). Interestingly, impairments in task parameters were often found for both arms of individual subjects with stroke (up to 58% for return time). Visual feedback did not improve performance on task parameters except for decreasing endpoint error for all subjects. Significant correlations between task performance and clinical measures were dependent on the arm assessed. Conclusions: This study used a simple postural perturbation task to highlight that subjects with stroke commonly have difficulties responding to mechanical disturbances that may have important implications for their ability to perform daily activities. [ABSTRACT FROM AUTHOR]

Background Existing clinical scores of upper limb function often use observer-based ordinal scales that are subjective and commonly have floor and ceiling effects. The purpose of the present study was to develop an upper limb motor task to assess objectively the ability of participants to select and engage motor actions with both hands. Methods A bilateral robotic system was used to quantify upper limb sensorimotor function of participants with stroke. Participants performed an object hit task that required them to hit virtual balls moving towards them in the workspace with virtual paddles attached to each hand. Task difficulty was initially low, but increased with time by increasing the speed and number of balls in the workspace. Data were collected from 262 control participants and 154 participants with recent stroke. Results Control participants hit ~60 to 90% of the 300 balls with relatively symmetric performance for the two arms. Participants with recent stroke performed the task with most participants hitting fewer balls than 95% of healthy controls (67% of right-affected and 87% of leftaffected strokes). Additionally, nearly all participants (97%) identified with visuospatial neglect hit fewer balls than healthy controls. More detailed analyses demonstrated that most participants with stroke displayed asymmetric performance between their affected and nonaffected limbs with regards to number of balls hit, workspace area covered by the limb and hand speed. Inter-rater reliability of task parameters was high with half of the correlations above 0.90. Significant correlations were observed between many of the task parameters and the Functional Independence Measure and/or the Behavioural Inattention Test. Conclusions As this object hit task requires just over two minutes to complete, it provides an objective and easy approach to quantify upper limb motor function and visuospatial skills following stroke. [ABSTRACT FROM AUTHOR]

Background: Several studies have found correlations between proprioception and visuomotor function during stroke recovery, however two more recent studies have found no correlation. Unfortunately, most of the studies to date have been conducted with clinical assessments of sensation that are observer-based and have poor reliability. We have recently developed new tests to assess position sense and motor function using robotic technology. The present study was conducted to reassess the relationship between position sense and upper limb movement following stroke. Methods: We assessed position sense and motor performance of 100 inpatient stroke rehabilitation subjects and 231 non-disabled controls. All subjects completed quantitative assessments of position sense (arm-position matching task) and motor performance (visually-guided reaching task) using the KINARM robotic device. Subjects also completed clinical assessments including handedness, vision, Purdue Pegboard, Chedoke-McMaster Stroke Assessment-Impairment Inventory and Functional Independence Measure (FIM). Neuroimaging documented lesion localization. Fisher's exact probability tests were used to determine the relationship between performances on the arm-position matching and visually-guided reaching task. Pearson's correlations were conducted to determine the relationship between robotically measured parameters and clinical assessments. Results: Performance by individual subjects on the matching and reaching tasks was statistically independent (Fisher's test, P<0.01). However, performance on the matching and reaching tasks both exhibited relationships with abilities in daily activities as measured by the FIM. Performance on the reaching task also displayed strong relationships with other clinical measures of motor impairment. Conclusions: Our data support the concept that position sense deficits are functionally relevant and point to the importance of assessing proprioceptive and motor impairments independently when planning treatment strategies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Position sense is commonly impaired after stroke. Traditional rehabilitation methods instruct patients to visualize their limbs to compensate for impaired position sense.Objective: Our goal was to evaluate how the use of vision influences impaired position sense.Methods: We examined 177 stroke survivors, an average of 12.7 days (+/- 10 days (SD)) post-stroke, and 133 neurologically-intact controls with a robotic assessment of position sense. The robot positioned one limb (affected) and subjects attempted to mirror-match the position using the opposite limb (unaffected). Subjects completed the test without, then with vision of their limbs. We examined three measures of position sense: variability (Var), contraction/expansion (C/E) and systematic shift (Shift). We classified stroke survivors as having full compensation if they performed the robotic task abnormally without vision but corrected performance within the range of normal with vision. Stroke survivors were deemed to have partial compensation if they performed the task outside the range of normal without and with vision, but improved significantly with vision. Those with absent compensation performed the task abnormally in both conditions and did not improve with vision.Results: Many stroke survivors demonstrated impaired position sense with vision occluded [Var: 116 (66%), C/E: 91 (51%), Shift: 52 (29%)]. Of those stroke survivors with impaired position sense, some exhibited full compensation with vision [Var: 23 (20%), C/E: 42 (46%), Shift: 32 (62%)], others showed partial compensation [Var: 37 (32%), C/E: 8 (9%), Shift: 3 (6%)] and many displayed absent compensation (Var: 56 (48%), C/E: 41 (45%), Shift: 17 (33%)]. Stroke survivors with an affected left arm, visuospatial neglect and/or visual field defects were less likely to compensate for impaired position sense using vision.Conclusions: Our results indicate that vision does not help many stroke survivors compensate for impaired position sense, at least within the current paradigm. This contrasts with historical reports that vision helps compensate for proprioceptive loss following neurologic injuries. [ABSTRACT FROM AUTHOR]

Background: The use of integrated robotic technology to quantify the spectrum of motor symptoms of Parkinson's Disease (PD) has the potential to facilitate objective assessment that is independent of clinical ratings. The purpose of this study is to use the KINARM exoskeleton robot to (1) differentiate subjects with PD from controls and (2) quantify the motor effects of dopamine replacement therapies (DRTs).Methods: Twenty-six subjects (Hoehn and Yahr mean 2.2; disease duration 0.5 to 15 years) were evaluated OFF (after > 12 h of their last dose) and ON their DRTs with the Unified Parkinson's Disease Rating Scale (UPDRS) and the KINARM exoskeleton robot. Bilateral upper extremity bradykinesia, rigidity, and postural stability were quantified using a repetitive movement task to hit moving targets, a passive stretch task, and a torque unloading task, respectively. Performance was compared against healthy age-matched controls.Results: Mean hand speed was 41% slower and 25% fewer targets were hit in subjects with PD OFF medication than in controls. Receiver operating characteristic (ROC) area for hand speed was 0.94. The torque required to stop elbow movement during the passive stretch task was 34% lower in PD subjects versus controls and resulted in an ROC area of 0.91. The torque unloading task showed a maximum displacement that was 29% shorter than controls and had an ROC area of 0.71. Laterality indices for speed and end total torque were correlated to the most affected side. Hand speed laterality index had an ROC area of 0.80 against healthy controls. DRT administration resulted in a significant reduction in a cumulative score of parameter Z-scores (a measure of global performance compared to healthy controls) in subjects with clinically effective levodopa doses. The cumulative score was also correlated to UPDRS scores for the effect of DRT.Conclusions: Robotic assessment is able to objectively quantify parkinsonian symptoms of bradykinesia, rigidity and postural stability similar to the UPDRS. This integrated testing platform has the potential to aid clinicians in the management of PD and help assess the effects of novel therapies. [ABSTRACT FROM AUTHOR]

Background: Robotic technologies to measure human behavior are emerging as a new approach to assess brain function. Recently, we developed a robot-based postural Load Task to assess corrective responses to mechanical disturbances to the arm and found impairments in many participants with stroke compared to a healthy cohort (Bourke et al, J NeuroEngineering Rehabil 12: 7, 2015). However, a striking feature was the large range and skewed distribution of healthy performance. This likely reflects the use of different strategies across the healthy control sample, making it difficult to identify impairments. Here, we developed an intuitive "Unload Task". We hypothesized this task would reduce healthy performance variability and improve the detection of impairment following stroke.Methods: Performance on the Load and Unload Task in the KINARM exoskeleton robot was directly compared for healthy control (n = 107) and stroke (n = 31) participants. The goal was to keep a cursor representing the hand inside a virtual target and return "quickly and accurately" if the robot applied (or removed) an unexpected load to the arm (0.5-1.5 Nm). Several kinematic parameters quantified performance. Impairment was defined as performance outside the 95% of controls (corrected for age, sex and handedness). Task Scores were calculated using standardized parameter scores reflecting overall task performance.Results: The distribution of healthy control performance was smaller and less skewed for the Unload Task compared to the Load Task. Fewer task outliers (outside 99.9 percentile for controls) were removed from the Unload Task (3.7%) compared to the Load Task (7.4%) when developing normative models of performance. Critically, more participants with stroke failed the Unload Task based on Task Score with their affected arm (68%) compared to the Load Task (23%). More impairments were found at the parameter level for the Unload (median = 52%) compared to Load Task (median = 29%).Conclusions: The Unload Task provides an improved approach to assess fast corrective responses of the arm. We found that corrective responses are impaired in persons living with stroke, often equally in both arms. Impairments in generating rapid motor corrections may place individuals at greater risk of falls when they move and interact in the environment. [ABSTRACT FROM AUTHOR]

Background: The KINARM robot produces a granular dataset of participant performance metrics associated with proprioceptive, motor, visuospatial, and executive function. This comprehensive battery includes several behavioral tasks that each generate 9 to 20 metrics of performance. Therefore, the entire battery of tasks generates well over 100 metrics per participant, which can make clinical interpretation challenging. Therefore, we sought to reduce these multivariate data by applying principal component analysis (PCA) to increase interpretability while minimizing information loss.Methods: Healthy right-hand dominant participants were assessed using a bilateral KINARM end-point robot. Subjects (Ns = 101-208) were assessed using 6 behavioral tasks and automated software generated 9 to 20 metrics related to the spatial and temporal aspects of subject performance. Data from these metrics were converted to Z-scores prior to PCA. The number of components was determined from scree plots and parallel analysis, with interpretability considered as a qualitative criterion. Rotation type (orthogonal vs oblique) was decided on a per task basis.Results: The KINARM performance data, per task, was substantially reduced (range 67-79%), while still accounting for a large amount of variance (range 70-82%). The number of KINARM parameters reduced to 3 components for 5 out of 6 tasks and to 5 components for the sixth task. Many components were comprised of KINARM parameters with high loadings and only some cross loadings were observed, which demonstrates a strong separation of components.Conclusions: Complex participant data produced by the KINARM robot can be reduced into a small number of interpretable components by using PCA. Future applications of PCA may offer potential insight into specific patterns of sensorimotor impairment among patient populations. [ABSTRACT FROM AUTHOR]

Background: KINARM end point robotic testing on a range of tasks evaluating sensory, motor and cognitive function in children/adolescents with no neurologic impairment has been shown to be reliable. The objective of this study was to determine whether differences in baseline performance on multiple robotic tasks could be identified between pediatric/adolescent ice hockey players (age range 10-14) with and without a history of concussion.Methods: Three hundred and eighty-five pediatric/adolescent ice hockey players (ages 10-14) completed robotic testing (94 with and 292 without a history of concussion). Five robotic tasks characterized sensorimotor and/or cognitive performance with assessment of reaching, position sense, bimanual motor function, visuospatial skills, attention and decision-making. Seventy-six performance parameters are reported across all tasks.Results: There were no significant differences in performance demonstrated between children with a history of concussion [median number of days since last concussion: 480 (range 8-3330)] and those without across all five tasks. Performance by the children with no history of concussion was used to identify parameter reference ranges that spanned 95 % of the group. All 76 parameter means from the concussion group fell within the normative reference ranges.Conclusions: There are no differences in sensorimotor and/or cognitive performance across multiple parameters using KINARM end point robotic testing in children/adolescents with or without a history of concussion. [ABSTRACT FROM AUTHOR]

Background: Stroke can affect our ability to perform daily activities, although it can be difficult to identify the underlying functional impairment(s). Recent theories highlight the importance of sensory feedback in selecting future motor actions. This selection process can involve multiple processes to achieve a behavioural goal, including selective attention, feature/object recognition, and movement inhibition. These functions are often impaired after stroke, but existing clinical measures tend to explore these processes in isolation and without time constraints. We sought to characterize patterns of post-stroke impairments in a dynamic situation where individuals must identify and select spatial targets rapidly in a motor task engaging both arms. Impairments in generating rapid motor decisions and actions could guide functional rehabilitation targets, and identify potential of individuals to perform daily activities such as driving.Methods: Subjects were assessed in a robotic exoskeleton. Subjects used virtual paddles attached to their hands to hit away 200 virtual target objects falling towards them while avoiding 100 virtual distractors. The inclusion of distractor objects required subjects to rapidly assess objects located across the workspace and make motor decisions about which objects to hit.Results: As many as 78 % of the 157 subjects with subacute stroke had impairments in individual global, spatial, temporal, or hand-specific task parameters relative to the 95 % performance bounds for 309 non-disabled control subjects. Subjects with stroke and neglect (Behavioural Inattention Test score <130; n = 28) were more often impaired in task parameters than other subjects with stroke. Approximately half of subjects with stroke hit proportionally more distractor objects than 95 % of controls, suggesting they had difficulty in attending to and selecting appropriate objects. This impairment was observed for affected and unaffected limbs including some whose motor performance was comparable to controls. The proportion of distractors hit also significantly correlated with the Montreal Cognitive Assessment scores for subjects with stroke (r s  < = - 0.48, P < 10-9).Conclusions: A simple robot-based task identified that many subjects with stroke have impairments in the rapid selection and generation of motor responses to task specific spatial goals in the workspace. [ABSTRACT FROM AUTHOR]

Background: Development of clinical neurological assessments aimed at separating normal from abnormal capabilities requires a comprehensive understanding of how basic neurological functions change (or do not change) with increasing age across adulthood. In the case of proprioception, the research literature has failed to conclusively determine whether or not position sense in the upper limb deteriorates in elderly individuals. The present study was conducted a) to quantify whether upper limb position sense deteriorates with increasing age, and b) to generate a set of normative data that can be used for future comparisons with clinical populations.Methods: We examined position sense in 209 healthy males and females between the ages of 18 and 90 using a robotic arm position-matching task that is both objective and reliable. In this task, the robot moved an arm to one of nine positions and subjects attempted to mirror-match that position with the opposite limb. Measures of position sense were recorded by the robotic apparatus in hand-and joint-based coordinates, and linear regressions were used to quantify age-related changes and percentile boundaries of normal behaviour. For clinical comparisons, we also examined influences of sex (male versus female) and test-hand (dominant versus non-dominant) on all measures of position sense.Results: Analyses of hand-based parameters identified several measures of position sense (Variability, Shift, Spatial Contraction, Absolute Error) with significant effects of age, sex, and test-hand. Joint-based parameters at the shoulder (Absolute Error) and elbow (Variability, Shift, Absolute Error) also exhibited significant effects of age and test-hand.Conclusions: The present study provides strong evidence that several measures of upper extremity position sense exhibit declines with age. Furthermore, this data provides a basis for quantifying when changes in position sense are related to normal aging or alternatively, pathology. [ABSTRACT FROM AUTHOR]