Measures of Interjoint Coordination Post-stroke Across Different Upper Limb Movement Tasks

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

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

Upper limb motor dysfunction is associated with fragmented kinetics after brain injury

BACKGROUND

Characterization of motor deficits after brain injury is important for rehabilitation personalization. While studies reported abnormalities in the kinematics of paretic and non-paretic elbow extension for patients with brain injuries, kinematic analysis is not sufficient to explore how patients deal with musculoskeletal redundancy and the energetic aspect of movement execution. Conversely, interarticular coordination and movement kinetics can reflect patients' motor strategies. This study investigates motor strategies of paretic and non-paretic upper limb after brain injury to highlight motor deficits or compensation strategies.

METHODS

26 brain-injured hemiplegic patients and 24 healthy controls performed active elbow extensions in the horizontal plane, with both upper limbs for patients and, with the dominant upper limb for controls. Elbow and shoulder kinematics, interarticular coordination, net joint kinetics were quantified.

FINDINGS

Results show alterations in kinematics, and a strong correlation between elbow and shoulder angles, as well as time to reach elbow and shoulder peak angular velocity in both upper limbs of patients. Net joint kinetics were lower for paretic limb and highlighted a fragmented motor strategy with increased number of transitions between concentric and eccentric phases.

INTERPRETATION

In complement to kinematic results, our kinetic results confirmed patients' difficulties to manage both spatially and temporally the joint degrees of freedom redundancy but revealed a fragmented compensatory motor strategy allowing patients upper limb extension despite quality alteration and decrease in energy efficiency. Motor rehabilitation should improve the management of this fragmentation strategy to improve the performance and the efficiency of active movement after brain injury.

Upper limb assessment with inertial measurement units according to the international classification of functioning in stroke: a systematic review and correlation meta-analysis

OBJECTIVE

To investigate the usefulness of inertial measurement units (IMUs) in the assessment of motor function of the upper limb (UL) in accordance with the international classification of functioning (ICF).

DATA SOURCES

PubMed; Scopus; Embase; WoS and PEDro databases were searched from inception to 1 February 2022.

METHODS

The current systematic review follows PRISMA recommendations. Articles including IMU assessment of UL in stroke individuals have been included and divided into four ICF categories (b710, b735, b760, d445). We used correlation meta-analysis to pool the Fisher Z-score of each correlation between kinematics and clinical assessment.

RESULTS

A total of 35 articles, involving 475 patients, met the inclusion criteria. In the included studies, IMUs have been employed to assess the mobility of joint functions (n = 6), muscle tone functions (n = 4), control of voluntary movement functions (n = 15), and hand and arm use (n = 15). A significant correlation was found in overall meta-analysis based on 10 studies, involving 213 subjects: (r = 0.69) (95% CI: 0.69/0.98; p < 0.001) as in the d445 (r = 0.71) and b760 (r = 0.64) ICF domains, with no heterogeneity across the studies.

CONCLUSION

The literature supports the integration of IMUs and conventional clinical assessment in functional evaluation of the UL after a stroke. The use of a limited number of wearable sensors can provide additional kinematic features of UL in all investigated ICF domains, especially in the ADL tasks when a strong correlation with clinical evaluation was found.

Upper extremity kinematics: development of a quantitative measure of impairment severity and dissimilarity after stroke

Background

Strokes are a leading cause of disability worldwide, with many survivors experiencing difficulty in recovering upper extremity movement, particularly hand function and grasping ability. There is currently no objective measure of movement quality, and without it, rehabilitative interventions remain at best informed estimations of the underlying neural structures' response to produce movement. In this article, we utilize a novel modification to Procrustean distance to quantify curve dissimilarity and propose the Reach Severity and Dissimilarity Index (RSDI) as an objective measure of motor deficits.

Methods

All experiments took place at the Medstar National Rehabilitation Hospital; persons with stroke were recruited from the hospital patient population. Using Fugl-Meyer (FM) scores and reach capacities, stroke survivors were placed in either mild or severe impairment groups. Individuals completed sets of reach-to-target tasks to extrapolate kinematic metrics describing motor performance. The Procrustes method of statistical shape analysis was modified to identify reaching sub-movements that were congruous to able-bodied sub-movements.

Findings

Movement initiation proceeds comparably to the reference curve in both two- and three-dimensional representations of mild impairment movement. There were significant effects of the location of congruent segments between subject and reference curves, mean velocities, peak roll angle, and target error. These metrics were used to calculate a preliminary RSDI score with severity and dissimilarity sub-scores, and subjects were reclassified in terms of rehabilitation goals as Speed Emphasis, Strength Emphasis, and Combined Emphasis.

Interpretation

The modified Procrustes method shows promise in identifying disruptions in movement and monitoring recovery without adding to patient or clinician burden. The proposed RSDI score can be adapted and expanded to other functional movements and used as an objective clinical tool. By reducing the impact of stroke on disability, there is a significant potential to improve quality of life through individualized rehabilitation.

Hand-worn devices for assessment and rehabilitation of motor function and their potential use in BCI protocols: a review

Introduction

Various neurological conditions can impair hand function. Affected individuals cannot fully participate in activities of daily living due to the lack of fine motor control. Neurorehabilitation emphasizes repetitive movement and subjective clinical assessments that require clinical experience to administer.

Methods

Here, we perform a review of literature focused on the use of hand-worn devices for rehabilitation and assessment of hand function. We paid particular attention to protocols that involve brain-computer interfaces (BCIs) since BCIs are gaining ground as a means for detecting volitional signals as the basis for interactive motor training protocols to augment recovery. All devices reviewed either monitor, assist, stimulate, or support hand and finger movement.

Results

A majority of studies reviewed here test or validate devices through clinical trials, especially for stroke. Even though sensor gloves are the most commonly employed type of device in this domain, they have certain limitations. Many such gloves use bend or inertial sensors to monitor the movement of individual digits, but few monitor both movement and applied pressure. The use of such devices in BCI protocols is also uncommon.

Discussion

We conclude that hand-worn devices that monitor both flexion and grip will benefit both clinical diagnostic assessment of function during treatment and closed-loop BCI protocols aimed at rehabilitation.

Exercise repetition rate measured with simple sensors at home can be used to estimate Upper Extremity Fugl-Meyer score after stroke

Introduction

It would be valuable if home-based rehabilitation training technologies could automatically assess arm impairment after stroke. Here, we tested whether a simple measure-the repetition rate (or "rep rate") when performing specific exercises as measured with simple sensors-can be used to estimate Upper Extremity Fugl-Meyer (UEFM) score.

Methods

41 individuals with arm impairment after stroke performed 12 sensor-guided exercises under therapist supervision using a commercial sensor system comprised of two pucks that use force and motion sensing to measure the start and end of each exercise repetition. 14 of these participants then used the system at home for three weeks.

Results

Using linear regression, UEFM score was well estimated using the rep rate of one forward-reaching exercise from the set of 12 exercises (r² = 0.75); this exercise required participants to alternately tap pucks spaced about 20 cm apart (one proximal, one distal) on a table in front of them. UEFM score was even better predicted using an exponential model and forward-reaching rep rate (Leave One Out Cross Validation (LOOCV) r² = 0.83). We also tested the ability of a nonlinear, multivariate model (a regression tree) to predict UEFM, but such a model did not improve prediction (LOOCV r² = 0.72). However, the optimal decision tree also used the forward-reaching task along with a pinch grip task to subdivide more and less impaired patients in a way consistent with clinical intuition. At home, rep rate for the forward-reaching exercise well predicted UEFM score using an exponential model (LOOCV r² = 0.69), but only after we re-estimated coefficients using the home data.

Discussion

These results show how a simple measure-exercise rep rate measured with simple sensors-can be used to infer an arm impairment score and suggest that prediction models should be tuned separately for the clinic and home environments.

Automatic Post-Stroke Severity Assessment Using Novel Unsupervised Consensus Learning for Wearable and Camera-Based Sensor Datasets

Stroke survivors often suffer from movement impairments that significantly affect their daily activities. The advancements in sensor technology and IoT have provided opportunities to automate the assessment and rehabilitation process for stroke survivors. This paper aims to provide a smart post-stroke severity assessment using AI-driven models. With the absence of labelled data and expert assessment, there is a research gap in providing virtual assessment, especially for unlabeled data. Inspired by the advances in consensus learning, in this paper, we propose a consensus clustering algorithm, PSA-NMF, that combines various clusterings into one united clustering, i.e., cluster consensus, to produce more stable and robust results compared to individual clustering. This paper is the first to investigate severity level using unsupervised learning and trunk displacement features in the frequency domain for post-stroke smart assessment. Two different methods of data collection from the U-limb datasets-the camera-based method (Vicon) and wearable sensor-based technology (Xsens)-were used. The trunk displacement method labelled each cluster based on the compensatory movements that stroke survivors employed for their daily activities. The proposed method uses the position and acceleration data in the frequency domain. Experimental results have demonstrated that the proposed clustering method that uses the post-stroke assessment approach increased the evaluation metrics such as accuracy and F-score. These findings can lead to a more effective and automated stroke rehabilitation process that is suitable for clinical settings, thus improving the quality of life for stroke survivors.

Quantitative Assessment of Upper Limb Movement in Post-Stroke Adults for Identification of Sensitive Measures in Reaching and Lifting Activities

BACKGROUND

The assumption of this work is the achievement of objective results of the movement structure, which forms the basis for in-depth analysis and, consequently, for determining the upper limb movements that are most affected by stroke compared to healthy people.

METHODS

An analysis of relevant and systematically identified features of upper limb movement in post-stroke adults is presented based on scalable hypothesis tests. The basic features were calculated using movements defined by the x, y, and z coordinates (i.e., 3D trajectory time series) and compared to the results of post-stroke patients with healthy controls of similar age.

RESULTS

After automatic feature selection, out of the 1004 common features of upper limb movement, the most differentiated were the upper arm movements in reaching kinematics. In terms of movement type, movements in the frontal plane (shoulder abduction and adduction) were the most sensitive to changes. The largest number of discriminating features was determined on the basis of acceleration time series.

CONCLUSIONS

In the 3D assessment of functional activities of the upper limb, the upper arm turned out to be the most differentiated body segment, especially during abduction and adduction movements. The results indicate a special need to pay attention to abduction and adduction movements to improve the activities of daily living of the upper limbs after a stroke.

Identification of inverse kinematic parameters in redundant systems: Towards quantification of inter-joint coordination in the human upper extremity

Understanding and quantifying inter-joint coordination is valuable in several domains such as neurorehabilitation, robot-assisted therapy, robotic prosthetic arms, and control of supernumerary arms. Inter-joint coordination is often understood as a consistent spatiotemporal relation among kinematically redundant joints performing functional and goal-oriented movements. However, most approaches in the literature to investigate inter-joint coordination are limited to analysis of the end-point trajectory or correlation analysis of the joint rotations without considering the underlying task; e.g., creating a desirable hand movement toward a goal as in reaching motions. This work goes beyond this limitation by taking a model-based approach to quantifying inter-joint coordination. More specifically, we use the weighted pseudo-inverse of the Jacobian matrix and its associated null-space to explain the human kinematics in reaching tasks. We propose a novel algorithm to estimate such Inverse Kinematics weights from observed kinematic data. These estimated weights serve as a quantification for spatial inter-joint coordination; i.e., how costly a redundant joint is in its contribution to creating an end-effector velocity. We apply our estimation algorithm to datasets obtained from two different experiments. In the first experiment, the estimated Inverse Kinematics weights pinpoint how individuals change their Inverse Kinematics strategy when exposed to the viscous field wearing an exoskeleton. The second experiment shows how the resulting Inverse Kinematics weights can quantify a robotic prosthetic arm's contribution (or the level of assistance).

Is There a Relation between Brain and Muscle Activity after Virtual Reality Training in Individuals with Stroke? A Cross-Sectional Study

Objective-The aim was to verify the correlation between cerebral and muscular electrical activity in subjects trained in virtual reality after a stroke. Method-The trial design was a cross-sectional study. Fourteen volunteers who were diagnosed with a stroke participated in the study. The intervention protocol was to perform functional activity with an upper limb using virtual reality. The functional protocol consisted of four one-minute series with a two-minute interval between series in a single session. Results-We observed, at initial rest, a positive correlation between brachii biceps and the frontal canal medial region (F7/F8) (r = 0.59; p = 0.03) and frontal canal lateral region (F3/F4) (r = 0.71; p = 0.006). During the activity, we observed a positive correlation between the anterior deltoid and frontal anterior channel (AF3/AF4) (r = 0.73; p = 0.004). At final rest, we observed a positive correlation between the anterior deltoid and temporal region channel (T7/T8) (r = 0.70; p = 0.005). Conclusions-We conclude that there was no correlation between brain and muscle activity for the biceps brachii muscle in subjects trained with virtual reality. However, there was a positive correlation for the deltoid anterior muscle.

An Analysis of Lower Limb Coordination Variability in Unilateral Tasks in Healthy Adults: A Possible Prognostic Tool

Interlimb coordination variability analysis can shed light into the dynamics of higher order coordination and motor control. However, it is not clear how the interlimb coordination of people with no known injuries change in similar activities with increasing difficulty. This study aimed to ascertain if the interlimb coordination variability range and patterns of healthy participants change in different unilateral functional tasks with increasing complexity and whether leg dominance affects the interlimb coordination variability. In this cross-sectional study fourteen younger participants with no known injuries completed three repeated unilateral sit-to-stands (UniSTS), step-ups (SUs), and continuous-hops (Hops). Using four inertial sensors mounted on the lower legs and thighs, angular rotation of thighs and shanks were recorded. Using Hilbert transform, the phase angle of each segment and then the continuous relative phase (CRP) of the two segments were measured. The CRP is indicative of the interlimb coordination. Finally, the linear and the nonlinear shank-thigh coordination variability of each participant in each task was calculated. The results show that the linear shank-thigh coordination variability was significantly smaller in the SUs compared to both UniSTS and Hops in both legs. There were no significant differences found between the latter two tests in their linear coordination variability. However, Hops were found to have significantly larger nonlinear shank-thigh coordination variability compared to the SUs and the UniSTS. This can be due to larger vertical and horizontal forces required for the task and can reveal inadequate motor control during the movement. The combination of nonlinear and linear interlimb coordination variability can provide more insight into human movement as they measure different aspects of coordination variability. It was also seen that leg dominance does not affect the lower limb coordination variability in participants with no known injuries. The results should be tested in participants recovering from lower limb injuries.

The Use of Armeo®Spring Device to Assess the Effect of Trunk Stabilization Exercises on the Functional Capabilities of the Upper Limb-An Observational Study of Patients after Stroke

Almost half of stroke patients report impaired function of the upper limb and hand. Stability of the trunk is required for the proper movement of the body, including the legs and arms. The aim of the study was to analyze the effect of trunk stabilization exercises on coordinated movement of the affected upper limb in patients after stroke, using an Armoe®Spring device and the “wall” and “abacus” functional tests. Materials and methods: This is a randomized, double-blinded study. The research was carried out in the Rehabilitation Clinic on a group of 60 stroke patients who were randomly assigned to groups differing in the rehabilitation program. The study group had physiotherapy based on the NDT Bobath concept and the control group used classic exercises. The importance of the trunk for upper limb coordination was assessed on the Armeo®Spring device using three evaluation programs, “perpendicular fishing”; “horizontal fishing”; “reaction time”, and two proprietary tests, “wall” and “abacus”. Results: The post-treatment analysis showed significantly better results in the study group for the abacus (p < 0.001), wall (p = 0.003) tests, and a significantly higher percentage of task completion in the vertical fishing (p = 0.036) and reaction time (p = 0.009) tests. Conclusions: Physiotherapy including exercises to stabilize the trunk had a significant effect on increasing the functional efficiency of the affected upper limb and on improving the handgrip strength. The Armeo®Spring device is a good device for the functional assessment of the upper limb before and after therapy.

Kinematic Evaluation via Inertial Measurement Unit Associated with Upper Extremity Motor Function in Subacute Stroke: A Cross-Sectional Study

Kinematic evaluation via portable sensor system has been increasingly applied in neurological sciences and clinical practice. However, conventional kinematic evaluation rarely extends the context beyond the motor impairment level. In addition, kinematic tasks with numerous items could be complex and time consuming that pose a burden to test applications and data processing. The study aimed to explore the correlation of finger-to-nose task (FNT) kinematics via Inertial Measurement Unit with upper limb motor function in subacute stroke. In this study, six FNT kinematic variables were used to measure movement time, smoothness, and velocity in 37 participants with subacute stroke. Upper limb motor function was evaluated with the Fugl-Meyer Assessment for Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), and modified Barthel Index (MBI). As a result, mean velocity, peak velocity, and the number of movement units were associated with the clinical assessments. The multivariable linear regression models could estimate 55%, 51%, and 32% of variance in FMA-UE, ARAT, and MBI, respectively. In addition, age, gender, type of stroke, and paretic side had no significant effects on these associations. Results show that FNT kinematic variables measured via Inertial Measurement Unit are associated with upper extremity motor function in individuals with subacute stroke. The objective kinematic evaluation may be suitable for predicting clinical measures of motor impairment and capacity to understand upper extremity motor recovery and clinical decision making after stroke. This trial is registered with ChiCTR1900026656.