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

The independence of impairments in proprioception and visuomotor adaptation after stroke

BACKGROUND

Proprioceptive impairments are common after stroke and are associated with worse motor recovery and poor rehabilitation outcomes. Motor learning may also be an important factor in motor recovery, and some evidence in healthy adults suggests that reduced proprioceptive function is associated with reductions in motor learning. It is unclear how impairments in proprioception and motor learning relate after stroke. Here we used robotics and a traditional clinical assessment to examine the link between impairments in proprioception after stroke and a type of motor learning known as visuomotor adaptation.

METHODS

We recruited participants with first-time unilateral stroke and controls matched for overall age and sex. Proprioceptive impairments in the more affected arm were assessed using robotic arm position- (APM) and movement-matching (AMM) tasks. We also assessed proprioceptive impairments using a clinical scale (Thumb Localization Test; TLT). Visuomotor adaptation was assessed using a task that systematically rotated hand cursor feedback during reaching movements (VMR). We quantified how much participants adapted to the disturbance and how many trials they took to adapt to the same levels as controls. Spearman's rho was used to examine the relationship between proprioception, assessed using robotics and the TLT, and visuomotor adaptation. Data from healthy adults were used to identify participants with stroke who were impaired in proprioception and visuomotor adaptation. The independence of impairments in proprioception and adaptation were examined using Fisher's exact tests.

RESULTS

Impairments in proprioception (58.3%) and adaptation (52.1%) were common in participants with stroke (n = 48; 2.10% acute, 70.8% subacute, 27.1% chronic stroke). Performance on the APM task, AMM task, and TLT scores correlated weakly with measures of visuomotor adaptation. Fisher's exact tests demonstrated that impairments in proprioception, assessed using robotics and the TLT, were independent from impairments in visuomotor adaptation in our sample.

CONCLUSION

Our results suggest impairments in proprioception may be independent from impairments in visuomotor adaptation after stroke. Further studies are needed to understand factors that influence the relationship between motor learning, proprioception and other rehabilitation outcomes throughout stroke recovery.

Transforming modeling in neurorehabilitation: clinical insights for personalized rehabilitation

Practicing clinicians in neurorehabilitation continue to lack a systematic evidence base to personalize rehabilitation therapies to individual patients and thereby maximize outcomes. Computational modeling- collecting, analyzing, and modeling neurorehabilitation data- holds great promise. A key question is how can computational modeling contribute to the evidence base for personalized rehabilitation? As representatives of the clinicians and clinician-scientists who attended the 2023 NSF DARE conference at USC, here we offer our perspectives and discussion on this topic. Our overarching thesis is that clinical insight should inform all steps of modeling, from construction to output, in neurorehabilitation and that this process requires close collaboration between researchers and the clinical community. We start with two clinical case examples focused on motor rehabilitation after stroke which provide context to the heterogeneity of neurologic injury, the complexity of post-acute neurologic care, the neuroscience of recovery, and the current state of outcome assessment in rehabilitation clinical care. Do we provide different therapies to these two different patients to maximize outcomes? Asking this question leads to a corollary: how do we build the evidence base to support the use of different therapies for individual patients? We discuss seven points critical to clinical translation of computational modeling research in neurorehabilitation- (i) clinical endpoints, (ii) hypothesis- versus data-driven models, (iii) biological processes, (iv) contextualizing outcome measures, (v) clinical collaboration for device translation, (vi) modeling in the real world and (vii) clinical touchpoints across all stages of research. We conclude with our views on key avenues for future investment (clinical-research collaboration, new educational pathways, interdisciplinary engagement) to enable maximal translational value of computational modeling research in neurorehabilitation.

Spiral strapping for improving upper extremity motor functions in individuals with stroke: A randomized controlled trial

BACKGROUND

The rehabilitation process for the upper extremities of individuals with stroke requires therapists to use splints for supportive and corrective purposes. The aim of this study was to assess the effectiveness of spiral strapping in inhibiting spasticity and improving the upper extremity motor functions of individuals with chronic stroke.

METHODS

Forty Saudi individuals aged 50-60 years with chronic stroke participated in this study. Their degrees of spasticity according to the Modified Ashworth Scale ranged across grades 1, 1+, and 2. Participants were randomly assigned to experimental and control groups. Participants in both groups received 1 h of conventional physical therapy for 3 d/wk to improve the motor functions of their upper extremities. In addition, participants in the experimental group wore an upper-limb spiral strapping with a hand splint 10 h/d for 6 d/wk. The treatment program for both groups was delivered for 4 weeks. Changes in the scores of Action Research Arm Test for elbow joint spasticity, active range of motion of the shoulder, elbow, and forearm joints, and hand grip strength were evaluated before and after treatment in both groups.

RESULTS

Significant improvements in all measured variables after treatment were reported in both groups, except for elbow joint spasticity in the control group. The experimental group showed significant post-treatment improvement in the scores for all measured variables compared with the control group.

CONCLUSIONS

Spiral strapping was beneficial in inhibiting mild degrees of spasticity and improving the motor functions of the upper extremities of stroke patients.

Reoptimization of single-joint motor patterns to non-Earth gravity torques induced by a robotic exoskeleton

Gravity is a ubiquitous component of our environment that we have learned to optimally integrate in movement control. Yet, altered gravity conditions arise in numerous applications from space exploration to rehabilitation, thereby pressing the sensorimotor system to adapt. Here, we used a robotic exoskeleton to reproduce the elbow joint-level effects of arbitrary gravity fields ranging from 1g to -1g, passing through Mars- and Moon-like gravities, and tested whether humans can reoptimize their motor patterns accordingly. By comparing the motor patterns of actual arm movements with those predicted by an optimal control model, we show that our participants (N = 61 ) adapted optimally to each gravity-like torque. These findings suggest that the joint-level effects of a large range of gravities can be efficiently apprehended by humans, thus opening new perspectives in arm weight support training in manipulation tasks, whether it be for patients or astronauts.

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.

Design and Development of a Spherical 5-Bar Thumb Exoskeleton Mechanism for Poststroke Rehabilitation

This paper presents the kinematic design and development of a two degree-of-freedom (2DOF) spherical 5-bar thumb exoskeleton to augment the finger individuating grasp exercise robot (FINGER) rehabilitation robot, which assists the index and middle fingers individually in naturalistic grasping. The thumb module expands the capabilities of FINGER, allowing for broader proprioceptive training and assessment of hand function. The design process started by digitizing thumb-grasping motions to the index and the middle fingers separately, recorded from multiple healthy subjects utilizing a motion capture system. Fitting spheres to trajectory data of each subject allowed normalization of all subjects' data to a common center and radius. A two-revolute joint serial-chain mechanism was synthesized (intermediate optimization step) to reach the normalized trajectories. Next, the two resulting grasping trajectories were spatially sampled as targets for the 2DOF spherical 5-bar synthesis. Optimization of the spherical 5-bar included symmetry constraints and cost-function penalties for poor manipulability. The resulting exoskeleton assists both flexion/extension and abduction/adduction of the thumb enabling a wide range of motions. Consistent with FINGER, the parallel structure of the spherical 5-bar places the actuators at the base of the module, allowing for desirable characteristics, including high backdrivability, high controllable bandwidth, and low mechanical impedance. The mechanical design was developed from the kinematic solution, including an adjustable thumb cuff to accommodate different hand sizes. Fit and function of the device were tested on multiple subjects, including survivors of stroke. A proportional-derivative force controller with gravity and friction compensation was implemented to reduce resistance to motion during subject testing.

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.

Neurodata Tracker: Software for computational assessment of hand motor skills based on optical motion capture in a virtual environment

Objectives

Deficits affecting hand motor skills negatively impact the quality of life of patients. The NeuroData Tracker platform has been developed for the objective and precise evaluation of hand motor deficits. We describe the design and development of the platform and analyse the technological feasibility and usability in a relevant clinical setting.

Methods

A software application was developed in Unity (C#) to obtain kinematic data from hand movement tracking by a portable device with two cameras and three infrared sensors (leap motion®). Four exercises were implemented: (a) wrist flexion-extension (b) finger-grip opening-closing (c) finger spread (d) fist opening-closing. The most representative kinematic parameters were selected for each exercise. A script in Python was integrated in the platform to transform real-time kinematic data into relevant information for the clinician. The application was tested in a pilot study comparing the data provided by the tool from ten healthy subjects without any motor impairment and ten patients diagnosed with a stroke with mild to moderate hand motor deficit.

Results

The NeuroData Tracker allowed the parameterization of kinematics of hand movement and the issuance of a report with the results. The comparison of the data obtained suggests the feasibility of the tool for detecting differences between patients and healthy subjects.

Conclusions

This new platform based on optical motion capturing provides objective measurement of hand movement allowing quantification of motor deficits. These findings require further validation of the tool in larger trials to verify its usefulness in the clinical setting.

Technology-assisted assessment of spasticity: a systematic review

BACKGROUND

Spasticity is defined as "a motor disorder characterised by a velocity dependent increase in tonic stretch reflexes (muscle tone) with exaggerated tendon jerks". It is a highly prevalent condition following stroke and other neurological conditions. Clinical assessment of spasticity relies predominantly on manual, non-instrumented, clinical scales. Technology based solutions have been developed in the last decades to offer more specific, sensitive and accurate alternatives but no consensus exists on these different approaches.

METHOD

A systematic review of literature of technology-based methods aiming at the assessment of spasticity was performed. The approaches taken in the studies were classified based on the method used as well as their outcome measures. The psychometric properties and usability of the methods and outcome measures reported were evaluated.

RESULTS

124 studies were included in the analysis. 78 different outcome measures were identified, among which seven were used in more than 10 different studies each. The different methods rely on a wide range of different equipment (from robotic systems to simple goniometers) affecting their cost and usability. Studies equivalently applied to the lower and upper limbs (48% and 52%, respectively). A majority of studies applied to a stroke population (N = 79). More than half the papers did not report thoroughly the psychometric properties of the measures. Analysis identified that only 54 studies used measures specific to spasticity. Repeatability and discriminant validity were found to be of good quality in respectively 25 and 42 studies but were most often not evaluated (N = 95 and N = 78). Clinical validity was commonly assessed only against clinical scales (N = 33). Sensitivity of the measure was assessed in only three studies.

CONCLUSION

The development of a large diversity of assessment approaches appears to be done at the expense of their careful evaluation. Still, among the well validated approaches, the ones based on manual stretching and measuring a muscle activity reaction and the ones leveraging controlled stretches while isolating the stretch-reflex torque component appear as the two promising practical alternatives to clinical scales. These methods should be further evaluated, including on their sensitivity, to fully inform on their potential.

The effect of coupled inhibitory-facilitatory repetitive transcranial magnetic stimulation on shaping early reorganization of the motor network after stroke

Neural plasticity is a major factor driving cortical reorganization after stroke. This study aimed to evaluate functional connectivity (FC) changes in the cortical motor network after coupled inhibitory-facilitatory repetitive transcranial magnetic stimulation (rTMS) treatment and to assess the correlation between FC changes and functional recovery, further characterizing the neural mechanisms underlying the beneficial effects of rTMS. We randomly divided 63 patients with acute stroke into four groups: (1) Group A received coupled inhibitory-facilitatory rTMS [1 Hz over the contralesional primary motor cortex (M1) and 10 Hz over ipsilesional M1]; (2) Group B received a contralesional sham stimulation and ipsilesional 10 Hz stimulation; (3) Group C received a contralesional 1 Hz rTMS and ipsilesional sham stimulation; and (4) Group D received bilateral sham stimulation only. Standardized rehabilitation therapy was performed immediately after rTMS, and each group was treated with their respective treatment modalities for 4 weeks. Twenty-four hours before and after the intervention, participants underwent resting-state functional magnetic resonance imaging. Additional functional assessments were conducted at baseline, after treatment, and at the 3 month follow-up. The rTMS treatment significantly changed the FCs of intra- and inter-hemispheric cortical motor networks in the rTMS groups (A and B) compared with the sham group (Group D). This effect was more pronounced in Group A, which displayed a changed FC between the contralesional postcentral gyrus and contralesional superior parietal gyrus, between the contralesional precentral gyrus and contralesional postcentral gyrus, and between the ipsilesional postcentral gyrus and contralesional superior parietal gyrus, when compared with Groups B and C. Importantly, FC changes were significantly correlated with improvement of motor function. In the early stages of ischemic stroke, coupled rTMS was more conducive to motor recovery by modulating the FCs of intra-hemispheric and inter-hemispheric motor networks. Our results suggested that FC changes were related to motor function recovery for early-stage cerebral stroke patients treated with coupled rTMS. These findings could help to understand the mechanism of coupled rTMS and further the use of this therapy as an adjunct rehabilitation technique in motor recovery.

Reverse Visually Guided Reaching in Patients with Parkinson’s Disease

In addition to motor symptoms such as difficulty in movement initiation and bradykinesia, patients with Parkinson’s disease (PD) display nonmotor executive cognitive dysfunction with deficits in inhibitory control. Preoperative psychological assessments are used to screen for impulsivity that may be worsened by deep brain stimulation (DBS) of the subthalamic nucleus (STN). However, it is unclear whether anti-Parkinson’s therapy, such as dopamine replacement therapy (DRT) or DBS, which has beneficial effects on motor function, adversely affects inhibitory control or its domains. The detrimental effects of STN-DBS are more apparent when tasks test the inhibition of habitual prepotent responses or involve complex cognitive loads. Our goal was to use a reverse visually guided reaching (RVGR) task, a hand-based version of the antisaccade task, to simultaneously measure motor performance and response inhibition in subjects with PD. We recruited 55 healthy control subjects, 26 PD subjects receiving treatment with DRTs, and 7 PD subjects receiving treatment with STN-DBS and DRTs. In the RVGR task, a cursor moved opposite to the subject’s hand movement. This was compared to visually guided reaching (VGR) where the cursor moved in the same direction as the subject’s hand movement. Reaction time, mean speed, and direction errors (in RVGR) were assessed. Reaction times were longer, and mean speeds were slower during RVGR compared to VGR in all three groups but worse in untreated subjects with PD. Treatment with DRTs, DBS, or DBS + DRT improved the reaction time and speed on the RVGR task to a greater extent than VGR. Additionally, DBS or DBS + DRT demonstrated an increase in direction errors, which was correlated with decreased reaction time. These results show that the RVGR task quantifies the benefit of STN-DBS on bradykinesia and the concomitant reduction of proactive inhibitory control. The RVGR task has the potential to be used to rapidly screen for preoperative deficits in inhibitory control and to titrate STN-DBS, to maximize the therapeutic benefits on movement, and minimize impaired inhibitory control.

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).

Assessing visually guided reaching in people with multiple sclerosis with and without self-reported upper limb impairment

The ability to accurately complete goal-directed actions, such as reaching for a glass of water, requires coordination between sensory, cognitive and motor systems. When these systems are impaired, like in people with multiple sclerosis (PwMS), deficits in movement arise. To date, the characterization of upper limb performance in PwMS has typically been limited to results attained from self-reported questionnaires or clinical tools. Our aim was to characterize visually guided reaching performance in PwMS. Thirty-six participants (12 PwMS who reported upper limb impairment (MS-R), 12 PwMS who reported not experiencing upper limb impairment (MS-NR), and 12 age- and sex-matched control participants without MS (CTL)) reached to 8 targets in a virtual environment while seeing a visual representation of their hand in the form of a cursor on the screen. Reaches were completed with both the dominant and non-dominant hands. All participants were able to complete the visually guided reaching task, such that their hand landed on the target. However, PwMS showed noticeably more atypical reaching profiles when compared to control participants. In accordance with these observations, analyses of reaching performance revealed that the MS-R group was more variable with respect to the time it took to initiate and complete their movements compared to the CTL group. While performance of the MS-NR group did not differ significantly from either the CTL or MS-R groups, individuals in the MS-NR group were less consistent in their performance compared to the CTL group. Together these findings suggest that PwMS with and without self-reported upper limb impairment have deficits in the planning and/or control of their movements. We further argue that deficits observed during movement in PwMS who report upper limb impairment may arise due to participants compensating for impaired movement planning processes.

Correlation Between Proprioceptive Impairment and Motor Deficits After Stroke: A Meta-Analysis Review

Introduction: Proprioceptive impairment is a common symptom after stroke. Clarifying how proprioception correlates with motor function after stroke may be helpful in optimizing proprioception-augmented movement training. Previous studies have shown inconsistent findings. A meta-analysis is an optimal method to explore the correlation and identify the factors contributing to these inconsistencies.

Objective: To explore the correlation between proprioception and motor function after stroke through a meta-analysis, taking into account characteristics of the measurements used in these studies.

Methods: We searched multiple databases until November 2021 for eligible studies that measured both proprioception and motor functions in persons with stroke and reported their correlation or data for correlation analysis. A meta-analysis of the correlations was performed. The subgroup analysis and meta-regression were further conducted to investigate potential factors contributing to the heterogeneity of correlation strength, based on the participants' characteristics, proprioception, and motor function measures.

Results: In total, 28 studies comprising of 1,829 participants with stroke were included in the meta-analysis. The overall correlation between proprioception and motor function was significant (r = 0.267, p < 0.05), but there was heterogeneity across studies (I² = 45%, p < 0.05). The results of the subgroup analysis showed proprioception of the axial segment in weight-bearing conditions (r = 0.443, p < 0.05) and upper limb without weight-bearing (r = 0.292, p < 0.05) had a stronger correlation with motor function than proprioception of the lower limb without weight-bearing. The proprioception measured through ipsilateral matching (r = 0.412, p < 0.05) showed a stronger correlation with motor function than through contralateral matching. The International Classification of Functioning, Disability, and Health (ICF) domains of motor function, movement function (r = 0.338, p < 0.05), activity performance (r = 0.239, p < 0.05), and independence (r = 0.319, p < 0.05) showed a stronger correlation with proprioception than with other domains.

Conclusion: There is a significant correlation between proprioception and motor dysfunction after stroke. The proprioception measured in the axial segment under weight-bearing conditions or measured with ipsilateral matching, and motor function, specifically in the ICF domains of movement function, activity performance, and independence showed a positive contribution to the association between proprioception and motor function. The correlation does not imply causation and might be underestimated by attributes of current tests for proprioception and motor function. Further studies are needed to clarify the cause-effect relationship.

Human Weight Compensation With a Backdrivable Upper-Limb Exoskeleton: Identification and Control

Active exoskeletons are promising devices for improving rehabilitation procedures in patients and preventing musculoskeletal disorders in workers. In particular, exoskeletons implementing human limb’s weight support are interesting to restore some mobility in patients with muscle weakness and help in occupational load carrying tasks. The present study aims at improving weight support of the upper limb by providing a weight model considering joint misalignments and a control law including feedforward terms learned from a prior population-based analysis. Three experiments, for design and validation purposes, are conducted on a total of 65 participants who performed posture maintenance and elbow flexion/extension movements. The introduction of joint misalignments in the weight support model significantly reduced the model errors, in terms of weight estimation, and enhanced the estimation reliability. The introduced control architecture reduced model tracking errors regardless of the condition. Weight support significantly decreased the activity of antigravity muscles, as expected, but increased the activity of elbow extensors because gravity is usually exploited by humans to accelerate a limb downwards. These findings suggest that an adaptive weight support controller could be envisioned to further minimize human effort in certain applications.

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

Background: The efficacy of upper-limb Robot-assisted Therapy (ulRT) in stroke subjects is well-established. The robot-measured kinematic data can assess the biomechanical changes induced by ulRT and the progress of patient over time. However, literature on the analysis of pre-treatment kinematic parameters as predictive biomarkers of upper limb recovery is limited.

Objective: The aim of this study was to calculate pre-treatment kinematic parameters from point-to-point reaching movements in different directions and to identify biomarkers of upper-limb motor recovery in subacute stroke subjects after ulRT.

Methods: An observational retrospective study was conducted on 66 subacute stroke subjects who underwent ulRT with an end-effector robot. Kinematic parameters were calculated from the robot-measured trajectories during movements in different directions. A Generalized Linear Model (GLM) was applied considering the post-treatment Upper Limb Motricity Index and the kinematic parameters (from demanding directions of movement) as dependent variables, and the pre-treatment kinematic parameters as independent variables.

Results: A subset of kinematic parameters significantly predicted the motor impairment after ulRT: the accuracy in adduction and internal rotation movements of the shoulder was the major predictor of post-treatment Upper Limb Motricity Index. The post-treatment kinematic parameters of the most demanding directions of movement significantly depended on the ability to execute elbow flexion-extension and abduction and external rotation movements of the shoulder at baseline.

Conclusions: The multidirectional analysis of robot-measured kinematic data predicts motor recovery in subacute stroke survivors and paves the way in identifying subjects who may benefit more from ulRT.

Predictors of high dose of massed practice following stroke

Objective

The aim of this study is to determine the factors that affect patients' ability to carry out high dose of massed practice.

Methods

Patients with stroke were included in the study if they had no severe impairment in motor and cognitive functions. Dose of massed practice, motor function, perceived amount and quality of use of the arm in the real world, wrist and elbow flexors spasticity, dominant hand stroke, presence of shoulder pain, and central post-stroke pain were assessed on the first day. Dose of massed practice was assessed again on the second day. The data were analyzed using descriptive statistics and linear multiple regression.

Results

Only motor function (β = -0.310, r = 0.787, P < 0.001), perceived amount of use (β = 0.300, r = 0.823; 95% CI = 0.34-107.224, P = 0.049), severity of shoulder pain (β = -0.155, r = -0.472, P = 0.019), wrist flexors spasticity (β = -0.154, r = -0.421, P = 0.002), age (β = -0.129, r = -0.366, P = 0.018), dominant hand stroke (β = -0.091, r = -0.075, P = 0.041), and sex (β = -0.090, r = -0.161, P = 0.036) significantly influenced patients' ability to carry out high dose of massed practice.

Conclusion

Many factors affect patients' ability to carry out high dose of massed practice. Understanding these factors can help in designing appropriate rehabilitation.

Haptic Training: Which Types Facilitate (re)Learning of Which Motor Task and for Whom? Answers by a Review

The use of robots has attracted researchers to design numerous haptic training methods to support motor learning. However, investigations of new methods yielded inconclusive results regarding their effectiveness to enhance learning due to the diversity of tasks, haptic designs, participants' skill level, and study protocols. In this review, we developed a taxonomy to identify generalizable findings out of publications on haptic training. In the taxonomy, we grouped the results of studies on healthy learners based on participants' skill level and tasks' characteristics. Our inspection of included studies revealed that: i) Performance-enhancing haptic methods were beneficial for novices, ii) Training with haptics was as effective as training with other feedback modalities, and iii) Performance-enhancing and performance-degrading haptic methods were useful for the learning of temporal and spatial aspects, respectively. We also observed that these findings are in line with results from robot-aided neurorehabilitation studies on patients. Our review suggests that haptic training can be effective to foster learning, especially when the information cannot be provided with other feedback modalities. We believe the findings from the taxonomy constitute a general guide, which can assist researchers when designing studies to investigate the effectiveness of haptics on learning different tasks.

Effect of post-stroke spasticity on voluntary movement of the upper limb

Background

Hemiparesis following stroke is often accompanied by spasticity. Spasticity is one factor among the multiple components of the upper motor neuron syndrome that contributes to movement impairment. However, the specific contribution of spasticity is difficult to isolate and quantify. We propose a new method of quantification and evaluation of the impact of spasticity on the quality of movement following stroke.

Methods

Spasticity was assessed using the Tonic Stretch Reflex Threshold (TSRT). TSRT was analyzed in relation to stochastic models of motion to quantify the deviation of the hemiparetic upper limb motion from the normal motion patterns during a reaching task. Specifically, we assessed the impact of spasticity in the elbow flexors on reaching motion patterns using two distinct measures of the ‘distance’ between pathological and normal movement, (a) the bidirectional Kullback–Liebler divergence (BKLD) and (b) Hellinger’s distance (HD). These measures differ in their sensitivity to different confounding variables. Motor impairment was assessed clinically by the Fugl-Meyer assessment scale for the upper extremity (FMA-UE). Forty-two first-event stroke patients in the subacute phase and 13 healthy controls of similar age participated in the study. Elbow motion was analyzed in the context of repeated reach-to-grasp movements towards four differently located targets. Log-BKLD and HD along with movement time, final elbow extension angle, mean elbow velocity, peak elbow velocity, and the number of velocity peaks of the elbow motion were computed.

Results

Upper limb kinematics in patients with lower FMA-UE scores (greater impairment) showed greater deviation from normality when the distance between impaired and normal elbow motion was analyzed either with the BKLD or HD measures. The severity of spasticity, reflected by the TSRT, was related to the distance between impaired and normal elbow motion analyzed with either distance measure. Mean elbow velocity differed between targets, however HD was not sensitive to target location. This may point at effects of spasticity on motion quality that go beyond effects on velocity.

Conclusions

The two methods for analyzing pathological movement post-stroke provide new options for studying the relationship between spasticity and movement quality under different spatiotemporal constraints.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Towards a Platform for Robot-Assisted Minimally-Supervised Therapy of Hand Function: Design and Pilot Usability Evaluation

Background

Robot-assisted therapy can increase therapy dose after stroke, which is often considered insufficient in clinical practice and after discharge, especially with respect to hand function. Thus far, there has been a focus on rather complex systems that require therapist supervision. To better exploit the potential of robot-assisted therapy, we propose a platform designed for minimal therapist supervision, and present the preliminary evaluation of its immediate usability, one of the main and frequently neglected challenges for real-world application. Such an approach could help increase therapy dose by allowing the training of multiple patients in parallel by a single therapist, as well as independent training in the clinic or at home.

Methods

We implemented design changes on a hand rehabilitation robot, considering aspects relevant to enabling minimally-supervised therapy, such as new physical/graphical user interfaces and two functional therapy exercises to train hand motor coordination, somatosensation and memory. Ten participants with chronic stroke assessed the usability of the platform and reported the perceived workload during a single therapy session with minimal supervision. The ability to independently use the platform was evaluated with a checklist.

Results

Participants were able to independently perform the therapy session after a short familiarization period, requiring assistance in only 13.46 (7.69–19.23)% of the tasks. They assigned good-to-excellent scores on the System Usability Scale to the user-interface and the exercises [85.00 (75.63–86.88) and 73.75 (63.13–83.75) out of 100, respectively]. Nine participants stated that they would use the platform frequently. Perceived workloads lay within desired workload bands. Object grasping with simultaneous control of forearm pronosupination and stiffness discrimination were identified as the most difficult tasks.

Discussion

Our findings demonstrate that a robot-assisted therapy device can be rendered safely and intuitively usable upon first exposure with minimal supervision through compliance with usability and perceived workload requirements. The preliminary usability evaluation identified usability challenges that should be solved to allow real-world minimally-supervised use. Such a platform could complement conventional therapy, allowing to provide increased dose with the available resources, and establish a continuum of care that progressively increases therapy lead of the patient from the clinic to the home.

Review: How Can Intelligent Robots and Smart Mechatronic Modules Facilitate Remote Assessment, Assistance, and Rehabilitation for Isolated Adults With Neuro-Musculoskeletal Conditions?

Worldwide, at the time this article was written, there are over 127 million cases of patients with a confirmed link to COVID-19 and about 2.78 million deaths reported. With limited access to vaccine or strong antiviral treatment for the novel coronavirus, actions in terms of prevention and containment of the virus transmission rely mostly on social distancing among susceptible and high-risk populations. Aside from the direct challenges posed by the novel coronavirus pandemic, there are serious and growing secondary consequences caused by the physical distancing and isolation guidelines, among vulnerable populations. Moreover, the healthcare system's resources and capacity have been focused on addressing the COVID-19 pandemic, causing less urgent care, such as physical neurorehabilitation and assessment, to be paused, canceled, or delayed. Overall, this has left elderly adults, in particular those with neuromusculoskeletal (NMSK) conditions, without the required service support. However, in many cases, such as stroke, the available time window of recovery through rehabilitation is limited since neural plasticity decays quickly with time. Given that future waves of the outbreak are expected in the coming months worldwide, it is important to discuss the possibility of using available technologies to address this issue, as societies have a duty to protect the most vulnerable populations. In this perspective review article, we argue that intelligent robotics and wearable technologies can help with remote delivery of assessment, assistance, and rehabilitation services while physical distancing and isolation measures are in place to curtail the spread of the virus. By supporting patients and medical professionals during this pandemic, robots, and smart digital mechatronic systems can reduce the non-COVID-19 burden on healthcare systems. Digital health and cloud telehealth solutions that can complement remote delivery of assessment and physical rehabilitation services will be the subject of discussion in this article due to their potential in enabling more effective and safer NMSDK rehabilitation, assistance, and assessment service delivery. This article will hopefully lead to an interdisciplinary dialogue between the medical and engineering sectors, stake holders, and policy makers for a better delivery of care for those with NMSK conditions during a global health crisis including future pandemics.

Three-Dimensional Assessment of Upper Limb Proprioception via a Wearable Exoskeleton

Proprioception—the sense of body segment’s position and movement—plays a crucial role in human motor control, integrating the sensory information necessary for the correct execution of daily life activities. Despite scientific evidence recognizes that several neurological diseases hamper proprioceptive encoding with consequent inability to correctly perform movements, proprioceptive assessment in clinical settings is still limited to standard scales. Literature on physiology of upper limb’s proprioception is mainly focused on experimental approaches involving planar setups, while the present work provides a novel paradigm for assessing proprioception during single—and multi-joint matching tasks in a three-dimensional workspace. To such extent, a six-degrees of freedom exoskeleton, ALEx-RS (Arm Light Exoskeleton Rehab Station), was used to evaluate 18 healthy subjects’ abilities in matching proprioceptive targets during combined single and multi-joint arm’s movements: shoulder abduction/adduction, shoulder flexion/extension, and elbow flexion/extension. Results provided evidence that proprioceptive abilities depend on the number of joints simultaneously involved in the task and on their anatomical location, since muscle spindles work along their preferred direction, modulating the streaming of sensory information accordingly. These findings suggest solutions for clinical sensorimotor evaluation after neurological disease, where assessing proprioceptive deficits can improve the recovery path and complement the rehabilitation outcomes.

Robotic Assessment of Wrist Proprioception During Kinaesthetic Perturbations: A Neuroergonomic Approach

Position sense refers to an aspect of proprioception crucial for motor control and learning. The onset of neurological diseases can damage such sensory afference, with consequent motor disorders dramatically reducing the associated recovery process. In regular clinical practice, assessment of proprioceptive deficits is run by means of clinical scales which do not provide quantitative measurements. However, existing robotic solutions usually do not involve multi-joint movements but are mostly applied to a single proximal or distal joint. The present work provides a testing paradigm for assessing proprioception during coordinated multi-joint distal movements and in presence of kinaesthetic perturbations: we evaluated healthy subjects' ability to match proprioceptive targets along two of the three wrist's degrees of freedom, flexion/extension and abduction/adduction. By introducing rotations along the pronation/supination axis not involved in the matching task, we tested two experimental conditions, which differed in terms of the temporal imposition of the external perturbation: in the first one, the disturbance was provided after the presentation of the proprioceptive target, while in the second one, the rotation of the pronation/ supination axis was imposed during the proprioceptive target presentation. We investigated if (i) the amplitude of the perturbation along the pronation/supination would lead to proprioceptive miscalibration; (ii) the encoding of proprioceptive target, would be influenced by the presentation sequence between the target itself and the rotational disturbance. Eighteen participants were tested by means of a haptic neuroergonomic wrist device: our findings provided evidence that the order of disturbance presentation does not alter proprioceptive acuity. Yet, a further effect has been noticed: proprioception is highly anisotropic and dependent on perturbation amplitude. Unexpectedly, the configuration of the forearm highly influences sensory feedbacks, and significantly alters subjects' performance in matching the proprioceptive targets, defining portions of the wrist workspace where kinaesthetic and proprioceptive acuity are more sensitive. This finding may suggest solutions and applications in multiple fields: from general haptics where, knowing how wrist configuration influences proprioception, might suggest new neuroergonomic solutions in device design, to clinical evaluation after neurological damage, where accurately assessing proprioceptive deficits can dramatically complement regular therapy for a better prediction of the recovery path.

Somatosensory deafferentation reveals lateralized roles of proprioception in feedback and adaptive feedforward control of movement and posture

Proprioception provides crucial information necessary for determining limb position and movement, and plausibly also for updating internal models that might underlie the control of movement and posture. Seminal studies of upper-limb movements in individuals living with chronic, large fiber deafferentation have provided evidence for the role of proprioceptive information in the hypothetical formation and maintenance of internal models to produce accurate motor commands. Vision also contributes to sensorimotor functions but cannot fully compensate for proprioceptive deficits. More recent work has shown that posture and movement control processes are lateralized in the brain, and that proprioception plays a fundamental role in coordinating the contributions of these processes to the control of goal-directed actions. In fact, the behavior of each limb in a deafferented individual resembles the action of a controller in isolation. Proprioception, thus, provides state estimates necessary for the nervous system to efficiently coordinate multiple motor control processes.

Precision implementation of early ambulation in elderly patients undergoing off-pump coronary artery bypass graft surgery: a randomized-controlled clinical trial

Background

Although early ambulation (EA) is associated with improved outcomes in post-operative patients, implementation of EA in elderly patients is still a challenge. In this study, we aimed to design and assess a precision early ambulation program for cardiac rehabilitation.

Methods

We conducted a single-center, randomized and controlled clinical trial in elderly patients aged over 60 years after off-pump coronary artery bypass graft (OPCABG) surgery. Patients were randomly assigned to a precision early ambulation (PEA) group or a routine ambulation (Control) group. Age-predicted maximal heart rate (APMHR) and maximal oxygen uptake (VO_2max) were used as a reference to formulate and monitor the PEA regimen. The primary end-point was the postoperative length of stay in hospital (PLOS). The secondary end-points included 90-day mortality, incidence of early discharge, laboratory tests, length of ICU stay, the incidence of multiple organ complications and post-traumatic stress disorder (PTSD). Ambulation outcomes were also recorded.

Results

In total, 178 patients were enrolled (n = 89 per group). In the intent-to-treat analysis, PLOS in the PEA group was shorter than that in the Control group (9.04 ± 3.08 versus 10.09 ± 3.32 days, respectively. Mean difference 1.045 days; 95% confidence interval [CI] 0.098–1.992; P = 0.031 in the unadjusted model; mean difference 0.957 days; CI 0.007–1.907; P = 0.048 in adjusted model). The incidence of early discharge differed significantly between the PEA and control groups (41[46.1%] versus 24[27.0%] patients, respectively. Odds ratio [OR] 0.432; CI 0.231–0.809; P = 0.009 in unadjusted model; OR 0.466; CI 0.244–0.889, P = 0.02 in adjusted model). The time of first bowel movement, partial pressure O₂ and post-traumatic stress disorder score in the PEA group were better than those in the Control group. Participants walked much longer distances on day 3 in the PEA group than those in the Control group (76.12 ± 29.02 versus 56.80 ± 24.40 m, respectively, P < 0.001).

Conclusion

APMHR and VO_2max are valuable for implementation of PEA according to an established security threshold. PEA after OPCAPG surgery is safe and reliable for elderly patients, not only reducing the hospital stay, but also improving their physiological and psychological symptoms.

Trial registration

This study is a component of a protocol retrospectively registered: Application of ERAS in cardiovascular surgery. Trial registration number: ChiCTR1800018167. Date of registration: 3rd September, 2018. URL of trial registry record: http://www.chictr.org.cn/index.aspx